From dbbb1eadeb4326a8f30f8430e58521612f50286a Mon Sep 17 00:00:00 2001 From: Greenmask CI Date: Sat, 16 Nov 2024 21:33:09 +0000 Subject: [PATCH] Deployed 63dc967 to v0.2.5 with MkDocs 1.6.1 and mike 2.1.3 --- latest | 2 +- v0.2.5/404.html | 3088 ++++++++ v0.2.5/architecture/index.html | 3418 +++++++++ v0.2.5/assets/built_in_transformers/img.png | Bin 0 -> 16273 bytes .../built_in_transformers/orders-schema.png | Bin 0 -> 20480 bytes .../person-person-schema.png | Bin 0 -> 45160 bytes v0.2.5/assets/images/favicon.png | Bin 0 -> 1870 bytes v0.2.5/assets/images/social/architecture.png | Bin 0 -> 25054 bytes .../custom_functions/core_functions.png | Bin 0 -> 35176 bytes .../custom_functions/faker_function.png | Bin 0 -> 27563 bytes .../custom_functions/index.png | Bin 0 -> 35677 bytes .../advanced_transformers/index.png | Bin 0 -> 35745 bytes .../advanced_transformers/json.png | Bin 0 -> 22432 bytes .../advanced_transformers/template.png | Bin 0 -> 23470 bytes 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b/latest @@ -1 +1 @@ -v0.2.4 \ No newline at end of file +v0.2.5 \ No newline at end of file diff --git a/v0.2.5/404.html b/v0.2.5/404.html new file mode 100644 index 00000000..149a7429 --- /dev/null +++ b/v0.2.5/404.html @@ -0,0 +1,3088 @@ + + + + + + + + + + + + + + + + + + + Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Architecture

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Introduction

+

It is evident that the most appropriate approach for executing logical backup dumping and restoration is by leveraging the core PostgreSQL utilities, specifically pg_dump and pg_restore. Greenmask has been purposefully designed to align with PostgreSQL's native utilities, ensuring compatibility. Greenmask primarily handles data dumping operations independently and delegates the responsibilities of schema dumping and restoration to pg_dump and pg_restore respectively, maintaining seamless integration with PostgreSQL's standard tools.

+

Backup process

+

The process of backing up PostgreSQL databases is divided into three distinct sections:

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  • Pre-data — this section encompasses the raw schema of tables, excluding primary keys (PK) and foreign keys (FK).
    • +
  • Data — the data section contains the actual table data in COPY format, including information about sequence current values and Large Objects data.
    • +
  • Post-data — in this section, you'll find the definitions of indexes, triggers, rules, and constraints (such as PK and FK).
    • +
+

Greenmask focuses exclusively on the data section during runtime. It delegates the handling of the pre-data and post-data sections to the core PostgreSQL utilities, pg_dump and pg_restore.

+

Greenmask employs the directory format of pg_dump and pg_restore. This format is particularly suitable for +parallel execution and partial restoration, and it includes clear metadata files that aid in determining the backup and restoration steps. Greenmask has been optimized to work seamlessly with remote storage systems and anonymization procedures.

+

When performing data dumping, Greenmask utilizes the COPY command in TEXT format, maintaining reliability and +compatibility with the vanilla PostgreSQL utilities.

+

Additionally, Greenmask supports parallel execution, significantly reducing the time required for the dumping process.

+

Storage options

+

The core PostgreSQL utilities, pg_dump and pg_restore, traditionally operate with files in a directory format, offering no alternative methods. To meet modern backup requirements and provide flexible approaches, +Greenmask introduces the concept of storages.

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  • s3 — this option supports any S3-like storage system, including AWS S3, which makes it versatile and adaptable to various cloud-based storage solutions.
    • +
  • directory — this is the standard choice, representing the ordinary filesystem directory for local storage.
    • +
+

Restoration process

+

In the restoration process, Greenmask combines the capabilities of different tools:

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  • For schema restoration Greenmask utilizes pg_restore to restore the database schema. This ensures that the schema is accurately reconstructed.
    • +
  • For data restoration Greenmask independently applies the data using the COPY protocol. This allows Greenmask to handle the data efficiently, especially when working with various storage solutions. Greenmask is aware of the restoration metadata, which enables it to download only the necessary data. This feature is particularly useful for partial restoration scenarios, such as restoring a single table from a complete backup.
    • +
+

Greenmask also supports parallel restoration, which can significantly reduce the time required to complete the restoration process. This parallel execution enhances the efficiency of restoring large datasets.

+

Data anonymization and validation

+

Greenmask works with COPY lines, collects schema metadata using the Golang driver, and employs this driver in the encoding and decoding process. The validate command offers a way to assess the impact on both schema +(validation warnings) and data (transformation and displaying differences). This command allows you to validate the schema and data transformations, ensuring the desired outcomes during the anonymization process.

+

Customization

+

If your table schema relies on functional dependencies between columns, you can address this challenge using the TemplateRecord transformer. This transformer enables you to define transformation logic for entire tables, offering type-safe operations when assigning new values.

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Greenmask provides a framework for creating your custom transformers, which can be reused efficiently. These +transformers can be seamlessly integrated without requiring recompilation, thanks to the PIPE (stdin/stdout) +interaction.

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Note

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Furthermore, Greenmask's architecture is designed to be highly extensible, making it possible to introduce other interaction protocols, such as HTTP or Socket, for conducting anonymization procedures.

+
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PostgreSQL version compatibility

+

Greenmask is compatible with PostgreSQL versions 11 and higher.

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\n * import { animationFrameScheduler } from 'rxjs';\n *\n * const div = document.querySelector('div');\n *\n * animationFrameScheduler.schedule(function(height) {\n * div.style.height = height + \"px\";\n *\n * this.schedule(height + 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * }, 0, 0);\n *\n * // You will see a div element growing in height\n * ```\n */\n\nexport const animationFrameScheduler = new AnimationFrameScheduler(AnimationFrameAction);\n\n/**\n * @deprecated Renamed to {@link animationFrameScheduler}. Will be removed in v8.\n */\nexport const animationFrame = animationFrameScheduler;\n", "import { Observable } from '../Observable';\nimport { SchedulerLike } from '../types';\n\n/**\n * A simple Observable that emits no items to the Observer and immediately\n * emits a complete notification.\n *\n * Just emits 'complete', and nothing else.\n *\n * ![](empty.png)\n *\n * A simple Observable that only emits the complete notification. It can be used\n * for composing with other Observables, such as in a {@link mergeMap}.\n *\n * ## Examples\n *\n * Log complete notification\n *\n * ```ts\n * import { EMPTY } from 'rxjs';\n *\n * EMPTY.subscribe({\n * next: () => console.log('Next'),\n * complete: () => console.log('Complete!')\n * });\n *\n * // Outputs\n * // Complete!\n * ```\n *\n * Emit the number 7, then complete\n *\n * ```ts\n * import { EMPTY, startWith } from 'rxjs';\n *\n * const result = EMPTY.pipe(startWith(7));\n * result.subscribe(x => console.log(x));\n *\n * // Outputs\n * // 7\n * ```\n *\n * Map and flatten only odd numbers to the sequence `'a'`, `'b'`, `'c'`\n *\n * ```ts\n * import { interval, mergeMap, of, EMPTY } from 'rxjs';\n *\n * const interval$ = interval(1000);\n * const result = interval$.pipe(\n * mergeMap(x => x % 2 === 1 ? of('a', 'b', 'c') : EMPTY),\n * );\n * result.subscribe(x => console.log(x));\n *\n * // Results in the following to the console:\n * // x is equal to the count on the interval, e.g. (0, 1, 2, 3, ...)\n * // x will occur every 1000ms\n * // if x % 2 is equal to 1, print a, b, c (each on its own)\n * // if x % 2 is not equal to 1, nothing will be output\n * ```\n *\n * @see {@link Observable}\n * @see {@link NEVER}\n * @see {@link of}\n * @see {@link throwError}\n */\nexport const EMPTY = new Observable((subscriber) => subscriber.complete());\n\n/**\n * @param scheduler A {@link SchedulerLike} to use for scheduling\n * the emission of the complete notification.\n * @deprecated Replaced with the {@link EMPTY} constant or {@link scheduled} (e.g. `scheduled([], scheduler)`). Will be removed in v8.\n */\nexport function empty(scheduler?: SchedulerLike) {\n return scheduler ? emptyScheduled(scheduler) : EMPTY;\n}\n\nfunction emptyScheduled(scheduler: SchedulerLike) {\n return new Observable((subscriber) => scheduler.schedule(() => subscriber.complete()));\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport function isScheduler(value: any): value is SchedulerLike {\n return value && isFunction(value.schedule);\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\nimport { isScheduler } from './isScheduler';\n\nfunction last(arr: T[]): T | undefined {\n return arr[arr.length - 1];\n}\n\nexport function popResultSelector(args: any[]): ((...args: unknown[]) => unknown) | undefined {\n return isFunction(last(args)) ? args.pop() : undefined;\n}\n\nexport function popScheduler(args: any[]): SchedulerLike | undefined {\n return isScheduler(last(args)) ? args.pop() : undefined;\n}\n\nexport function popNumber(args: any[], defaultValue: number): number {\n return typeof last(args) === 'number' ? args.pop()! : defaultValue;\n}\n", "export const isArrayLike = ((x: any): x is ArrayLike => x && typeof x.length === 'number' && typeof x !== 'function');", "import { isFunction } from \"./isFunction\";\n\n/**\n * Tests to see if the object is \"thennable\".\n * @param value the object to test\n */\nexport function isPromise(value: any): value is PromiseLike {\n return isFunction(value?.then);\n}\n", "import { InteropObservable } from '../types';\nimport { observable as Symbol_observable } from '../symbol/observable';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being Observable (but not necessary an Rx Observable) */\nexport function isInteropObservable(input: any): input is InteropObservable {\n return isFunction(input[Symbol_observable]);\n}\n", "import { isFunction } from './isFunction';\n\nexport function isAsyncIterable(obj: any): obj is AsyncIterable {\n return Symbol.asyncIterator && isFunction(obj?.[Symbol.asyncIterator]);\n}\n", "/**\n * Creates the TypeError to throw if an invalid object is passed to `from` or `scheduled`.\n * @param input The object that was passed.\n */\nexport function createInvalidObservableTypeError(input: any) {\n // TODO: We should create error codes that can be looked up, so this can be less verbose.\n return new TypeError(\n `You provided ${\n input !== null && typeof input === 'object' ? 'an invalid object' : `'${input}'`\n } where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.`\n );\n}\n", "export function getSymbolIterator(): symbol {\n if (typeof Symbol !== 'function' || !Symbol.iterator) {\n return '@@iterator' as any;\n }\n\n return Symbol.iterator;\n}\n\nexport const iterator = getSymbolIterator();\n", "import { iterator as Symbol_iterator } from '../symbol/iterator';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being an Iterable */\nexport function isIterable(input: any): input is Iterable {\n return isFunction(input?.[Symbol_iterator]);\n}\n", "import { ReadableStreamLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport async function* readableStreamLikeToAsyncGenerator(readableStream: ReadableStreamLike): AsyncGenerator {\n const reader = readableStream.getReader();\n try {\n while (true) {\n const { value, done } = await reader.read();\n if (done) {\n return;\n }\n yield value!;\n }\n } finally {\n reader.releaseLock();\n }\n}\n\nexport function isReadableStreamLike(obj: any): obj is ReadableStreamLike {\n // We don't want to use instanceof checks because they would return\n // false for instances from another Realm, like an + + + + + + + + + + + + + + + + + + + + + + + +
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Faker functions

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Greenmask uses go-faker/faker under the hood for generating of synthetic data.

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Faker functions: Address

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FunctionDescriptionSignature
fakerRealAddressGenerates a random real-world address that includes: city, state, postal code, latitude, and longitudefakerRealAddress() (res ReadAddress)
fakerLatitudeGenerates random fake latitudefakerLatitude() (res float64)
fakerLongitudeGenerates random fake longitudefakerLongitude() (res float64)
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Faker functions: Datetime

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FunctionDescriptionSignature
fakerUnixTimeGenerates random Unix time in secondsfakerLongitude() (res int64)
fakerDateGenerates random date with the pattern of YYYY-MM-DDfakerDate() (res string)
fakerTimeStringGenerates random timefakerTimeString() (res string)
fakerMonthNameGenerates a random monthfakerMonthName() (res string)
fakerYearStringGenerates a random yearfakerYearString() (res string)
fakerDayOfWeekGenerates a random day of a weekfakerDayOfWeek() (res string)
fakerDayOfMonthGenerates a random day of a monthfakerDayOfMonth() (res string)
fakerTimestampGenerates a random timestamp with the pattern of YYYY-MM-DD HH:MM:SSfakerTimestamp() (res string)
fakerCenturyGenerates a random centuryfakerCentury() (res string)
fakerTimezoneGenerates a random timezone namefakerTimezone() (res string)
fakerTimeperiodGenerates a random time period with the patter of either AM or PMfakerTimeperiod() (res string)
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Faker functions: Internet

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FunctionDescriptionSignature
fakerEmailGenerates a random emailfakerEmail() (res string)
fakerMacAddressGenerates a random MAC addressfakerMacAddress() (res string)
fakerDomainNameGenerates a random domain namefakerDomainName() (res string)
fakerURLGenerates a random URL with the pattern of https://www.domainname.some/somepathfakerURL() (res string)
fakerUsernameGenerates a random usernamefakerUsername() (res string)
fakerIPv4Generates a random IPv4 addressfakerIPv4() (res string)
fakerIPv6Generates a random IPv6 addressfakerIPv6() (res string)
fakerPasswordGenerates a random passwordfakerPassword() (res string)
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Faker functions: words and sentences

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FunctionDescriptionSignature
fakerWordGenerates a random wordfakerWord() (res string)
fakerSentenceGenerates a random sentencefakerSentence() (res string)
fakerParagraphGenerates a random sequence of sentences as a paragraphfakerParagraph() (res string)
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Faker functions: Payment

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FunctionDescriptionSignature
fakerCCTypeGenerates a random credit card type, e.g. VISA, MasterCard, etc.fakerCCType() (res string)
fakerCCNumberGenerates a random credit card numberfakerCCNumber() (res string)
fakerCurrencyGenerates a random currency namefakerCurrency() (res string)
fakerAmountWithCurrencyGenerates random amount preceded with random currencyfakerAmountWithCurrency() (res string)
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Faker functions: Person

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FunctionDescriptionSignature
fakerTitleMaleGenerates a random male title from the predefined listfakerTitleMale() (res string)
fakerTitleFemaleGenerates a random female title from the predefined listfakerTitleFemale() (res string)
fakerFirstNameGenerates a random first namefakerFirstName() (res string)
fakerFirstNameMaleGenerates a random male first namefakerFirstNameMale() (res string)
fakerFirstNameFemaleGenerates a random female first namefakerFirstNameFemale() (res string)
fakerFirstLastNameGenerates a random last namefakerFirstLastName() (res string)
fakerNameGenerates a random full name preceded with a titlefakerName() (res string)
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Faker functions: Phone

+ + + + + + + + + + + + + + + + + + + + + + + + + +
FunctionDescriptionSignature
fakerPhoneNumberGenerates a random phone numberfakerPhoneNumber() (res string)
fakerTollFreePhoneNumberGenerates a random phone number with the pattern of (123) 456-7890fakerTollFreePhoneNumber() (res string)
fakerE164PhoneNumberGenerates a random phone number with the pattern of +12345678900fakerE164PhoneNumber() (res string)
+

Faker functions: UUID

+ + + + + + + + + + + + + + + + + + + + +
FunctionDescriptionSignature
fakerUUIDHyphenatedGenerates a random unique user ID separated by hyphensfakerUUID() (res string)
fakerUUIDDigitGenerates a random unique user ID in the HEX formatfakerUUIDDigit() (res string)
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Template custom functions

+

Within Greenmask, custom functions play a crucial role, providing a wide array of options for implementing diverse +logic. Under the hood, the custom functions are based on +the sprig Go's template functions. Greenmask enhances this capability by +introducing additional functions and transformation functions. These extensions mirror the logic found in +the standard transformers but offer you the flexibility to implement intricate +and comprehensive logic tailored to your specific needs.

+

Currently, you can use template custom functions for the advanced transformers:

+ +

and for the Transformation condition feature as well.

+

Custom functions are arbitrarily divided into 2 groups:

+
    +
  • Core functions — custom functions that vary in purpose and include PostgreSQL driver, JSON + output, testing, and transformation functions.
    • +
  • Faker functions — custom function of a faker type which generate synthetic data.
    • +
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Advanced transformers

+

Advanced transformers are modifiable anonymization methods that users can adjust based on their needs by using custom functions.

+

Below you can find an index of all advanced transformers currently available in Greenmask.

+
    +
  1. Json — changes a JSON content by using delete and set operations.
    2. +
  2. Template — executes a Go template of your choice and applies the result to a specified column.
    3. +
  3. TemplateRecord — modifies records by using a Go template of your choice and applies the changes via the PostgreSQL +driver.
    4. +
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Json

+ +

Change a JSON document using delete and set operations. NULL values are kept.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NamePropertiesDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesjson, jsonb
operationsA list of operations that contains editing delete and setYes-
∟operationSpecifies the operation type: set or deleteYes-
∟pathThe path to an object to be modified. See path syntax below.Yes-
∟valueA value to be assigned to the provided pathNo-
∟value_templateA Golang template to be assigned to the provided path. See the list of template functions below.No-
∟error_not_existThrows an error if the key does not exist by the provided path. Disabled by default.falseNo-
+

Description

+

The Json transformer applies a sequence of changing operations (set and/or delete) to a JSON document. The value can be static or dynamic. For the set operation type, a static value is provided in the value parameter, while a dynamic value is provided in the value_template parameter, taking the data received after template execution as a result. Both the value and value_template parameters are mandatory for the set operation.

+

Path syntax

+

The Json transformer is based on tidwall/sjson and supports the same path syntax. See their documentation for syntax rules.

+

Template functions

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
FunctionDescriptionSignature
.GetPathReturns the current path to which the operation is being applied.GetPath() (path string)
.GetOriginalValueReturns the original value to which the current operation path is pointing. If the value at the specified path does not exist, it returns nil..GetOriginalValue() (value any)
.OriginalValueExistsReturns a boolean value indicating whether the specified path exists or not..OriginalValueExists() (exists bool)
.GetColumnValueReturns an encoded into Golang type value for a specified column or throws an error. A value can be any of int, float, time, string, bool, or slice or map..GetColumnValue(name string) (value any, err error)
.GetRawColumnValueReturns a raw value for a specified column as a string or throws an error.GetRawColumnValue(name string) (value string, err error)
.EncodeValueByColumnEncodes a value of any type into its raw string representation using the specified column name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValueByColumn(name string, value any) (res any, err error)
.DecodeValueByColumnDecodes a value from its raw string representation to a Golang type using the specified column name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByColumn(name string, value any) (res any, err error)
.EncodeValueByTypeEncodes a value of any type into its string representation using the specified type name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValueByType(name string, value any) (res any, err error)
.DecodeValueByTypeDecodes a value from its raw string representation to a Golang type using the specified type name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByType(name string, value any) (res any, err error)
+

Example: Changing JSON document

+
Json transformer example
- schema: "bookings"
+  name: "aircrafts_data"
+  transformers:
+    - name: "Json"
+      params:
+        column: "model"
+        operations:
+          - operation: "set"
+            path: "en"
+            value: "Boeing 777-300-2023"
+          - operation: "set"
+            path: "seats"
+            error_not_exist: True
+            value_template: "{{ randomInt 100 400 }}"
+          - operation: "set"
+            path: "details.preperties.1"
+            value: {"name": "somename", "description": null}
+          - operation: "delete"
+            path: "values.:2"
+
+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/advanced_transformers/template/index.html b/v0.2.5/built_in_transformers/advanced_transformers/template/index.html new file mode 100644 index 00000000..cdfaef2c --- /dev/null +++ b/v0.2.5/built_in_transformers/advanced_transformers/template/index.html @@ -0,0 +1,3561 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Template - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Template

+ +

Execute a Go template and automatically apply the result to a specified column.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesany
templateA Go template stringYes-
validateValidates the template result using the PostgreSQL driver decoding procedure. Throws an error if a custom type does not have an encode-decoder implementation.falseNo-
+

Description

+

The Template transformer executes Go templates and automatically applies the template result to a specified column. Go template system is designed to be extensible, enabling developers to access data objects and incorporate custom functions programmatically. For more information, you can refer to the official Go Template documentation.

+

With the Template transformer, you can implement complicated transformation logic using basic or custom template functions. Below you can get familiar with the basic template functions for the Template transformer. For more information about available custom template functions, see Custom functions.

+
+

Warning

+

Pay attention to the whitespaces in templates. Use dash-wrapped - brackets {{- -}} for +trimming the spaces. For example, the value "2023-12-19" is not the same as " 2023-12-19 " and it may throw an error when restoring.

+
+

Template functions

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
FunctionDescriptionSignature
.GetColumnTypeReturns a string with the column type..GetColumnType(name string) (typeName string, err error)
.GetValueReturns the column value for column assigned in the column parameter, encoded by the PostgreSQL driver into any type along with any associated error. Supported types include int, float, time, string, bool, as well as slice or map of any type..GetValue() (value any, err error)
.GetRawValueReturns a raw value as a string for column assigned in the column parameter..GetRawColumnValue(name string) (value string, err error)
.GetColumnValueReturns an encoded value for a specified column or throws an error. A value can be any of int, float, time, string, bool, or slice or map..GetColumnValue(name string) (value any, err error)
.GetRawColumnValueReturns a raw value for a specified column as a string or throws an error.GetRawColumnValue(name string) (value string, err error)
.EncodeValueEncodes a value of any type into its string representation using the type assigned to the table column specified in the column parameter. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValue(value any) (res any, err error)
.DecodeValueDecodes a value from its raw string representation to a Golang type using the data type assigned to the table column specified in the column parameter. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByColumn(value any) (res any, err error)
.EncodeValueByColumnEncodes a value of any type into its raw string representation using the specified column name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValueByColumn(name string, value any) (res any, err error)
.DecodeValueByColumnDecodes a value from its raw string representation to a Golang type using the specified column name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByColumn(name string, value any) (res any, err error)
.EncodeValueByTypeEncodes a value of any type into its string representation using the specified type name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValueByType(name string, value any) (res any, err error)
.DecodeValueByTypeDecodes a value from its raw string representation to a Golang type using the specified type name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByType(name string, value any) (res any, err error)
+

Example: Update the firstname column

+

Below you can see the table structure:

+

person-person-schema.png

+

Change rule

+

The goal is to modify the firstname column based on the following conditions:

+
    +
  • If the current value of the firstname column is equal to Terri, replace it with Mary.
    • +
  • For all other cases, generate a random name and append Jr.
    • +
+

Using a template function

+

To generate random names, you can use the fakerFirstName template function, which is designed to create +synthetic names.

+
Template transformer example
- schema: "humanresources"
+  name: "employee"
+  transformation:
+    - name: "Template"
+      params:
+        column: "firstname"
+        template: >
+          {{- if eq .GetValue "Terri" -}}
+            Mary
+          {{- else -}}
+            {{- fakerFirstName -}} Jr
+          {{- end -}}
+
+        validate: true
+
+

Expected result:

+
+
+
+ + + + + + + + + + + + + + + +
column nameoriginal valuetransformed
firstnameTerriMary
+
+
+ + + + + + + + + + + + + + + +
column nameoriginal valuetransformed
firstnameKen JrMike
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TemplateRecord

+ +

Modify records using a Go template and apply changes by using the PostgreSQL driver functions. This transformer provides a way to implement custom transformation logic.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnsA list of columns to be affected by the template. The list of columns will be checked for constraint violations.Noany
templateA Go template stringYes-
validateValidate the template result via PostgreSQL driver decoding procedure. Throws an error if a custom type does not have an encode-decoder implementation.falseNo-
+

Description

+

TemplateRecord uses Go templates to change data. However, while the Template transformer operates with a single column and automatically applies results, the TemplateRecord transformer can make changes to a set of columns in the string, and using driver functions .SetValue or .SetRawValue is mandatory to do that.

+

With the TemplateRecord transformer, you can implement complicated transformation logic using basic or custom template functions. Below you can get familiar with the basic template functions for the TemplateRecord transformer. For more information about available custom template functions, see Custom functions.

+

Template functions

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
FunctionDescriptionSignature
.GetColumnTypeReturns a string with the column type..GetColumnType(name string) (typeName string, err error)
.GetColumnValueReturns an encoded value for a specified column or throws an error. A value can be any of int, float, time, string, bool, or slice or map..GetColumnValue(name string) (value any, err error)
.GetRawColumnValueReturns a raw value for a specified column as a string or throws an error.GetRawColumnValue(name string) (value string, err error)
.SetColumnValueSets a new value of a specific data type to the column. The value assigned must be compatible with the PostgreSQL data type of the column. For example, it is allowed to assign an int value to an INTEGER column, but you cannot assign a float value to a timestamptz column.SetColumnValue(name string, v any) (bool, error)
.SetRawColumnValueSets a new raw value for a column, inheriting the column's existing data type, without performing data type validation. This can lead to errors when restoring the dump if the assigned value is not compatible with the column type. To ensure compatibility, consider using the .DecodeValueByColumn function followed by .SetColumnValue, for example, {{ "13" \| .DecodeValueByColumn "items_amount" \| .SetColumnValue "items_amount" }}..SetRawColumnValue(name string, value any) (err error)
.EncodeValueByColumnEncodes a value of any type into its raw string representation using the specified column name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValueByColumn(name string, value any) (res any, err error)
.DecodeValueByColumnDecodes a value from its raw string representation to a Golang type using the specified column name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByColumn(name string, value any) (res any, err error)
.EncodeValueByTypeEncodes a value of any type into its string representation using the specified type name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValueByType(name string, value any) (res any, err error)
.DecodeValueByTypeDecodes a value from its raw string representation to a Golang type using the specified type name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByType(name string, value any) (res any, err error)
+

Example: Generate a random created_at and updated_at dates

+

Below you can see the table structure:

+

img.png

+

The goal is to modify the "created_at" and "updated_at" columns based on the following rules:

+
    +
  • Do not change the value if the created_at is Null.
    • +
  • If the created_at is not Null, generate the current time and use it as the minimum threshold for randomly + generating the updated_at value.
    • +
  • Assign all generated values using the .SetColumnValue function.
    • +
+
Template transformer example
- name: "TemplateRecord"
+  params:
+    columns:
+      - "created_at"
+      - "updated_at"
+    template: >
+      {{ $val := .GetColumnValue "created_at" }}
+      {{ if isNotNull $val }}
+          {{ $createdAtValue := now }}
+          {{ $maxUpdatedDate := date_modify "24h" $createdAtValue }}
+          {{ $updatedAtValue := randomDate $createdAtValue $maxUpdatedDate }}
+          {{ .SetColumnValue "created_at" $createdAtValue }}
+          {{ .SetColumnValue "updated_at" $updatedAtValue }}
+      {{ end }}
+    validate: true
+
+

Expected result:

+ + + + + + + + + + + + + + + + + + + + +
column nameoriginal valuetransformed
created_at2021-01-20 07:01:00.513325+002023-12-17 19:37:29.910054Z
updated_at2021-08-09 21:27:00.513325+002023-12-18 10:05:25.828498Z
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Dynamic parameters

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Description

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Most transformers in Greenmask have dynamic parameters. This functionality is possible because Greenmask utilizes a +database driver that can encode and decode raw values into their actual type representations.

+

This allows you to retrieve parameter values directly from the records. This capability is particularly beneficial when +you need to resolve functional dependencies between fields or satisfy constraints. Greenmask processes transformations +sequentially. Therefore, when you reference a field that was transformed in a previous step, you will access the +transformed value.

+

Definition

+
dynamic_params:
+  - column: "column_name" # (1)
+    cast_to: "cast_function" # (2)
+    template: "template_function" # (3)
+    default_value: any # (4)
+
+
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  1. Name of the column from which the value is retrieved.
    2. +
  2. Function used to cast the column value to the desired type.
    3. +
  3. Default value used if the column's value is NULL.
    4. +
  4. Template used for casting the column value to the desired type.
    5. +
+

Dynamic parameter options

+
    +
  • +

    column - Specifies the column name. The value from each record in this column will be passed to the transformer as a + parameter.

    +
    • +
  • +

    cast_to - Indicates the function used to cast the column value to the desired type. Before being passed to the + transformer, the value is cast to this type. For more details, see Cast functions.

    +
    • +
  • +

    template - Defines the template used for casting the column value to the desired type. You can create your own + template and incorporate predefined functions and operators to implement the casting logic or other logic required for + passing the value to the transformer. For more details, + see Template functions.

    +
    • +
  • +

    default_value - Determines the default value used if the column's value is NULL. This value is represented in raw + format appropriate to the type specified in the column parameter.

    +
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Cast functions

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namedescriptioninput typeoutput type
UnixNanoToDateCast int value as Unix Timestamp in Nano Seconds to date typeint2, int4, int8, numeric, float4, float8date
UnixMicroToDateCast int value as Unix Timestamp in Micro Seconds to date typeint2, int4, int8, numeric, float4, float8date
UnixMilliToDateCast int value as Unix Timestamp in Milli Seconds to date typeint2, int4, int8, numeric, float4, float8date
UnixSecToDateCast int value as Unix Timestamp in Seconds to date typeint2, int4, int8, numeric, float4, float8date
UnixNanoToTimestampCast int value as Unix Timestamp in Nano Seconds to timestamp typeint2, int4, int8, numeric, float4, float8timestamp
UnixMicroToTimestampCast int value as Unix Timestamp in Micro Seconds to timestamp typeint2, int4, int8, numeric, float4, float8timestamp
UnixMilliToTimestampCast int value as Unix Timestamp in Milli Seconds to timestamp typeint2, int4, int8, numeric, float4, float8timestamp
UnixSecToTimestampCast int value as Unix Timestamp in Seconds to timestamp typeint2, int4, int8, numeric, float4, float8timestamp
UnixNanoToTimestampTzCast int value as Unix Timestamp in Nano Seconds to timestamptz typeint2, int4, int8, numeric, float4, float8timestamptz
UnixMicroToTimestampTzCast int value as Unix Timestamp in Micro Seconds to timestamptz typeint2, int4, int8, numeric, float4, float8timestamptz
UnixMilliToTimestampTzCast int value as Unix Timestamp in Milli Seconds to timestamptz typeint2, int4, int8, numeric, float4, float8timestamptz
UnixSecToTimestampTzCast int value as Unix Timestamp in Seconds to timestamptz typeint2, int4, int8, numeric, float4, float8timestamptz
DateToUnixNanoCast date value to int value as a Unix Timestamp in Nano Secondsdateint2, int4, int8, numeric, float4, float8
DateToUnixMicroCast date value to int value as a Unix Timestamp in Micro Secondsdateint2, int4, int8, numeric, float4, float8
DateToUnixMilliCast date value to int value as a Unix Timestamp in Milli Secondsdateint2, int4, int8, numeric, float4, float8
DateToUnixSecCast date value to int value as a Unix Timestamp in Secondsdateint2, int4, int8, numeric, float4, float8
TimestampToUnixNanoCast timestamp value to int value as a Unix Timestamp in Nano Secondstimestampint2, int4, int8, numeric, float4, float8
TimestampToUnixMicroCast timestamp value to int value as a Unix Timestamp in Micro Secondstimestampint2, int4, int8, numeric, float4, float8
TimestampToUnixMilliCast timestamp value to int value as a Unix Timestamp in Milli Secondstimestampint2, int4, int8, numeric, float4, float8
TimestampToUnixSecCast timestamp value to int value as a Unix Timestamp in Secondstimestampint2, int4, int8, numeric, float4, float8
TimestampTzToUnixNanoCast timestamptz value to int value as a Unix Timestamp in Nano Secondstimestamptzint2, int4, int8, numeric, float4, float8
TimestampTzToUnixMicroCast timestamptz value to int value as a Unix Timestamp in Micro Secondstimestamptzint2, int4, int8, numeric, float4, float8
TimestampTzToUnixMilliCast timestamptz value to int value as a Unix Timestamp in Milli Secondstimestamptzint2, int4, int8, numeric, float4, float8
TimestampTzToUnixSecCast timestamptz value to int value as a Unix Timestamp in Secondstimestamptzint2, int4, int8, numeric, float4, float8
FloatToIntCast float value to one of integer type. The fractional part will be discardednumeric, float4, float8int2, int4, int8, numeric
IntToFloatCast int value to one of integer typeint2, int4, int8, numericnumeric, float4, float8
IntToBoolCast int value to boolean. The value with 0 is false, 1 is trueint2, int4, int8, numeric, float4, float8bool
BoolToIntCast boolean value to int. The value false is 0, true is 1boolint2, int4, int8, numeric, float4, float8
+

Example: Functional dependency resolution between columns

+

There is simplified schema of the table humanresources.employee from the playground:

+
       Column      |            Type                      
+------------------+-----------------------------
+ businessentityid | integer                      
+ jobtitle         | character varying(50)        
+ birthdate        | date                        
+ hiredate         | date                         
+Check constraints:
+    CHECK (birthdate >= '1930-01-01'::date AND birthdate <= (now() - '18 years'::interval))
+
+

As you can see, there is a functional dependency between the birthdate and hiredate columns. Logically, +the hiredate should be later than the birthdate. Additionally, the birthdate should range from 1930-01-01 +to 18 years prior to the current date.

+

Imagine that you need to generate random birthdate and hiredate columns. To ensure these dates satisfy the +constraints, you can use dynamic parameters in the RandomDate transformer:

+
- schema: "humanresources"
+  name: "employee"
+  transformers:
+
+    - name: "RandomDate" # (1)
+      params:
+        column: "birthdate"
+        min: '{{ now | tsModify "-30 years" | .EncodeValue }}' # (2)
+        max: '{{ now | tsModify "-18 years" | .EncodeValue }}' # (3)
+
+    - name: "RandomDate" # (4)
+      params:
+        column: "hiredate"
+        max: "{{ now | .EncodeValue }}" # (5)
+      dynamic_params:
+        min:
+          column: "birthdate" # (6)
+          template: '{{ .GetValue | tsModify "18 years" | .EncodeValue }}' # (7)
+
+
    +
  1. Firstly we generate the RadnomDate for birthdate column. The result of the transformation will used as the minimum + value for the next transformation for hiredate column.
    2. +
  2. Apply the template for static parameter. It calculates the now date and subtracts 30 years from it. The result + is 1994. The function tsModify return not a raw data, but time.Time object. For getting the raw value suitable for + birthdate type we need to pass this value to .EncodeValue function. This value is used as the minimum value for + the birthdate column.
    3. +
  3. The same as the previous step, but we subtract 18 years from the now date. The result is 2002.
    4. +
  4. Generate the RadnomDate for hiredate column based on the value from the birthdate.
    5. +
  5. Set the maximum value for the hiredate column. The value is the current date.
    6. +
  6. The min parameter is set to the value of the birthdate column from the previous step.
    7. +
  7. The template gets the value of the randomly generated birthdate value and adds 18 years to it.
    8. +
+

Below is the result of the transformation:

+

img.png

+

From the result, you can see that all functional dependencies and constraints are satisfied.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
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+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/index.html b/v0.2.5/built_in_transformers/index.html new file mode 100644 index 00000000..3a48eba0 --- /dev/null +++ b/v0.2.5/built_in_transformers/index.html @@ -0,0 +1,3222 @@ + + + + + + + + + + + + + + + + + + + + + + + + + About transformers - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

About transformers

+

Transformers in Greenmask are methods which are applied to anonymize sensitive data. All Greenmask transformers are +split into the following groups:

+
    +
  • Dynamic parameters — transformers that require an input of parameters and generate + random data based on them.
    • +
  • Transformation engines — the type of generator used in transformers. Hash (deterministic) + and random (randomization)
    • +
  • Parameters templating — generate static parameters values from templates.
    • +
  • Transformation conditions — conditions that can be applied to transformers. If the + condition is not met, the transformer will not be applied.
    • +
  • Transformation Inheritance — transformation inheritance for partitioned tables and + tables with foreign keys. Define once and apply to all.
    • +
  • Standard transformers — transformers that require only an input of parameters.
    • +
  • Advanced transformers — transformers that can be modified according to user's needs + with the help of custom functions.
    • +
  • Custom transformers — coming soon...
    • +
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/parameters_templating/index.html b/v0.2.5/built_in_transformers/parameters_templating/index.html new file mode 100644 index 00000000..9e07dc96 --- /dev/null +++ b/v0.2.5/built_in_transformers/parameters_templating/index.html @@ -0,0 +1,3417 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Parameters templating - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

Parameters templating

+

Description

+

It is allowed to generate parameter values from templates. It is useful when you don't want to write values manually, +but instead want to generate and initialize them dynamically.

+

Here you can find the list of template functions that can be used in the +template Custom functions.

+

You can encode and decode objects using the driver function bellow.

+

Template functions

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
FunctionDescriptionSignature
.GetColumnTypeReturns a string with the column type..GetColumnType(name string) (typeName string, err error)
.EncodeValueByColumnEncodes a value of any type into its raw string representation using the specified column name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValueByColumn(name string, value any) (res any, err error)
.DecodeValueByColumnDecodes a value from its raw string representation to a Golang type using the specified column name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByColumn(name string, value any) (res any, err error)
.EncodeValueByTypeEncodes a value of any type into its string representation using the specified type name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValueByType(name string, value any) (res any, err error)
.DecodeValueByTypeDecodes a value from its raw string representation to a Golang type using the specified type name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByType(name string, value any) (res any, err error)
.DecodeValueDecodes a value from its raw string representation to a Golang type using the data type assigned to the table column specified in the column parameter. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..DecodeValueByColumn(value any) (res any, err error)
.EncodeValueEncodes a value of any type into its string representation using the type assigned to the table column specified in the column parameter. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible..EncodeValue(value any) (res any, err error)
+
+

Warning

+

If column parameter is not linked to column parameter, then functions .DecodeValue and .EncodeValue will return +an error. You can use .DecodeValueByType and .EncodeValueByType or .DecodeValueByColumn and +.EncodeValueByColumn instead.

+
+

Example

+

In the example below, the min and max values for the birth_date column are generated dynamically using the now +template function. The value returns the current date and time. The tsModify function is then used to subtract 30 +(and 18) years. But because the parameter type is mapped on column parameter type, the EncodeValue function is used +to encode the value into the column type.

+

For example, if we have the now date as 2021-01-01, the dynamically calculated min value will be 1994-01-01 and +the max value will be 2006-01-01.

+
CREATE TABLE account
+(
+    id         SERIAL PRIMARY KEY,
+    gender     VARCHAR(1) NOT NULL,
+    email      TEXT       NOT NULL NOT NULL UNIQUE,
+    first_name TEXT       NOT NULL,
+    last_name  TEXT       NOT NULL,
+    birth_date DATE,
+    created_at TIMESTAMP  NOT NULL DEFAULT NOW()
+);
+
+INSERT INTO account (first_name, gender, last_name, birth_date, email)
+VALUES ('John', 'M', 'Smith', '1980-01-01', 'john.smith@gmail.com');
+
+
- schema: "public"
+  name: "account"
+  transformers:
+    - name: "RandomDate"
+      params:
+        column: "birth_date"
+        min: '{{ now | tsModify "-30 years" | .EncodeValue }}' # 1994
+        max: '{{ now | tsModify "-18 years" | .EncodeValue }}' # 2006
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
birth_date1980-01-011995-09-06
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/cmd/index.html b/v0.2.5/built_in_transformers/standard_transformers/cmd/index.html new file mode 100644 index 00000000..d8e36334 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/cmd/index.html @@ -0,0 +1,3676 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Cmd - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
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+ + + + + + + +

Cmd

+ +

Transform data via external program using stdin and stdout interaction.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnsA list of column names to be affected. If empty, the entire tuple is used. Read about the structure further.YesAny
executableThe path to the executable parameter fileYes-
argsA list of parameters for the executableNo-
driverThe row driver with parameters that is used for interacting with cmd. See details below.{"name": "csv"}No-
validatePerforms a decoding operation using the PostgreSQL driver for data received from the command to ensure the data format is correctfalseNo-
timeoutTimeout for sending and receiving data from the external command2sNo-
expected_exit_codeThe expected exit code on SIGTERM signal. If the exit code is unexpected, the transformation exits with an error.0No-
skip_on_behaviourSkips transformation call if one of the provided columns has a null value (any) or each of the provided columns has null values (all). This option works together with the skip_on_null_input parameter on columns. Possible values: all, any.allNo-
+
+

Warning

+

The parameter validate_output=true may cause an error if the type does not have a PostgreSQL driver decoder +implementation. Most of the types, such as int, float, text, varchar, date, timestamp, etc., have +encoders and decoders, as well as inherited types like domain types based on them.

+
+

Description

+

The Cmd transformer allows you to send original data to an external program via stdin and receive transformed data +from stdout. It supports various interaction formats such as json, csv, or plain text for one-column +transformations. The interaction is performed line by line, so at the end of each sent data, a new line +symbol \n must be included.

+

Types of interaction modes

+

text

+

Textual driver that is used only for one column transformation, thus you cannot provide here more than one column. +The value encodes into string laterally. For example, 2023-01-03 01:00:00.0+03.

+

json

+

JSON line driver. It has two formats that can be passed through driver.json_data_format: [text|bytes]. Use +the bytes format for binary datatypes. Use the text format for non-binary datatypes and for those that can be +represented as string literals. The default json_data_format is text.

+
+
+
+
{
+  "column1": {
+    "d": "some_value1",
+    "n": false,
+  },
+  "column2": {
+    "d": "some_value2",
+    "n": false,
+  }
+}
+
+
+
+
{
+  "column1": {
+    "d": "aGVsbG8gd29ybHNeODcxMjE5MCUlJSUlJQ==",
+    "n": false,
+  },
+  "column2": {
+    "d": "aGVsbG8gd29ybHNeODcxMjE5MCUlJSUlJQ==",
+    "n": false,
+  }
+}
+
+
+
+
+

where:

+
    +
  • Each line is a JSON line with a map of attribute numbers to their values
    • +
  • d — the raw data represented as base64 encoding for the bytes format or Unicode text for the text format. The base64 + encoding is needed because data can be binary.
    • +
  • n — indicates if NULL is present
    • +
+

csv

+

CSV driver (comma-separated). The number of attributes is the same as the number of table columns, but the +columns that were not mentioned in the columns list are empty. The NULL value is represented as \N. Each attribute +is escaped by a quote ("). For example, if the transformed table has attributes id, title, and created_at, and +only id and created_at require transformation, then the CSV line will look as follows:

+
csv line example
"123","","2023-01-03 01:00:00.0+03"
+
+

Column object attributes

+
    +
  • name — the name of the column. This value is required. Depending on the attributes that follows further, this column + may be used just as a value and is not affected in any way.
    • +
  • not_affected — indicates whether the column is affected in the transformation. This attribute is required for the + validation procedure when Greenmask is called with greenmask dump --validate. Setting not_affected=true can be + helpful when the command transformer transforms data depending on the value of another column. For example, if you + want to generate an updated_at column value depending on the created_at column value, you can set created_at + to not_affected=true. The default value is false.
    • +
  • skip_original_data — indicates whether the original data is required for the transformer. This attribute can be + helpful for decreasing the interaction time. One use case is when the command works as a generator and returns the + value without relying on the original data. The default value is false.
    • +
  • skip_on_null_input — specifies whether to skip transformation when the original value is null. This attribute + works in conjunction with the skip_on_behaviour parameter. For example, if you have two affected columns + with skip_on_null_input=true and one column is null, then, if skip_on_behaviour=any, the transformation will be + skipped, or, if skip_on_behaviour=and, the transformation will be performed. The default is false.
    • +
+

Example: Apply transformation performed by external command in TEXT format

+

In the following example, jobtitle columns is transformed via external command transformer.

+
External transformer in python example
#!/usr/bin/env python3
+import signal
+import sys
+
+signal.signal(signal.SIGTERM, lambda sig, frame: exit(0))
+
+
+# If we want to implement a simple generator, we need read the line from stdin and write any result to stdout
+for _ in sys.stdin:
+    # Writing the result to stdout with new line and flushing the buffer
+    sys.stdout.write("New Job Title")
+    sys.stdout.write("\n")
+    sys.stdout.flush()
+
+
Cmd transformer config example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "Cmd"
+      params:
+        driver:
+          name: "text"
+        expected_exit_code: -1
+        skip_on_null_input: true
+        validate: true
+        skip_on_behaviour: "any"
+        timeout: 60s
+        executable: "/var/lib/playground/test.py"
+        columns:
+          - name: "jobtitle"
+            skip_original_data: true
+            skip_on_null_input: true 
+
+

Example: Apply transformation performed by external command in JSON format

+

In the following example, jobtitle and loginid columns are transformed via external command +transformer.

+
External transformer in python example
#!/usr/bin/env python3
+import json
+import signal
+import sys
+
+signal.signal(signal.SIGTERM, lambda sig, frame: exit(0))
+
+for line in sys.stdin:
+    res = json.loads(line)
+    # Setting dummy values
+    res["jobtitle"] = {"d": "New Job Title", "n": False}
+    res["loginid"]["d"] = "123"
+
+    # Writing the result to stdout with new line and flushing the buffer
+    sys.stdout.write(json.dumps(res))
+    sys.stdout.write("\n")
+    sys.stdout.flush()
+
+
Cmd transformer config example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "Cmd"
+      params:
+        driver:
+          name: "json" # (1)
+          json_data_format: "text" # (4)
+        expected_exit_code: -1
+        skip_on_null_input: true
+        validate: true
+        skip_on_behaviour: "any" # (2)
+        timeout: 60s
+        executable: "/var/lib/playground/test.py"
+        columns:
+          - name: "jobtitle"
+            skip_original_data: true
+            skip_on_null_input: true # (3)
+          - name: "loginid"
+            skip_original_data: false # (5)
+            skip_on_null_input: true # (3)
+
+

{ .annotate }

+
    +
  1. Validate the received data via decode procedure using the PostgreSQL driver. Note that this may cause an error if the + type is not supported in the PostgreSQL driver.
    2. +
  2. Skip transformation (keep the values) if one of the affected columns (not_affected=false) has a null value.
    3. +
  3. If a column has a null value, then skip it. This works in conjunction with skip_on_behaviour. Since it has the + value any, if one of the columns (jobtitle or loginid) has a null value, then skip the + transformation call.
    4. +
  4. The format of JSON can be either text or bytes. The default value is text.
    5. +
  5. The skip_original_data attribute is set to true the date will not be transfered to the command. This column + will contain the empty original data
    6. +
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/dict/index.html b/v0.2.5/built_in_transformers/standard_transformers/dict/index.html new file mode 100644 index 00000000..0bf35942 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/dict/index.html @@ -0,0 +1,3388 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Dict - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Dict

+ +

Replace values matched by dictionary keys.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesany
valuesValue replace mapping as in: {"string": "string"}. The string with value "\N" is considered NULL.No-
defaultShown if no value has been matched with dict. The string with value "\N" is considered NULL. By default is empty.No-
fail_not_matchedWhen no value is matched with the dict, fails the replacement process if set to true, or keeps the current value, if set to false.trueNo-
validatePerforms the encode-decode procedure using column type to ensure that values have correct typetrueNo-
+

Description

+

The Dict transformer uses a user-provided key-value dictionary to replace values based on matches specified in +the values parameter mapping. These provided values must align with the PostgreSQL type format. To validate the values +format before application, you can utilize the validate parameter, triggering a decoding procedure via the PostgreSQL +driver.

+

If there are no matches by key, an error will be raised according to a default fail_not_matched: true parameter. You +can change this behaviour by providing the default parameter, value from which will be shown in case of a missing +match.

+

In certain cases where the driver type does not support the validation operation, an error may occur. For setting or +matching a NULL value, use a string with the \N sequence.

+

Example: Replace marital status

+

The following example replaces marital status from S to M or from M to S and raises an error if there is no +match:

+
Dict transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "Dict"
+      params:
+        column: "maritalstatus"
+        values:
+          "S": "M"
+          "M": "S"
+        validate: true
+        fail_not_matched: true
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
maritalstatusSM
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
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+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/hash/index.html b/v0.2.5/built_in_transformers/standard_transformers/hash/index.html new file mode 100644 index 00000000..ac50c61c --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/hash/index.html @@ -0,0 +1,3347 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Hash - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Hash

+ +

Generate a hash of the text value using the Scrypt hash function under the hood. NULL values are kept.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
saltHex encoded salt string. This value may be provided via environment variable GREENMASK_GLOBAL_SALTYestext, varchar
functionHash algorithm to anonymize data. Can be any of md5, sha1, sha256, sha512, sha3-224, sha3-254, sha3-384, sha3-512.sha1No-
max_lengthIndicates whether to truncate the hash tail and specifies at what length. Can be any integer number, where 0 means "no truncation".0No-
+

Example: Generate hash from job title

+

The following example generates a hash from the jobtitle into sha1 and truncates the results after the 10th character.

+

We can set the salt via the environment variable GREENMASK_GLOBAL_SALT:

+
export GREENMASK_GLOBAL_SALT="12343567baaa"
+
+
Hash transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "Hash"
+      params:
+        column: "jobtitle"
+        function: "sha1"
+        max_length: 10
+
+
Expected result
| column name | original value                   | transformed |
+|-------------|----------------------------------|-------------|
+| jobtitle    | Research and Development Manager | 3a456da5c5  |
+
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/index.html b/v0.2.5/built_in_transformers/standard_transformers/index.html new file mode 100644 index 00000000..1d7d45b7 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/index.html @@ -0,0 +1,3256 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Standard transformers - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Standard transformers

+

Standard transformers are ready-to-use methods that require no customization and perform with just as little as parameters input. Below you can find an index of all standard transformers currently available in Greenmask.

+
    +
  1. Cmd — transforms data via external program using stdin and stdout interaction.
    2. +
  2. Dict — replaces values matched by dictionary keys.
    3. +
  3. Hash — generates a hash of the text value.
    4. +
  4. Masking — masks a value using one of the masking behaviors depending on your domain.
    5. +
  5. NoiseDate — randomly adds or subtracts a duration within the provided ratio interval to the original date value.
    6. +
  6. NoiseFloat — adds or subtracts a random fraction to the original float value.terval to the original date value.
    7. +
  7. NoiseNumeric — adds or subtracts a random fraction to the original numeric value.
    8. +
  8. NoiseInt — adds or subtracts a random fraction to the original integer value.
    9. +
  9. RandomBool — generates random boolean values.
    10. +
  10. RandomChoice — replaces values randomly chosen from a provided list.
    11. +
  11. RandomDate — generates a random date in a specified interval.
    12. +
  12. RandomFloat — generates a random float within the provided interval.
    13. +
  13. RandomInt — generates a random integer within the provided interval.
    14. +
  14. RandomString — generates a random string using the provided characters within the specified length range.
    15. +
  15. RandomUuid — generates a random unique user ID.
    16. +
  16. RandomLatitude — generates a random latitude value.
    17. +
  17. RandomLongitude — generates a random longitude value.
    18. +
  18. RandomUnixTimestamp — generates a random Unix timestamp.
    19. +
  19. RandomDayOfWeek — generates a random day of the week.
    20. +
  20. RandomDayOfMonth — generates a random day of the month.
    21. +
  21. RandomMonthName — generates the name of a random month.
    22. +
  22. RandomYearString — generates a random year as a string.
    23. +
  23. RandomCentury — generates a random century.
    24. +
  24. RandomTimezone — generates a random timezone.
    25. +
  25. RandomEmail — generates a random email address.
    26. +
  26. RandomUsername — generates a random username.
    27. +
  27. RandomPassword — generates a random password.
    28. +
  28. RandomDomainName — generates a random domain name.
    29. +
  29. RandomURL — generates a random URL.
    30. +
  30. RandomMac — generates a random MAC addresses.
    31. +
  31. RandomIP — generates a random IPv4 or IPv6 addresses.
    32. +
  32. RandomWord — generates a random word.
    33. +
  33. RandomSentence — generates a random sentence.
    34. +
  34. RandomParagraph — generates a random paragraph.
    35. +
  35. RandomCCType — generates a random credit card type.
    36. +
  36. RandomCCNumber — generates a random credit card number.
    37. +
  37. RandomCurrency — generates a random currency code.
    38. +
  38. RandomAmountWithCurrency — generates a random monetary amount with currency.
    39. +
  39. RandomPerson — generates a random person data (first name, last name, etc.)
    40. +
  40. RandomPhoneNumber — generates a random phone number.
    41. +
  41. RandomTollFreePhoneNumber — generates a random toll-free phone number.
    42. +
  42. RandomE164PhoneNumber — generates a random phone number in E.164 format.
    43. +
  43. RealAddress — generates a real address.
    44. +
  44. RegexpReplace — replaces a string using a regular expression.
    45. +
  45. Replace — replaces an original value by the provided one.
    46. +
  46. SetNull — sets NULL value to the column.
    47. +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/masking/index.html b/v0.2.5/built_in_transformers/standard_transformers/masking/index.html new file mode 100644 index 00000000..92524751 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/masking/index.html @@ -0,0 +1,3401 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Masking - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Masking

+ +

Mask a value using one of the masking rules depending on your domain. NULL values are kept.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
typeData type of attribute (default, password, name, addr, email, mobile, tel, id, credit, url)defaultNo-
+

Description

+

The Masking transformer replaces characters with asterisk * symbols depending on the provided data type. If the +value is NULL, it is kept unchanged. It is based on ggwhite/go-masker and +supports the following masking rules:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TypeDescription
defaultReturns * symbols with the same length, e.g. input: test1234 output: ********
nameMasks the second letter the third letter in a word, e. g. input: ABCD output: A**D
passwordAlways returns ************
addressKeeps first 6 letters, masks the rest, e. g. input: Larnaca, makarios st output: Larnac*************
emailKeeps a domain and the first 3 letters, masks the rest, e. g. input: ggw.chang@gmail.com output: ggw****@gmail.com
mobileMasks 3 digits starting from the 4th digit, e. g. input: 0987654321 output: 0987***321
telephoneRemoves (, ), , - chart, and masks last 4 digits of telephone number, then formats it to (??)????-????, e. g. input: 0227993078 output: (02)2799-****
idMasks last 4 digits of ID number, e. g. input: A123456789 output: A12345****
credit_cartMasks 6 digits starting from the 7th digit, e. g. input 1234567890123456 output 123456******3456
urlMasks the password part of the URL, if applicable, e. g. http://admin:mysecretpassword@localhost:1234/uri output: http://admin:xxxxx@localhost:1234/uri
+

Example: Masking employee national ID number

+

In the following example, the national ID number of an employee is masked.

+
Masking transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "Masking"
+      params:
+        column: "nationalidnumber"
+        type: "id"
+
+
Expected result
| column name      | original value | transformed |
+|------------------|----------------|-------------|
+| nationalidnumber | 295847284      | 295847****  |
+
+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/noise_date/index.html b/v0.2.5/built_in_transformers/standard_transformers/noise_date/index.html new file mode 100644 index 00000000..116cffe4 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/noise_date/index.html @@ -0,0 +1,3481 @@ + + + + + + + + + + + + + + + + + + + + + + + + + NoiseDate - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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NoiseDate

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Randomly add or subtract a duration within the provided ratio interval to the original date value.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesdate, timestamp, timestamptz
min_ratioThe minimum random value for noise. The value must be in PostgreSQL interval format, e. g. 1 year 2 mons 3 day 04:05:06.075% from max_ration parameterNo-
max_ratioThe maximum random value for noise. The value must be in PostgreSQL interval format, e. g. 1 year 2 mons 3 day 04:05:06.07Yes-
minMin threshold date (and/or time) of value. The value has the same format as column parameterNo-
maxMax threshold date (and/or time) of value. The value has the same format as column parameterNo-
truncateTruncate the date to the specified part (nanosecond, microsecond, millisecond, second, minute, hour, day, month, year). The truncate operation is not applied by default.No-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Dynamic parameters

+ + + + + + + + + + + + + + + + + +
ParameterSupported types
mindate, timestamp, timestamptz
maxdate, timestamp, timestamptz
+

Description

+

The NoiseDate transformer randomly generates duration between min_ratio and max_ratio parameter and adds it to or +subtracts it from the original date value. The min_ratio or max_ratio parameters must be written in the +PostgreSQL interval format. +You can also truncate the resulted date up to a specified part by setting the truncate parameter.

+

In case you have constraints on the date range, you can set the min and max parameters to specify the threshold +values. The values for min and max must have the same format as the column parameter. Parameters min and max +support dynamic mode.

+
+

Info

+

If the noised value exceeds the max threshold, the transformer will set the value to max. If the noised value +is lower than the min threshold, the transformer will set the value to min.

+
+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Adding noise to the modified date

+

In the following example, the original timestamp value of modifieddate will be noised up +to 1 year 2 months 3 days 4 hours 5 minutes 6 seconds and 7 milliseconds with truncation up to the month part.

+
NoiseDate transformer example
- schema: "humanresources"
+  name: "jobcandidate"
+  transformers:
+    - name: "NoiseDate"
+      params:
+        column: "hiredate"
+        max_ratio: "1 year 2 mons 3 day 04:05:06.07"
+        truncate: "month"
+        max: "2020-01-01 00:00:00"
+
+

Example: Adding noise to the modified date with dynamic min parameter with hash engine

+

In the following example, the original timestamp value of hiredate will be noised up +to 1 year 2 months 3 days 4 hours 5 minutes 6 seconds and 7 milliseconds with truncation up to the month part. +The max threshold is set to 2020-01-01 00:00:00, and the min threshold is set to the birthdate column. If the +birthdate column is NULL, the default value 1990-01-01 will be used. The hash engine is used for deterministic +generation - the same input will always produce the same output.

+
NoiseDate transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "NoiseDate"
+      params:
+        column: "hiredate"
+        max_ratio: "1 year 2 mons 3 day 04:05:06.07"
+        truncate: "month"
+        max: "2020-01-01 00:00:00"
+        engine: "hash"
+      dynamic_params:
+        min:
+          column: "birthdate"
+          default: "1990-01-01"
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
hiredate2009-01-142010-08-01
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
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+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/noise_float/index.html b/v0.2.5/built_in_transformers/standard_transformers/noise_float/index.html new file mode 100644 index 00000000..86b43b50 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/noise_float/index.html @@ -0,0 +1,3450 @@ + + + + + + + + + + + + + + + + + + + + + + + + + NoiseFloat - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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NoiseFloat

+ +

Add or subtract a random fraction to the original float value.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesfloat4, float8
decimalThe decimal of the noised float value (number of digits after the decimal point)4No-
min_ratioThe minimum random percentage for noise, from 0 to 1, e. g. 0.1 means "add noise up to 10%"0.05No-
max_ratioThe maximum random percentage for noise, from 0 to 1, e. g. 0.1 means "add noise up to 10%"Yes-
minMin threshold of noised valueNo-
maxMax threshold of noised valueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Dynamic parameters

+ + + + + + + + + + + + + + + + + +
ParameterSupported types
minfloat4, float8, int2, int4, int8
maxfloat4, float8, int2, int4, int8
+

Description

+

The NoiseFloat transformer multiplies the original float value by randomly generated value that is not higher than +the max_ratio parameter and not less that max_ratio parameter and adds it to or subtracts it from the original +value. Additionally, you can specify the number of decimal digits by using the decimal parameter.

+

In case you have constraints on the float range, you can set the min and max parameters to specify the threshold +values. The values for min and max must have the same format as the column parameter. Parameters min and max +support dynamic mode. Engine parameter allows you to choose between random and hash engines for generating values. Read +more about the engines

+
+

Info

+

If the noised value exceeds the max threshold, the transformer will set the value to max. If the noised value +is lower than the min threshold, the transformer will set the value to min.

+
+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Adding noise to the purchase price

+

In this example, the original value of standardprice will be noised up to 50% and rounded up to 2 decimals.

+
NoiseFloat transformer example
- schema: "purchasing"
+  name: "productvendor"
+  columns_type_override: # (1)
+    lastreceiptcost: "float8"
+    standardprice: "float8"
+  transformers:
+    - name: "NoiseFloat"
+      params:
+        column: "lastreceiptcost"
+        max_ratio: 0.15
+        decimal: 2
+      dynamic_params:
+        min:
+          column: "standardprice"
+
+
    +
  1. The type overrides applied for example because the playground database does not contain any tables with float + columns.
    2. +
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
lastreceiptcost50.263547.87
+ + + + + + + + + + + + + + + + + + + + +
+
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/noise_int/index.html b/v0.2.5/built_in_transformers/standard_transformers/noise_int/index.html new file mode 100644 index 00000000..cf798c24 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/noise_int/index.html @@ -0,0 +1,3434 @@ + + + + + + + + + + + + + + + + + + + + + + + + + NoiseInt - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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NoiseInt

+ +

Add or subtract a random fraction to the original integer value.

+

Parameters

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NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesint2, int4, int8
min_ratioThe minimum random percentage for noise, from 0 to 1, e. g. 0.1 means "add noise up to 10%"0.05No-
max_ratioThe maximum random percentage for noise, from 0 to 1, e. g. 0.1 means "add noise up to 10%"Yes-
minMin threshold of noised valueNo-
maxMin threshold of noised valueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Dynamic parameters

+ + + + + + + + + + + + + + + + + +
ParameterSupported types
minint2, int4, int8
maxint2, int4, int8
+

Description

+

The NoiseInt transformer multiplies the original integer value by randomly generated value that is not higher than +the max_ratio parameter and not less that max_ratio parameter and adds it to or subtracts it from the original +value.

+

In case you have constraints on the integer range, you can set the min and max parameters to specify the +threshold values. The values for min and max must have the same format as the column parameter. Parameters min and +max support dynamic mode.

+
+

Info

+

If the noised value exceeds the max threshold, the transformer will set the value to max. If the noised value +is lower than the min threshold, the transformer will set the value to min.

+
+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Noise vacation hours of an employee

+

In the following example, the original value of vacationhours will be noised up to 40%. The transformer will set the +value to 10 if the noised value is lower than 10 and to 1000 if the noised value exceeds 1000.

+
NoiseInt transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "NoiseInt"
+      params:
+        column: "vacationhours"
+        max_ratio: 0.4
+        min: 10
+        max: 1000
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
vacationhours9969
+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/noise_numeric/index.html b/v0.2.5/built_in_transformers/standard_transformers/noise_numeric/index.html new file mode 100644 index 00000000..b32c2f90 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/noise_numeric/index.html @@ -0,0 +1,3450 @@ + + + + + + + + + + + + + + + + + + + + + + + + + NoiseNumeric - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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NoiseNumeric

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Add or subtract a random fraction to the original numeric value.

+

Parameters

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NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesnumeric, decimal
decimalThe decimal of the noised float value (number of digits after the decimal point)4No-
min_ratioThe minimum random percentage for noise, from 0 to 1, e. g. 0.1 means "add noise up to 10%"0.05No-
max_ratioThe maximum random percentage for noise, from 0 to 1, e. g. 0.1 means "add noise up to 10%"Yes-
minMin threshold of noised valueNo-
maxMax threshold of noised valueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Dynamic parameters

+ + + + + + + + + + + + + + + + + +
ParameterSupported types
minnumeric, decimal, float4, float8, int2, int4, int8
maxnumeric, decimal, float4, float8, int2, int4, int8
+

Description

+

The NoiseNumeric transformer multiplies the original numeric (or decimal) value by randomly generated value that is +not higher than the max_ratio parameter and not less that max_ratio parameter and adds it to or subtracts it from +the original value. Additionally, you can specify the number of decimal digits by using the decimal parameter.

+

In case you have constraints on the numeric range, you can set the min and max parameters to specify the threshold +values. The values for min and max must have the same format as the column parameter. Parameters min and max +support dynamic mode. Engine parameter allows you to choose between random and hash engines for generating values. Read +more about the engines

+
+

Info

+

If the noised value exceeds the max threshold, the transformer will set the value to max. If the noised value +is lower than the min threshold, the transformer will set the value to min.

+
+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+
+

Warning

+

Greenmask cannot parse the numeric type sitteng. For instance NUMERIC(10, 2). You should set min and max treshholds +manually as well as allowed decimal. This behaviour will be changed in the later versions. Grenmask will be able +to determine the decimal and scale of the column and set the min and max treshholds automatically if were not set.

+
+

Example: Adding noise to the purchase price

+

In this example, the original value of standardprice will be noised up to 50% and rounded up to 2 decimals.

+
NoiseNumeric transformer example
- schema: "purchasing"
+  name: "productvendor"
+  transformers:
+    - name: "NoiseNumeric"
+      params:
+        column: "lastreceiptcost"
+        max_ratio: 0.15
+        decimal: 2
+        max: 10000
+      dynamic_params:
+        min:
+          column: "standardprice"
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
lastreceiptcost50.263557.33
+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_amount_with_currency/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_amount_with_currency/index.html new file mode 100644 index 00000000..bac30183 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_amount_with_currency/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomAmountWithCurrency - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomAmountWithCurrency

+ +

The RandomAmountWithCurrency transformer is specifically designed to populate specified database columns with random financial amounts accompanied by currency codes. Ideal for applications requiring the simulation of financial transactions, this utility enhances the realism of financial datasets by introducing variability in amounts and currencies.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

This transformer automatically generates random financial amounts along with corresponding global currency codes (e. g., 250.00 USD, 300.00 EUR), injecting them into the designated database column. It provides a straightforward solution for populating financial records with varied and realistic data, suitable for testing payment systems, data anonymization, and simulation of economic models.

+

Example: Populate the payments table with random amounts and currencies

+

This example shows how to configure the RandomAmountWithCurrency transformer to populate the payment_details column in the payments table with random amounts and currencies. It is an effective approach to simulating a diverse range of payment transactions.

+
RandomAmountWithCurrency transformer example
- schema: "public"
+  name: "payments"
+  transformers:
+    - name: "RandomAmountWithCurrency"
+      params:
+        column: "payment_details"
+        keep_null: false
+
+

In this setup, the payment_details column will be updated with random financial amounts and currency codes for each entry, replacing any existing non-NULL values. The keep_null parameter, when set to true, ensures that existing NULL values in the column remain unchanged, preserving the integrity of records without specified payment details.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_bool/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_bool/index.html new file mode 100644 index 00000000..2a2b38a7 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_bool/index.html @@ -0,0 +1,3363 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomBool - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomBool

+ +

Generate random boolean values.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesbool
keep_nullIndicates whether NULL values should be replaced with transformed values or nottrueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Description

+

The RandomBool transformer generates a random boolean value. The behaviour for NULL values can be +configured using the keep_null parameter. The engine parameter allows you to choose between random and hash engines +for generating values. Read more about the engines in the Transformation engines +section.

+

Example: Generate a random boolean for a column

+

In the following example, the RandomBool transformer generates a random boolean value for the salariedflag column.

+
RandomBool transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "RandomBool"
+      params:
+        column: "salariedflag"
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
salariedflagtf
+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_cc_number/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_cc_number/index.html new file mode 100644 index 00000000..991466b8 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_cc_number/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomCCNumber - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomCCNumber

+ +

The RandomCCNumber transformer is specifically designed to populate specified database columns with random credit card numbers. This utility is crucial for applications that involve simulating financial data, testing payment systems, or anonymizing real credit card numbers in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

By leveraging algorithms capable of generating plausible credit card numbers that adhere to standard credit card validation rules (such as the Luhn algorithm), the RandomCCNumber transformer injects random credit card numbers into the designated database column. This approach ensures the generation of credit card numbers that are realistic for testing and development purposes, without compromising real-world applicability and security.

+

Example: Populate random credit card numbers for the payment_information table

+

This example demonstrates configuring the RandomCCNumber transformer to populate the cc_number column in the payment_information table with random credit card numbers. It is an effective strategy for creating a realistic set of payment data for application testing or data anonymization.

+
RandomCCNumber transformer example
- schema: "public"
+  name: "payment_information"
+  transformers:
+    - name: "RandomCCNumber"
+      params:
+        column: "cc_number"
+        keep_null: false
+
+

With this setup, the cc_number column will be updated with random credit card numbers for each entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, it will ensure that existing NULL values in the column are preserved, maintaining the integrity of records where credit card information is not applicable or available.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_cc_type/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_cc_type/index.html new file mode 100644 index 00000000..d3616319 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_cc_type/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomCCType - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomCCType

+ +

The RandomCCType transformer is designed to populate specified database columns with random credit card types. This tool is essential for applications that require the simulation of financial transaction data, testing payment processing systems, or anonymizing credit card type information in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

Utilizing a predefined list of credit card types (e.g., VISA, MasterCard, American Express, Discover), the RandomCCType transformer injects random credit card type names into the designated database column. This feature allows for the creation of realistic and varied financial transaction datasets by simulating a range of credit card types without using real card data.

+

Example: Populate random credit card types for the transactions table

+

This example shows how to configure the RandomCCType transformer to populate the card_type column in the transactions table with random credit card types. It is a straightforward method for simulating diverse payment methods across transactions.

+
RandomCCType transformer example
- schema: "public"
+  name: "transactions"
+  transformers:
+    - name: "RandomCCType"
+      params:
+        column: "card_type"
+        keep_null: false
+
+

In this configuration, the card_type column will be updated with random credit card types for each entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, maintaining the integrity of records where card type information is not applicable.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_century/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_century/index.html new file mode 100644 index 00000000..360dcdf1 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_century/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomCentury - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomCentury

+ +

The RandomCentury transformer is crafted to populate specified database columns with random century values. It is ideal for applications that require historical data simulation, such as generating random years within specific centuries for historical databases, testing datasets with temporal dimensions, or anonymizing dates in historical research data.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomCentury transformer utilizes an algorithm or a library function (hypothetical in this context) to generate random century values. Each value represents a century (e.g., 19th, 20th, 21st), providing a broad temporal range that can be used to enhance datasets requiring a distribution across different historical periods without the need for precise date information.

+

Example: Populate random centuries for the historical_artifacts table

+

This example shows how to configure the RandomCentury transformer to populate the century column in a historical_artifacts table with random century values, adding an element of variability and historical context to the dataset.

+
RandomCentury transformer example
- schema: "public"
+  name: "historical_artifacts"
+  transformers:
+    - name: "RandomCentury"
+      params:
+        column: "century"
+        keep_null: false
+
+

In this setup, the century column will be filled with random century values, replacing any existing non-NULL values. If the keep_null parameter is set to true, then existing NULL values in the column will remain untouched, preserving the original dataset's integrity where no temporal data is available.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_choice/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_choice/index.html new file mode 100644 index 00000000..b70828f5 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_choice/index.html @@ -0,0 +1,3384 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomChoice - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomChoice

+ +

Replace values randomly chosen from a provided list.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesany
valuesA list of values in any format. The string with value \N is considered NULL.Yes-
validatePerforms a decoding procedure via the PostgreSQL driver using the column type to ensure that values have correct typetrueNo
keep_nullIndicates whether NULL values should be replaced with transformed values or nottrueNo
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Description

+

The RandomChoice transformer replaces one randomly chosen value from the list provided in the values parameter. You +can use the validate parameter to ensure that values are correct before applying the transformation. The behaviour for +NULL values can be configured using the keep_null parameter.

+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Choosing randomly from provided dates

+

In this example, the provided values undergo validation through PostgreSQL driver decoding, and one value is randomly +chosen from the list.

+
RandomChoice transformer example
- schema: "humanresources"
+  name: "jobcandidate"
+  transformers:
+    - name: "RandomChoice"
+      params:
+        column: "modifieddate"
+        validate: true
+        engine: hash
+        values:
+          - "2023-12-21 07:41:06.891"
+          - "2023-12-21 07:41:06.896"
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
modifieddate2007-06-23 00:00:002023-12-21 07:41:06.891
+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_currency/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_currency/index.html new file mode 100644 index 00000000..59c5dd4e --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_currency/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomCurrency - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomCurrency

+ +

The RandomCurrency transformer is tailored to populate specified database columns with random currency codes. This tool is highly beneficial for applications involving the simulation of international financial data, testing currency conversion features, or anonymizing currency information in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

Utilizing a comprehensive list of global currency codes (e.g., USD, EUR, JPY), the RandomCurrency transformer injects random currency codes into the designated database column. This feature allows for the creation of diverse and realistic financial transaction datasets by simulating a variety of currencies without relying on actual financial data.

+

Example: Populate random currency codes for the transactions table

+

This example outlines configuring the RandomCurrency transformer to populate the currency_code column in a transactions table with random currency codes. It is an effective way to simulate international transactions across multiple currencies.

+
RandomCurrency transformer example
- schema: "public"
+  name: "transactions"
+  transformers:
+    - name: "RandomCurrency"
+      params:
+        column: "currency_code"
+        keep_null: false
+
+

In this configuration, the currency_code column will be updated with random currency codes for each entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, ensuring the integrity of records where currency data may not be applicable.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_date/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_date/index.html new file mode 100644 index 00000000..9302d7be --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_date/index.html @@ -0,0 +1,3491 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomDate - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomDate

+ +

Generate a random date in a specified interval.

+

Parameters

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NameDescriptionDefaultRequiredSupported DB types
columnName of the column to be affectedYesdate, timestamp, timestamptz
minThe minimum threshold date for the random value. The format depends on the column type.Yes-
maxThe maximum threshold date for the random value. The format depends on the column type.Yes-
truncateTruncate the date to the specified part (nanosecond, microsecond, millisecond, second, minute, hour, day, month, year). The truncate operation is not applied by default.No-
keep_nullIndicates whether NULL values should be replaced with transformed values or nottrueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Dynamic parameters

+ + + + + + + + + + + + + + + + + +
ParameterSupported types
mindate, timestamp, timestamptz
maxdate, timestamp, timestamptz
+

Description

+

The RandomDate transformer generates a random date within the provided interval, starting from min to max. It +can also perform date truncation up to the specified part of the date. The format of dates in the min and max +parameters must adhere to PostgreSQL types, including DATE, TIMESTAMP WITHOUT TIMEZONE, +or TIMESTAMP WITH TIMEZONE.

+
+

Note

+

The value of min and max parameters depends on the column type. For example, for the date column, the value +should be in the format YYYY-MM-DD, while for the timestamp column, the value should be in the format +YYYY-MM-DD HH:MM:SS or YYYY-MM-DD HH:MM:SS.SSSSSS. The timestamptz column requires the value to be in the +format YYYY-MM-DD HH:MM:SS.SSSSSS+HH:MM. Read more about date/time formats in +the PostgreSQL documentation.

+
+

The behaviour for NULL values can be configured using the keep_null parameter. The engine parameter allows you to +choose between random and hash engines for generating values. Read more about the engines in +the Transformation engines section.

+

Example: Generate modifieddate

+

In the following example, a random timestamp without timezone is generated for the modifieddate column within the +range from 2011-05-31 00:00:00 to 2013-05-31 00:00:00, and the part of the random value after day is truncated.

+
RandomDate transformer example
- schema: "sales"
+  name: "salesorderdetail"
+  transformers:
+    - name: "RandomDate"
+      params:
+        column: "modifieddate"
+        keep_null: false
+        min: "2011-05-31 00:00:00"
+        max: "2013-05-31 00:00:00"
+        truncate: "day"
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
modifieddate2014-06-30 00:00:002012-07-27 00:00:00
+ +

Example: Generate hiredate based on birthdate using two transformations

+

In this example, the RandomDate transformer generates a random date for the birthdate column within the +range now - 50 years to now - 18 years. The hire date is generated based on the birthdate, ensuring that the +employee is at least 18 years old when hired.

+
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "RandomDate"
+      params:
+        column: "birthdate"
+        min: '{{ now | tsModify "-50 years" | .EncodeValue }}' # 1994
+        max: '{{ now | tsModify "-18 years" | .EncodeValue }}' # 2006
+
+    - name: "RandomDate"
+      params:
+        column: "hiredate"
+        truncate: "month"
+        max: "{{ now | .EncodeValue }}"
+      dynamic_params:
+        min:
+          column: "birthdate"
+          template: '{{ .GetValue | tsModify "18 years" | .EncodeValue }}' # min age 18 years
+
+

Result:

+ + + + + + + + + + +
ColumnOriginalValueTransformedValue
birthdate1969-01-291985-10-29
hiredate2009-01-142023-01-01
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_day_of_month/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_day_of_month/index.html new file mode 100644 index 00000000..0f71539a --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_day_of_month/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomDayOfMonth - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomDayOfMonth

+ +

The RandomDayOfMonth transformer is designed to populate specified database columns with random day-of-the-month values. It is particularly useful for scenarios requiring the simulation of dates, such as generating random event dates, user sign-up dates, or any situation where the specific day of the month is needed without reference to the actual month or year.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar, int2, int4, int8, numeric
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

Utilizing the faker library, the RandomDayOfMonth transformer generates random numerical values representing days of the month, ranging from 1 to 31. This allows for the easy insertion of random but plausible day-of-the-month data into a database, enhancing realism or anonymizing actual dates.

+

Example: Populate random days of the month for the events table

+

This example illustrates how to configure the RandomDayOfMonth transformer to fill the event_day column in the events table with random day-of-the-month values, facilitating the simulation of varied event scheduling.

+
RandomDayOfMonth transformer example
- schema: "public"
+  name: "events"
+  transformers:
+    - name: "RandomDayOfMonth"
+      params:
+        column: "event_day"
+        keep_null: false
+
+

With this setup, the event_day column will be updated with random day-of-the-month values, replacing any existing non-NULL values. Setting keep_null to true ensures that NULL values in the column are left unchanged, maintaining any existing gaps in the data.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
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+ + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_day_of_week/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_day_of_week/index.html new file mode 100644 index 00000000..3260df56 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_day_of_week/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomDayOfWeek - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomDayOfWeek

+ +

The RandomDayOfWeek transformer is specifically designed to fill specified database columns with random day-of-the-week names. It is particularly useful for applications that require simulated weekly schedules, random event planning, or any scenario where the day of the week is relevant but the specific date is not.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

Utilizing the faker library, the RandomDayOfWeek transformer generates names of days (e. g., Monday, Tuesday) at random. This transformer can be applied to any text or varchar column in a database, introducing variability and realism into data sets that need to represent days of the week in a non-specific manner.

+

Example: Populate random days of the week for the work_schedule table

+

This example demonstrates configuring the RandomDayOfWeek transformer to populate the work_day column in the work_schedule table with random days of the week. This setup can help simulate a diverse range of work schedules without tying them to specific dates.

+
RandomDayOfWeek transformer example
- schema: "public"
+  name: "work_schedule"
+  transformers:
+    - name: "RandomDayOfWeek"
+      params:
+        column: "work_day"
+        keep_null: false
+
+

In this configuration, every entry in the work_day column will be updated with a random day of the week, replacing any existing non-NULL values. If the keep_null parameter is set to true, then existing NULL values within the column will remain unchanged.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_domain_name/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_domain_name/index.html new file mode 100644 index 00000000..f95332f9 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_domain_name/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomDomainName - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomDomainName

+ +

The RandomDomainName transformer is designed to populate specified database columns with random domain names. This tool is invaluable for simulating web data, testing applications that interact with domain names, or anonymizing real domain information in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

By leveraging an algorithm or library capable of generating believable domain names, the RandomDomainName transformer introduces random domain names into the specified database column. Each generated domain name includes a second-level domain (SLD) and a top-level domain (TLD), such as "example.com" or "website.org," providing a wide range of plausible web addresses for database enrichment.

+

Example: Populate random domain names for the websites table

+

This example demonstrates configuring the RandomDomainName transformer to populate the domain column in the websites table with random domain names. This approach facilitates the creation of a diverse and realistic set of web addresses for testing, simulation, or data anonymization purposes.

+
RandomDomainName transformer example
- schema: "public"
+  name: "websites"
+  transformers:
+    - name: "RandomDomainName"
+      params:
+        column: "domain"
+        keep_null: false
+
+

In this setup, the domain column will be updated with random domain names for each entry, replacing any existing non-NULL values. If keep_null is set to true, the transformer will preserve existing NULL values in the column, maintaining the integrity of data where domain information is not applicable.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_e164_phone_number/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_e164_phone_number/index.html new file mode 100644 index 00000000..58865bfc --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_e164_phone_number/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomE164PhoneNumber - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+
+ + + + + + + +

RandomE164PhoneNumber

+ +

The RandomE164PhoneNumber transformer is developed to populate specified database columns with random E.164 phone numbers. This tool is essential for applications requiring the simulation of contact information, testing phone number validation systems, or anonymizing phone number data in datasets while focusing on E.164 numbers.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomE164PhoneNumber transformer utilizes algorithms capable of generating random E.164 phone numbers with the standard international format and injects them into the designated database column. This feature allows for the creation of diverse and realistic contact information in datasets for development, testing, or data anonymization purposes.

+

Example: Populate random E.164 phone numbers for the contact_information table

+

This example demonstrates configuring the RandomE164PhoneNumber transformer to populate the phone_number column in the contact_information table with random E.164 phone numbers. It is an effective method for simulating a variety of contact information entries with E.164 numbers.

+
RandomE164PhoneNumber transformer example
- schema: "public"
+  name: "contact_information"
+  transformers:
+    - name: "RandomE164PhoneNumber"
+      params:
+        column: "phone_number"
+        keep_null: false
+
+

In this configuration, the phone_number column will be updated with random E.164 phone numbers for each contact information entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, ensuring the integrity of records where E.164 phone number information is not applicable or provided.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
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+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_email/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_email/index.html new file mode 100644 index 00000000..ff83707d --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_email/index.html @@ -0,0 +1,3495 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomEmail - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomEmail

+ +

Generate email addresses for a specified column.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_original_domainKeep original of the original addressfalseNo-
local_part_templateThe template for local part of emailNo-
domain_part_templateThe template for domain part of emailNo-
domainsList of domains for new email["gmail.com", "yahoo.com", "outlook.com", "hotmail.com", "aol.com", "icloud.com", "mail.com", "zoho.com", "yandex.com", "protonmail.com", "gmx.com", "fastmail.com"]No-
validateValidate generated email if using templatefalseNo-
max_random_lengthMax length of randomly generated part of the email32No-
keep_nullIndicates whether NULL values should be preservedfalseNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Description

+

The RandomEmail transformer generates random email addresses for the specified database column. By default, the +transformer generates random email addresses with a maximum length of 32 characters. The keep_original_domain +parameter allows you to preserve the original domain part of the email address. The local_part_template +and domain_part_template parameters enable you to specify templates for the local and domain parts of the email +address, respectively. If the validate parameter is set to true, the transformer will validate the generated email +addresses against the specified templates. The keep_null parameter allows you to preserve existing NULL values in the +column.

+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Templates parameters

+

In each template you have access to the columns of the table by using the {{ .column_name }} syntax. Note that +all values are strings. For example, you can use for assembling the email address by accessing to first_name and +last_name columns {{ .first_name | lower }}.{{ .last_name | lower }}.

+

The transformer always generates random sequences for the email, and you can use it by accessing +the {{ .random_string }} variable. For example, we can add random string in the end of local part +{{ .first_name | lower }}.{{ .last_name | lower }}.{{ .random_string }}.

+

Read more about template function Template functions.

+

Random email generation using first name and last name

+

In this example, the RandomEmail transformer generates random email addresses for the email column in the account +table. The transformer generates email addresses using the first_name and last_name columns as the local part +of the email address and adds a random string to the end of the local part with length 10 characters. The original +domain part of the email address is preserved.

+
CREATE TABLE account
+(
+    id         SERIAL PRIMARY KEY,
+    gender     VARCHAR(1) NOT NULL,
+    email      TEXT       NOT NULL NOT NULL UNIQUE,
+    first_name TEXT       NOT NULL,
+    last_name  TEXT       NOT NULL,
+    birth_date DATE,
+    created_at TIMESTAMP  NOT NULL DEFAULT NOW()
+);
+
+INSERT INTO account (first_name, gender, last_name, birth_date, email)
+VALUES ('John', 'M', 'Smith', '1980-01-01', 'john.smith@gmail.com');
+
+
RandomEmail transformer example
- schema: "public"
+  name: "account"
+  transformers:
+    - name: "RandomEmail"
+      params:
+        column: "email"
+        engine: "hash"
+        keep_original_domain: true
+        local_part_template: "{{ first_name | lower }}.{{ last_name | lower }}.{{ .random_string | trunc 10 }}"
+
+

Result:

+ + + + + + + +
ColumnOriginalValueTransformedValue
emailjohn.smith@gmail.comjohn.smith.a075d99e2d@gmail.com
+ +

Simple random email generation

+

In this example, the RandomEmail transformer generates random email addresses for the email column in the account +table. The transformer generates random email addresses with a maximum length of 10 characters.

+
RandomEmail transformer example
- schema: "public"
+  name: "account"
+  transformers:
+    - name: "RandomEmail"
+      params:
+        column: "email"
+        max_random_length: 10
+
+

Result:

+ + + + + + + +
ColumnOriginalValueTransformedValue
emailjohn.smith@gmail.comjohn.smith.a075d99e2d@gmail.com
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_float/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_float/index.html new file mode 100644 index 00000000..fdb10604 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_float/index.html @@ -0,0 +1,3432 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomFloat - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomFloat

+ +

Generate a random float within the provided interval.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesfloat4, float8
minThe minimum threshold for the random value. The value range depends on the column type.Yes-
maxThe maximum threshold for the random value. The value range depends on the column type.Yes-
decimalThe decimal of the random float value (number of digits after the decimal point)4No-
keep_nullIndicates whether NULL values should be replaced with transformed values or nottrueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Dynamic parameters

+ + + + + + + + + + + + + + + + + +
ParameterSupported types
minfloat4, float8
maxfloat4, float8
+

Description

+

The RandomFloat transformer generates a random float value within the provided interval, starting from min to +max, with the option to specify the number of decimal digits by using the decimal parameter. The behaviour for +NULL values can be configured using the keep_null parameter.

+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Generate random price

+

In this example, the RandomFloat transformer generates random prices in the range from 0.1 to 7000 while +maintaining a decimal of up to 2 digits.

+
RandomFloat transformer example
- schema: "sales"
+  name: "salesorderdetail"
+  columns_type_override:  # (1)
+    "unitprice": "float8"
+  transformers:
+    - name: "RandomFloat"
+      params:
+        column: "unitprice"
+        min: 0.1
+        max: 7000
+        decimal: 2
+
+
    +
  1. The type overrides applied for example because the playground database does not contain any tables with float + columns.
    2. +
+

Result:

+ + + + + + + +
ColumnOriginalValueTransformedValue
unitprice2024.9944449.7
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_int/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_int/index.html new file mode 100644 index 00000000..0cc44cc4 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_int/index.html @@ -0,0 +1,3461 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomInt - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomInt

+ +

Generate a random integer within the provided interval.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesint2, int4, int8
minThe minimum threshold for the random valueYes-
maxThe maximum threshold for the random valueYes-
keep_nullIndicates whether NULL values should be replaced with transformed values or nottrueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Dynamic parameters

+ + + + + + + + + + + + + + + + + +
ParameterSupported types
minint2, int4, int8
maxint2, int4, int8
+

Description

+

The RandomInt transformer generates a random integer within the specified min and max thresholds. The behaviour +for NULL values can be configured using the keep_null parameter.

+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Generate random item quantity

+

In the following example, the RandomInt transformer generates a random value in the range from 1 to 30 and assigns +it to +the orderqty column.

+
generate random orderqty in the range from 1 to 30
- schema: "sales"
+  name: "salesorderdetail"
+  transformers:
+    - name: "RandomInt"
+      params:
+        column: "orderqty"
+        min: 1
+        max: 30
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
orderqty129
+ +

Example: Generate random sick leave hours based on vacation hours

+

In the following example, the RandomInt transformer generates a random value in the range from 1 to the value of the +vacationhours column and assigns it to the sickleavehours column. This configuration allows for the simulation of +sick leave hours based on the number of vacation hours.

+
RandomInt transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "RandomInt"
+      params:
+        column: "sickleavehours"
+        max: 100
+      dynamic_params:
+        min:
+          column: "vacationhours"
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
sickleavehours6999
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_ip/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_ip/index.html new file mode 100644 index 00000000..86d05c52 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_ip/index.html @@ -0,0 +1,3456 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomIP - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomIP

+ +

The RandomIp transformer is designed to populate specified database columns with random IP v4 or V6 addresses. +This utility is essential for applications requiring the simulation of network data, testing systems that utilize IP +addresses, or anonymizing real IP addresses in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar, inet
subnetSubnet for generating random ip in V4 or V6 formatYes-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Dynamic parameters

+ + + + + + + + + + + + + +
NameSupported types
subnetcidr, text, varchar
+

Description

+

Utilizing a robust algorithm or library for generating IP addresses, the RandomIp transformer injects random IPv4 +or IPv6 addresses into the designated database column, depending on the provided subnet. The transformer automatically +detects whether to generate an IPv4 or IPv6 address based on the subnet version specified.

+

Example: Generate a Random IPv4 Address for a 192.168.1.0/24 Subnet

+

This example demonstrates how to configure the RandomIp transformer to inject a random IPv4 address into the +ip_address column for entries in the 192.168.1.0/24 subnet:

+
Create table ip_networks and insert data
CREATE TABLE ip_networks
+(
+    id         SERIAL PRIMARY KEY,
+    ip_address INET,
+    network    CIDR
+);
+
+INSERT INTO ip_networks (ip_address, network)
+VALUES ('192.168.1.10', '192.168.1.0/24'),
+       ('10.0.0.5', '10.0.0.0/16'),
+       ('172.16.254.3', '172.16.0.0/12'),
+       ('192.168.100.14', '192.168.100.0/24'),
+       ('2001:0db8:85a3:0000:0000:8a2e:0370:7334', '2001:0db8:85a3::/64'); -- An IPv6 address and network
+
+
RandomPerson transformer example
- schema: public
+  name: ip_networks
+  transformers:
+    - name: "RandomIp"
+      params:
+        subnet: "192.168.1.0/24"
+        column: "ip_address"
+        engine: "random"
+
+

Result:

+ + + + + + + +
ColumnOriginalValueTransformedValue
ip_address192.168.1.10192.168.1.28
+ +

Example: Generate a Random IP Based on the Dynamic Subnet Parameter

+

This configuration illustrates how to use the RandomIp transformer dynamically, where it reads the subnet information +from the network column of the database and generates a corresponding random IP address:

+
RandomPerson transformer example with dynamic mode
- schema: public
+  name: ip_networks
+  transformers:
+    - name: "RandomIp"
+      params:
+        column: "ip_address"
+        engine: "random"
+      dynamic_params:
+        subnet:
+          column: "network"
+
+

Result:

+ + + + + + + +
ColumnOriginalValueTransformedValue
ip_address192.168.1.10192.168.1.111
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_latitude/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_latitude/index.html new file mode 100644 index 00000000..c3889805 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_latitude/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomLatitude - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

RandomLatitude

+ +

The RandomLatitude transformer generates random latitude values for specified database columns. It is designed to support geographical data enhancements, particularly useful for applications requiring randomized but plausible geographical coordinates.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesfloat4, float8, numeric
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomLatitude transformer utilizes the faker library to produce random latitude values within the range of -90 to +90 degrees. This transformer can be applied to columns designated to store geographical latitude information, enhancing data sets with randomized latitude coordinates.

+

Example: Populate random latitude for the locations table

+

This example demonstrates configuring the RandomLatitude transformer to populate the latitude column in the locations table with random latitude values.

+
RandomLatitude transformer example
- schema: "public"
+  name: "locations"
+  transformers:
+    - name: "RandomLatitude"
+      params:
+        column: "latitude"
+        keep_null: false
+
+

With this configuration, the latitude column will be filled with random latitude values, replacing any existing non-NULL values. If keep_null is set to true, existing NULL values will be preserved.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_longitude/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_longitude/index.html new file mode 100644 index 00000000..86688cea --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_longitude/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomLongitude - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

RandomLongitude

+ +

The RandomLongitude transformer is designed to generate random longitude values for specified database columns, enhancing datasets with realistic geographic coordinates suitable for a wide range of applications, from testing location-based services to anonymizing real geographic data.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesfloat4, float8, numeric
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomLongitude transformer leverages the faker library to produce random longitude values within the globally accepted range of -180 to +180 degrees. This flexibility allows the transformer to be applied to any column intended for storing longitude data, providing a simple yet powerful tool for introducing randomized longitude coordinates into a database.

+

Example: Populate random longitude for the locations table

+

This example shows how to use the RandomLongitude transformer to fill the longitude column in the locations table with random longitude values.

+
RandomLongitude transformer example
- schema: "public"
+  name: "locations"
+  transformers:
+    - name: "RandomLongitude"
+      params:
+        column: "longitude"
+        keep_null: false
+
+

This setup ensures that all entries in the longitude column receive a random longitude value, replacing any existing non-NULL values. If keep_null is set to true, then existing NULL values in the column will remain unchanged.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_mac/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_mac/index.html new file mode 100644 index 00000000..a954e138 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_mac/index.html @@ -0,0 +1,3398 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomMac - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomMac

+ +

The RandomMac transformer is designed to populate specified database columns with random MAC addresses.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar, macaddr
keep_original_vendorShould the Individual/Group (I/G) and Universal/Local (U/L) bits be preserved from the original MAC address.falseNo-
cast_typeParam which allow to set Individual/Group (I/G) bit in MAC Address. Allowed values [any, individual, group]. If this value is individual, the address is meant for a single device (unicast). If it is group, the address is for a group of devices, which can include multicast and broadcast addresses.anyNo
management_typeParam which allow to set Universal/Local (U/L) bit in MAC Address. Allowed values [any, universal, local]. If this bit is universal, the address is universally administered (globally unique). If it is local, the address is locally administered (such as when set manually or programmatically on a network device).anyNo
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Description

+

The RandomMac transformer generates a random MAC address and injects it into the specified database column. The +transformer can be configured to preserve the Individual/Group (I/G) and Universal/Local (U/L) bits from the original +MAC address. You can also keep the original vendor bits in the generated MAC address by setting +the keep_original_vendor parameter to true.

+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Generate a Random MAC Address

+

This example demonstrates how to configure the RandomMac transformer to inject a random MAC address into the +mac_address column:

+
Create table mac_addresses and insert data
CREATE TABLE mac_addresses
+(
+    id          SERIAL PRIMARY KEY,
+    device_name VARCHAR(50),
+    mac_address MACADDR,
+    description TEXT
+);
+
+INSERT INTO mac_addresses (device_name, mac_address, description)
+VALUES ('Device A', '00:1A:2B:3C:4D:5E', 'Description for Device A'),
+       ('Device B', '01:2B:3C:4D:5E:6F', 'Description for Device B'),
+       ('Device C', '02:3C:4D:5E:6F:70', 'Description for Device C'),
+       ('Device D', '03:4D:5E:6F:70:71', 'Description for Device D'),
+       ('Device E', '04:5E:6F:70:71:72', 'Description for Device E');
+
+
RandomPerson transformer example
- schema: public
+  name: mac_addresses
+  transformers:
+    - name: "RandomMac"
+      params:
+        column: "mac_address"
+        engine: "random"
+        cast_type: "any"
+        management_type: "any"
+
+

Result:

+ + + + + + + +
ColumnOriginalValueTransformedValue
mac_address00:1a:2b:3c:4d:5eac:7f:a8:11:4e:0d
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_month_name/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_month_name/index.html new file mode 100644 index 00000000..047ab741 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_month_name/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomMonthName - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomMonthName

+ +

The RandomMonthName transformer is crafted to populate specified database columns with random month names. This transformer is especially useful for scenarios requiring the simulation of time-related data, such as user birth months or event months, without relying on specific date values.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomMonthName transformer utilizes the faker library to generate the names of months at random. It can be applied to any textual column in a database to introduce variety and realism into data sets that require representations of months without the need for specific calendar dates.

+

Example: Populate random month names for the user_profiles table

+

This example demonstrates how to configure the RandomMonthName transformer to fill the birth_month column in the user_profiles table with random month names, adding a layer of diversity to user data without using actual birthdates.

+
RandomMonthName transformer example
- schema: "public"
+  name: "user_profiles"
+  transformers:
+    - name: "RandomMonthName"
+      params:
+        column: "birth_month"
+        keep_null: false
+
+

With this setup, the birth_month column will be updated with random month names, replacing any existing non-NULL values. If the keep_null parameter is set to true, then existing NULL values within the column will remain untouched.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
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+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_numeric/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_numeric/index.html new file mode 100644 index 00000000..e4b51dc5 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_numeric/index.html @@ -0,0 +1,3430 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomNumeric - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomNumeric

+ +

Generate a random numeric within the provided interval.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesnumeric, decimal
minThe minimum threshold for the random value. The value range depends on the column type.Yes-
maxThe maximum threshold for the random value. The value range depends on the column type.Yes-
decimalThe decimal of the random numeric value (number of digits after the decimal point)4No-
keep_nullIndicates whether NULL values should be replaced with transformed values or nottrueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Dynamic parameters

+ + + + + + + + + + + + + + + + + +
ParameterSupported types
minint2, int4, int8, float4, float8, numeric, decimal
maxint2, int4, int8, float4, float8, numeric, decimal
+

Description

+

The RandomNumeric transformer generates a random numeric value within the provided interval, starting from min to +max, with the option to specify the number of decimal digits by using the decimal parameter. The behaviour for +NULL values can be configured using the keep_null parameter.

+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Generate random price

+

In this example, the RandomNumeric transformer generates random prices in the range from 0.1 to 7000 while +maintaining a decimal of up to 2 digits.

+
RandomNumeric transformer example
- schema: "sales"
+  name: "salesorderdetail"
+  transformers:
+    - name: "RandomNumeric"
+      params:
+        column: "unitprice"
+        min: 0.1
+        max: 7000
+        decimal: 2
+
+
    +
  1. The type overrides applied for example because the playground database does not contain any tables with numeric + columns.
    2. +
+

Result:

+ + + + + + + +
ColumnOriginalValueTransformedValue
unitprice2024.9944449.7
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_paragraph/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_paragraph/index.html new file mode 100644 index 00000000..d2ee2104 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_paragraph/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomParagraph - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomParagraph

+ +

The RandomParagraph transformer is crafted to populate specified database columns with random paragraphs. This utility is indispensable for applications that require the generation of extensive textual content, such as simulating articles, enhancing textual datasets for NLP systems, or anonymizing textual content in databases.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

Employing sophisticated text generation algorithms or libraries, the RandomParagraph transformer generates random paragraphs, injecting them into the designated database column. This transformer is designed to create varied and plausible paragraphs that simulate real-world textual content, providing a valuable tool for database enrichment, testing, and anonymization.

+

Example: Populate random paragraphs for the articles table

+

This example illustrates configuring the RandomParagraph transformer to populate the body column in an articles table with random paragraphs. It is an effective way to simulate diverse article content for development, testing, or demonstration purposes.

+
RandomParagraph transformer example
- schema: "public"
+  name: "articles"
+  transformers:
+    - name: "RandomParagraph"
+      params:
+        column: "body"
+        keep_null: false
+
+

With this setup, the body column will receive random paragraphs for each entry, replacing any existing non-NULL values. Setting the keep_null parameter to true allows for the preservation of existing NULL values within the column, maintaining the integrity of records where article content is not applicable or provided.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_password/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_password/index.html new file mode 100644 index 00000000..a0e87076 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_password/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomPassword - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomPassword

+ +

The RandomPassword transformer is designed to populate specified database columns with random passwords. This utility is vital for applications that require the simulation of secure user data, testing systems with authentication mechanisms, or anonymizing real passwords in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

Employing sophisticated password generation algorithms or libraries, the RandomPassword transformer injects random passwords into the designated database column. This feature is particularly useful for creating realistic and secure user password datasets for development, testing, or demonstration purposes.

+

Example: Populate random passwords for the user_accounts table

+

This example demonstrates how to configure the RandomPassword transformer to populate the password column in the user_accounts table with random passwords.

+
RandomPassword transformer example
- schema: "public"
+  name: "user_accounts"
+  transformers:
+    - name: "RandomPassword"
+      params:
+        column: "password"
+        keep_null: false
+
+

In this configuration, every entry in the password column will be updated with a random password. Setting the keep_null parameter to true will preserve existing NULL values in the column, accommodating scenarios where password data may not be applicable.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_person/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_person/index.html new file mode 100644 index 00000000..94babd07 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_person/index.html @@ -0,0 +1,3557 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomPerson - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomPerson

+ +

The RandomPerson transformer is designed to populate specified database columns with personal attributes such as +first name, last name, title and gender.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnsThe name of the column to be affectedYestext, varchar
genderset specific gender (possible values: Male, Female, Any)AnyNo-
gender_mappingSpecify gender name to possible values when using dynamic mode in "gender" parameterAnyNo-
fallback_genderSpecify fallback gender if not mapped when using dynamic mode in "gender" parameterAnyNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Description

+

The RandomPerson transformer utilizes a comprehensive list of first names to inject random first names into the +designated database column. This feature allows for the creation of diverse and realistic user profiles by +simulating a variety of first names without using real user data.

+

column object attributes

+
    +
  • name — the name of the column where the personal attributes will be stored. This value is required.
    • +
  • +

    template - the template for the column value. + You can use the next attributes: .FirstName, .LastName or .Title. For example, if you want to generate a full + name, you can use the next template: + "{{ .FirstName }} {{ .LastName }}"

    +
    • +
  • +

    hashing - the bool value. Indicates whether the column value must be passed through the hashing function. + The default value is false. If all column has hashing set to false (by default), then all columns will be + hashed.

    +
    • +
  • keep_null - the bool value. Indicates whether NULL values should be preserved. The default value is true
    • +
+

gender_mapping object attributes

+

gender_mapping - a dictionary that maps the gender value when gender parameters works in dynamic mode. +The default value is:

+
{
+  "Male": [
+    "male",
+    "M",
+    "m",
+    "man",
+    "Man"
+  ],
+  "Female": [
+    "female",
+    "F",
+    "f",
+    "w",
+    "woman",
+    "Woman"
+  ]
+}
+
+

fallback_gender

+

Gender that will be used if gender_mapping was not found. This parameter is optional +and required only for gender parameter in dynamic mode. The default value is Any.

+

Example: Populate random first name and last name for table user_profiles in static mode

+

This example demonstrates how to use the RandomPerson transformer to populate the name and surname columns in +the user_profiles table with random first names, last name, respectively.

+
Create table user_profiles and insert data
CREATE TABLE personal_data
+(
+    id      SERIAL PRIMARY KEY,
+    name    VARCHAR(100),
+    surname VARCHAR(100),
+    sex     CHAR(1) CHECK (sex IN ('M', 'F'))
+);
+
+-- Insert sample data into the table
+INSERT INTO personal_data (name, surname, sex)
+VALUES ('John', 'Doe', 'M'),
+       ('Jane', 'Smith', 'F'),
+       ('Alice', 'Johnson', 'F'),
+       ('Bob', 'Lee', 'M');
+
+
RandomPerson transformer example
- schema: public
+  name: personal_data
+  transformers:
+    - name: "RandomPerson"
+      params:
+        gender: "Any"
+        columns:
+          - name: "name"
+            template: "{{ .FirstName }}"
+          - name: "surname"
+            template: "{{ .LastName }}"
+        engine: "hash"
+
+

Result

+ + + + + + + + + + +
ColumnOriginalValueTransformedValue
nameJohnZane
surnameDoeMcCullough
+ +

Example: Populate random first name and last name for table user_profiles in dynamic mode

+

This example demonstrates how to use the RandomPerson transformer to populate the name, surname using dynamic +gender

+
RandomPerson transformer example with dynamic mode
- schema: public
+  name: personal_data
+  transformers:
+    - name: "RandomPerson"
+      params:
+        columns:
+          - name: "name"
+            template: "{{ .FirstName }}"
+          - name: "surname"
+            template: "{{ .LastName }}"
+        engine: "random"
+      dynamic_params:
+        gender:
+          column: sex
+
+

Result:

+ + + + + + + + + + +
ColumnOriginalValueTransformedValue
nameJohnMartin
surnameDoeMueller
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_phone_number/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_phone_number/index.html new file mode 100644 index 00000000..3d7dd32a --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_phone_number/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomPhoneNumber - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

RandomPhoneNumber

+ +

The RandomPhoneNumber transformer is developed to populate specified database columns with random phone numbers. This tool is essential for applications requiring the simulation of contact information, testing phone number validation systems, or anonymizing phone number data in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomPhoneNumber transformer utilizes algorithms capable of generating random phone numbers with various formats and injects them into the designated database column. This feature allows for the creation of diverse and realistic contact information in datasets for development, testing, or data anonymization purposes.

+

Example: Populate random phone numbers for the contact_information table

+

This example demonstrates configuring the RandomPhoneNumber transformer to populate the phone_number column in the contact_information table with random phone numbers. It is an effective method for simulating a variety of contact information entries.

+
RandomPhoneNumber transformer example
- schema: "public"
+  name: "contact_information"
+  transformers:
+    - name: "RandomPhoneNumber"
+      params:
+        column: "phone_number"
+        keep_null: false
+
+

In this configuration, the phone_number column will be updated with random phone numbers for each contact information entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, ensuring the integrity of records where phone number information is not applicable or provided.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_sentence/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_sentence/index.html new file mode 100644 index 00000000..c359d255 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_sentence/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomSentence - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

RandomSentence

+ +

The RandomSentence transformer is designed to populate specified database columns with random sentences. Ideal for simulating natural language text for user comments, testing NLP systems, or anonymizing textual data in databases.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomSentence transformer employs complex text generation algorithms or libraries to generate random sentences, injecting them into a designated database column without the need for specifying sentence length. This flexibility ensures the creation of varied and plausible text for a wide range of applications.

+

Example: Populate random sentences for the comments table

+

This example shows how to configure the RandomSentence transformer to populate the comment column in the comments table with random sentences. It is a straightforward method for simulating diverse user-generated content.

+
RandomSentence transformer example
- schema: "public"
+  name: "comments"
+  transformers:
+    - name: "RandomSentence"
+      params:
+        column: "comment"
+        keep_null: false
+
+

In this configuration, the comment column will be updated with random sentences for each entry, replacing any existing non-NULL values. If keep_null is set to true, existing NULL values in the column will be preserved, maintaining the integrity of records where comments are not applicable.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_string/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_string/index.html new file mode 100644 index 00000000..f87fcdd1 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_string/index.html @@ -0,0 +1,3390 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomString - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

RandomString

+ +

Generate a random string using the provided characters within the specified length range.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
min_lengthThe minimum length of the generated stringYes-
max_lengthThe maximum length of the generated stringYes-
symbolsThe range of characters that can be used in the random stringabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZNo-
keep_nullIndicates whether NULL values should be replaced with transformed values or nottrueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Description

+

The RandomString transformer generates a random string with a length between min_length and max_length using the +characters specified in the symbols string as the possible set of characters. The behaviour for NULL values can be +configured using the keep_null parameter.

+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Generate a random string for accountnumber

+

In the following example, a random string is generated for the accountnumber column with a length range from 9 +to 12. The +character set used for generation includes 1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ.

+
RandomString transformer example
- schema: "purchasing"
+  name: "vendor"
+  transformers:
+    - name: "RandomString"
+      params:
+        column: "accountnumber"
+        min_length: 9
+        max_length: 12
+        symbols: "1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
accountnumberAUSTRALI00014VUI6P2OZ
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_timezone/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_timezone/index.html new file mode 100644 index 00000000..6efc8a65 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_timezone/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomTimezone - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

RandomTimezone

+ +

The RandomTimezone transformer is designed to populate specified database columns with random timezone strings. This transformer is particularly useful for applications that require the simulation of global user data, testing of timezone-related functionalities, or anonymizing real user timezone information in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

Utilizing a comprehensive library or algorithm for generating timezone data, the RandomTimezone transformer provides random timezone strings (e. g., "America/New_York", "Europe/London") for database columns. This feature enables the creation of diverse and realistic datasets by simulating timezone information for user profiles, event timings, or any other data requiring timezone context.

+

Example: Populate random timezone strings for the user_accounts table

+

This example demonstrates how to configure the RandomTimezone transformer to populate the timezone column in the user_accounts table with random timezone strings, enhancing the dataset with varied global user representations.

+
RandomTimezone transformer example
- schema: "public"
+  name: "user_accounts"
+  transformers:
+    - name: "RandomTimezone"
+      params:
+        column: "timezone"
+        keep_null: false
+
+

With this configuration, every entry in the timezone column will be updated with a random timezone string, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values within the column will remain unchanged, preserving the integrity of rows without specified timezone data.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_toll_free_phone_number/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_toll_free_phone_number/index.html new file mode 100644 index 00000000..31d3f5e8 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_toll_free_phone_number/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomTollFreePhoneNumber - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

RandomTollFreePhoneNumber

+ +

The RandomTollFreePhoneNumber transformer is designed to populate specified database columns with random toll-free phone numbers. This tool is essential for applications requiring the simulation of contact information, testing phone number validation systems, or anonymizing phone number data in datasets while focusing on toll-free numbers.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomTollFreePhoneNumber transformer utilizes algorithms capable of generating random toll-free phone numbers with various formats and injects them into the designated database column. This feature allows for the creation of diverse and realistic toll-free contact information in datasets for development, testing, or data anonymization purposes.

+

Example: Populate random toll-free phone numbers for the contact_information table

+

This example demonstrates configuring the RandomTollFreePhoneNumber transformer to populate the phone_number column in the contact_information table with random toll-free phone numbers. It is an effective method for simulating a variety of contact information entries with toll-free numbers.

+
RandomTollFreePhoneNumber transformer example
- schema: "public"
+  name: "contact_information"
+  transformers:
+    - name: "RandomTollFreePhoneNumber"
+      params:
+        column: "phone_number"
+        keep_null: false
+
+

In this configuration, the phone_number column will be updated with random toll-free phone numbers for each contact information entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, ensuring the integrity of records where toll-free phone number information is not applicable or provided.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_unix_timestamp/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_unix_timestamp/index.html new file mode 100644 index 00000000..49aad3ed --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_unix_timestamp/index.html @@ -0,0 +1,3481 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomUnixTimestamp - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
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+ + + +
+
+
+ + + +
+
+ + + + + + + +

RandomUnixTimestamp

+ +

The RandomUnixTimestamp transformer generates random Unix time values (timestamps) for specified database columns. It +is +particularly useful for populating columns with timestamp data, simulating time-related data, or anonymizing actual +timestamps in a dataset.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesint2, int4, int8
minThe minimum threshold date for the random value in unix timestamp format (integer) with sec unit by defaultYes-
maxThe maximum threshold date for the random value in unix timestamp format (integer) with sec unit by defaultYes-
unitGenerated unix timestamp value unit. Possible values [second, millisecond, microsecond, nanosecond]secondYes-
min_unitMin unix timestamp threshold date unit. Possible values [second, millisecond, microsecond, nanosecond]secondYes-
max_unitMin unix timestamp threshold date unit. Possible values [second, millisecond, microsecond, nanosecond]secondYes-
keep_nullIndicates whether NULL values should be preservedfalseNo-
truncateTruncate the date to the specified part (nanosecond, microsecond, millisecond, second, minute, hour, day, month, year). The truncate operation is not applied by default.No-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Description

+

The RandomUnixTimestamp transformer generates random Unix timestamps within the provided interval, starting from min +to max. The min and max parameters are expected to be in Unix timestamp format. The min_unit and max_unit +parameters specify the unit of the Unix timestamp threshold date. The truncate parameter allows you to truncate the +date to the specified part of the date. The keep_null parameter allows you to specify whether NULL values should be +preserved or replaced with transformed values.

+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Generate random Unix timestamps with dynamic parameters

+

In this example, the RandomUnixTimestamp transformer generates random Unix timestamps using dynamic parameters. The +min parameter is set to the created_at column, which is converted to Unix seconds using the TimestampToUnixSec. +The max parameter is set to a fixed value. The paid_at column is populated with random Unix timestamps in the +range from created_at to 1715934239 (Unix timestamp for 2024-05-17 12:03:59). The unit parameter is set to +millisecond because the paid_at column stores timestamps in milliseconds.

+
CREATE TABLE transactions
+(
+    id         SERIAL PRIMARY KEY,
+    kind       VARCHAR(255),
+    total      DECIMAL(10, 2),
+    created_at TIMESTAMP,
+    paid_at    BIGINT -- stores milliseconds since the epoch
+);
+
+-- Inserting data with milliseconds timestamp
+INSERT INTO transactions (kind, total, created_at, paid_at)
+VALUES ('Sale', 199.99, '2023-05-17 12:00:00', (EXTRACT(EPOCH FROM TIMESTAMP '2023-05-17 12:05:00') * 1000)),
+       ('Refund', 50.00, '2023-05-18 15:00:00', (EXTRACT(EPOCH FROM TIMESTAMP '2023-05-18 15:10:00') * 1000)),
+       ('Sale', 129.99, '2023-05-19 10:30:00', (EXTRACT(EPOCH FROM TIMESTAMP '2023-05-19 10:35:00') * 1000));
+
+
RandomUnixTimestamp transformer example
- schema: "public"
+  name: "transactions"
+  transformers:
+    - name: "RandomUnixTimestamp"
+      params:
+        column: "paid_at"
+        max: 1715934239
+        unit: "millisecond"
+        min_unit: "second"
+        max_unit: "second"
+      dynamic_params:
+        min:
+          column: "created_at"
+          cast_to: "TimestampToUnixSec"
+
+

Result:

+ + + + + + + +
ColumnOriginalValueTransformedValue
paid_at16843251000001708919030732
+ +

Example: Generate simple random Unix timestamps

+

In this example, the RandomUnixTimestamp transformer generates random Unix timestamps for the paid_at column in the +range from 1615934239 (Unix timestamp for 2021-03-16 12:03:59) to 1715934239 (Unix timestamp +for 2024-05-17 12:03:59). The unit parameter is set to millisecond because the paid_at column stores timestamps +in milliseconds.

+
- schema: "public"
+  name: "transactions"
+  transformers:
+    - name: "RandomUnixTimestamp"
+      params:
+        column: "paid_at"
+        min: 1615934239
+        max: 1715934239
+        unit: "millisecond"
+
+

Result:

+ + + + + + + +
ColumnOriginalValueTransformedValue
paid_at16843251000001655768292548
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_url/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_url/index.html new file mode 100644 index 00000000..a0637a2f --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_url/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomURL - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
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+ + + +
+
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+ + + +
+
+ + + + + + + +

RandomURL

+ +

The RandomURL transformer is designed to populate specified database columns with random URL (Uniform Resource Locator) addresses. This tool is highly beneficial for simulating web content, testing applications that require URL input, or anonymizing real web addresses in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

Utilizing advanced algorithms or libraries for generating URL strings, the RandomURL transformer injects random, plausible URLs into the designated database column. Each generated URL is structured to include the protocol (e. g., "http://", "https://"), domain name, and path, offering a realistic range of web addresses for various applications.

+

Example: Populate random URLs for the webpages table

+

This example illustrates how to configure the RandomURL transformer to populate the page_url column in a webpages table with random URLs, providing a broad spectrum of web addresses for testing or data simulation purposes.

+
RandomURL transformer example
- schema: "public"
+  name: "webpages"
+  transformers:
+    - name: "RandomURL"
+      params:
+        column: "page_url"
+        keep_null: false
+
+

With this configuration, the page_url column will be filled with random URLs for each entry, replacing any existing non-NULL values. Setting the keep_null parameter to true allows for the preservation of existing NULL values within the column, accommodating scenarios where URL data may be intentionally omitted.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_username/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_username/index.html new file mode 100644 index 00000000..65549ec3 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_username/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomUsername - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

RandomUsername

+ +

The RandomUsername transformer is crafted to populate specified database columns with random usernames. This utility is crucial for applications that require the simulation of user data, testing systems with user login functionality, or anonymizing real usernames in datasets.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

By employing sophisticated algorithms or libraries capable of generating believable usernames, the RandomUsername transformer introduces random usernames into the specified database column. Each generated username is designed to be unique and plausible, incorporating a mix of letters, numbers, and possibly special characters, depending on the generation logic used.

+

Example: Populate random usernames for the user_accounts table

+

This example demonstrates configuring the RandomUsername transformer to populate the username column in a user_accounts table with random usernames. This setup is ideal for creating a diverse and realistic user base for development, testing, or demonstration purposes.

+
RandomUsername transformer example
- schema: "public"
+  name: "user_accounts"
+  transformers:
+    - name: "RandomUsername"
+      params:
+        column: "username"
+        keep_null: false
+
+

In this configuration, every entry in the username column will be updated with a random username, replacing any existing non-NULL values. If the keep_null parameter is set to true, then the transformer will preserve existing NULL values within the column, maintaining data integrity where usernames are not applicable or available.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_uuid/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_uuid/index.html new file mode 100644 index 00000000..a06958d6 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_uuid/index.html @@ -0,0 +1,3364 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomUuid - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomUuid

+ +

Generate random unique user ID using version 4.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar, uuid
keep_nullIndicates whether NULL values should be replaced with transformed values or nottrueNo-
engineThe engine used for generating the values [random, hash]. Use hash for deterministic generationrandomNo-
+

Description

+

The RandomUuid transformer generates a random UUID. The behaviour for NULL values can be configured using +the keep_null parameter.

+

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the +engines in the Transformation engines section.

+

Example: Updating the rowguid column

+

The following example replaces original UUID values of the rowguid column to randomly generated ones.

+
RandomUuid transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+  - name: "RandomUuid"
+    params:
+      column: "rowguid"
+      keep_null: false
+
+

Result

+ + + + + + + +
ColumnOriginalValueTransformedValue
rowguidf01251e5-96a3-448d-981e-0f99d789110d8ed8c4b2-7e7a-1e8d-f0f0-768e0e8ed0d0
+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_word/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_word/index.html new file mode 100644 index 00000000..7dbecbf7 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_word/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomWord - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomWord

+ +

The RandomWord transformer populates specified database columns with random words. Ideal for simulating textual content, enhancing linguistic datasets, or anonymizing text in databases.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomWord transformer employs a mechanism to inject random words into a designated database column, supporting the generation of linguistically plausible and contextually diverse text. This transformer is particularly beneficial for creating rich text datasets for development, testing, or educational purposes without specifying the language, focusing on versatility and ease of use.

+

Example: Populate random words for the content table

+

This example demonstrates configuring the RandomWord transformer to populate the tag column in the content table with random words. It is a straightforward approach to adding varied textual data for tagging or content categorization.

+
RandomWord transformer example
- schema: "public"
+  name: "content"
+  transformers:
+    - name: "RandomWord"
+      params:
+        column: "tag"
+        keep_null: false
+
+

In this setup, the tag column will be updated with random words for each entry, replacing any existing non-NULL values. If keep_null is set to true, existing NULL values in the column will remain unchanged, maintaining data integrity for records where textual data is not applicable.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/random_year_string/index.html b/v0.2.5/built_in_transformers/standard_transformers/random_year_string/index.html new file mode 100644 index 00000000..2de5fe82 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/random_year_string/index.html @@ -0,0 +1,3346 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RandomYearString - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RandomYearString

+ +

The RandomYearString transformer is designed to populate specified database columns with random year strings. It is ideal for scenarios that require the representation of years without specific dates, such as manufacturing years of products, birth years of users, or any other context where only the year is relevant.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar, int2, int4, int8, numeric
keep_nullIndicates whether NULL values should be preservedfalseNo-
+

Description

+

The RandomYearString transformer leverages the faker library to generate strings representing random years. This allows for the easy generation of year data in a string format, adding versatility and realism to datasets that need to simulate or anonymize year-related information.

+

Example: Populate random year strings for the products table

+

This example shows how to use the RandomYearString transformer to fill the manufacturing_year column in the products table with random year strings, simulating the diversity of manufacturing dates.

+
RandomYearString transformer example
- schema: "public"
+  name: "products"
+  transformers:
+    - name: "RandomYearString"
+      params:
+        column: "manufacturing_year"
+        keep_null: false
+
+

In this configuration, the manufacturing_year column will be populated with random year strings, replacing any existing non-NULL values. If keep_null is set to true, then existing NULL values in the column will be preserved.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/real_address/index.html b/v0.2.5/built_in_transformers/standard_transformers/real_address/index.html new file mode 100644 index 00000000..e2a1f7a6 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/real_address/index.html @@ -0,0 +1,3408 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RealAddress - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RealAddress

+ +

Generates real addresses for specified database columns using the faker library. It supports customization of the generated address format through Go templates.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NamePropertiesDescriptionDefaultRequiredSupported DB types
columnsSpecifies the affected column names along with additional properties for each columnYesVarious
∟nameThe name of the column to be affectedYesstring
∟templateA Go template string for formatting real address attributesYesstring
∟keep_nullIndicates whether NULL values should be preservedNobool
+

Template value descriptions

+

The template parameter allows for the injection of real address attributes into a customizable template. The following values can be included in your template:

+
    +
  • {{.Address}} — street address or equivalent
    • +
  • {{.City}} — city name
    • +
  • {{.State}} — state, province, or equivalent region name
    • +
  • {{.PostalCode}} — postal or ZIP code
    • +
  • {{.Latitude}} — geographic latitude
    • +
  • {{.Longitude}} — geographic longitude
    • +
+

These placeholders can be combined and formatted as desired within the template string to generate custom address formats.

+

Description

+

The RealAddress transformer uses the faker library to generate realistic addresses, which can then be formatted according to a specified template and applied to selected columns in a database. It allows for the generated addresses to replace existing values or to preserve NULL values, based on the transformer's configuration.

+

Example: Generate Real addresses for the employee table

+

This example shows how to configure the RealAddress transformer to generate real addresses for the address column in the employee table, using a custom format.

+
RealAddress transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+    - name: "RealAddress"
+      params:
+        columns:
+          - name: "address"
+            template: "{{.Address}}, {{.City}}, {{.State}} {{.PostalCode}}"
+            keep_null: false
+
+

This configuration will generate real addresses with the format "Street address, city, state postal code" and apply them to the address column, replacing any existing non-NULL values.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/regexp_replace/index.html b/v0.2.5/built_in_transformers/standard_transformers/regexp_replace/index.html new file mode 100644 index 00000000..020a22bd --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/regexp_replace/index.html @@ -0,0 +1,3364 @@ + + + + + + + + + + + + + + + + + + + + + + + + + RegexpReplace - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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RegexpReplace

+ +

Replace a string using a regular expression.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYestext, varchar
regexpThe regular expression pattern to search for in the column's valueYes-
replaceThe replacement value. This value may be replaced with a captured group from the regexp parameter.Yes-
+

Description

+

The RegexpReplace transformer replaces a string according to the applied regular expression. The valid regular expressions syntax is the same as the general syntax used by Perl, Python, and other languages. To be precise, it is the syntax accepted by RE2 and described in the Golang documentation, except for \C.

+

Example: Removing leading prefix from loginid column value

+

In the following example, the original values from loginid matching the adventure-works\{{ id_name }} format are replaced with {{ id_name }}.

+
RegexpReplace transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+  - name: "RegexpReplace"
+    params:
+      column: "loginid"
+      regexp: "adventure-works\\\\(.*)"
+      replace: "$1"
+
+
Expected result
| column name | original value       | transformed |
+|-------------|----------------------|-------------|
+| loginid     | adventure-works\ken0 | ken0        |
+
+
+

Note

+

YAML has control symbols, and using them without escaping may result in an error. In the example above, the prefix +of id is separated by the \ symbol. Since this symbol is a control symbol, we must escape it using \\. +However, the '\' symbol is also a control symbol for regular expressions, which is why we need to +double-escape it as \\\\.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/replace/index.html b/v0.2.5/built_in_transformers/standard_transformers/replace/index.html new file mode 100644 index 00000000..474d2169 --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/replace/index.html @@ -0,0 +1,3367 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Replace - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Replace

+ +

Replace an original value by the provided one.

+

Parameters

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesany
replaceThe value to replaceYes-
keep_nullIndicates whether NULL values should be replaced with transformed values or nottrueNo-
validatePerforms a decoding procedure via the PostgreSQL driver using the column type to ensure that values have correct typetrueNo-
+

Description

+

The Replace transformer replace an original value from the specified column with the provided one. It can optionally run a validation check with the validate parameter to ensure that the values are of a correct type before starting transformation. The behaviour for NULL values can be configured using the keep_null parameter.

+

Example: Updating the jobtitle column

+

In the following example, the provided value: "programmer" is first validated through driver decoding. If the current value of the +jobtitle column is not NULL, it will be replaced with programmer. If the current value is NULL, it will +remain NULL.

+
Replace transformer example
- schema: "humanresources"
+  name: "employee"
+  transformers:
+  - name: "Replace"
+    params:
+      column: "jobtitle"
+      value: "programmer"
+      keep_null: false
+      validate: true
+
+
Expected result
| column name | original value          | transformed |
+|-------------|-------------------------|-------------|
+| jobtitle    | Chief Executive Officer | programmer  |
+
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/standard_transformers/set_null/index.html b/v0.2.5/built_in_transformers/standard_transformers/set_null/index.html new file mode 100644 index 00000000..cf00cfde --- /dev/null +++ b/v0.2.5/built_in_transformers/standard_transformers/set_null/index.html @@ -0,0 +1,3354 @@ + + + + + + + + + + + + + + + + + + + + + + + + + SetNull - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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SetNull

+ +

Set NULL value to a column.

+

Parameters

+ + + + + + + + + + + + + + + + + + + +
NameDescriptionDefaultRequiredSupported DB types
columnThe name of the column to be affectedYesany
+

Description

+

The SetNull transformer assigns NULL value to a column. This transformer generates warning if the affected column has NOT NULL constraint.

+
NULL constraint violation warning
{
+  "hash": "5a229ee964a4ba674a41a4d63dab5a8c",
+  "meta": {
+    "ColumnName": "jobtitle",
+    "ConstraintType": "NotNull",
+    "ParameterName": "column",
+    "SchemaName": "humanresources",
+    "TableName": "employee",
+    "TransformerName": "SetNull"
+  },
+  "msg": "transformer may produce NULL values but column has NOT NULL constraint",
+  "severity": "warning"
+}
+
+

Example: Set NULL value to updated_at column

+
SetNull transformer example
- schema: "humanresources"
+  name: "employee"
+  transformation:
+    - name: "SetNull"
+      params:
+        column: "jobtitle"
+
+
Expected result
| column name | original value          | transformed |
+|-------------|-------------------------|-------------|
+| jobtitle    | Chief Executive Officer | NULL        |
+
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/transformation_condition/index.html b/v0.2.5/built_in_transformers/transformation_condition/index.html new file mode 100644 index 00000000..38be1283 --- /dev/null +++ b/v0.2.5/built_in_transformers/transformation_condition/index.html @@ -0,0 +1,3538 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Transformation conditions - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Transformation Condition

+

Description

+

The transformation condition feature allows you to execute a defined transformation only if a specified condition is +met. +The condition must be defined as a boolean expression that evaluates to true or false. Greenmask uses +expr-lang/expr under the hood. You can use all functions and syntax provided by the +expr library.

+

You can use the same functions that are described in +the built-in transformers

+

The transformers are executed one by one - this helps you create complex transformation pipelines. For instance +depending on value chosen in the previous transformer, you can decide to execute the next transformer or not.

+

Record descriptors

+

To improve the user experience, Greenmask offers special namespaces for accessing values in different formats: either +the driver-encoded value in its real type or as a raw string.

+
    +
  • record: This namespace provides the record value in its actual type.
    • +
  • raw_record: This namespace provides the record value as a string.
    • +
+

You can access a specific column’s value using record.column_name for the real type or raw_record.column_name for +the raw string value.

+
+

Warning

+

A record may always be modified by previous transformers before the condition is evaluated. This means Greenmask does +not retain the original record value and instead provides the current modified value for condition evaluation.

+
+

Null values condition

+

To check if the value is null, you can use null value for the comparisson. This operation works compatibly +with SQL operator IS NULL or IS NOT NULL.

+
Is null cond example
record.accountnumber == null && record.date > now()
+
+
Is not null cond example
record.accountnumber != null && record.date <= now()
+
+

Expression scope

+

Expression scope can be on table or specific transformer. If you define the condition on the table scope, then the +condition will be evaluated before any transformer is executed. If you define the condition on the transformer scope, +then the condition will be evaluated before the specified transformer is executed.

+
Table scope
- schema: "purchasing"
+  name: "vendor"
+  when: 'record.accountnumber == null || record.accountnumber == "ALLENSON0001"'
+  transformers:
+    - name: "RandomString"
+      params:
+        column: "accountnumber"
+        min_length: 9
+        max_length: 12
+        symbols: "1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
+
Transformer scope
- schema: "purchasing"
+  name: "vendor"
+  transformers:
+    - name: "RandomString"
+      when: 'record.accountnumber != null || record.accountnumber == "ALLENSON0001"'
+      params:
+        column: "accountnumber"
+        min_length: 9
+        max_length: 12
+        symbols: "1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
+

Int and float value definition

+

It is important to create the integer or float value in the correct format. If you want to define the integer value you +must write a number without dot (1, 2, etc.). If you want to define the float value you must write a number with +dot (1.0, 2.0, etc.).

+
+

Warning

+

You may see a wrong comparison result if you compare int and float, for example 1 == 1.0 will return false.

+
+

Architecture

+

Greenmask encodes the way only when evaluating the condition - this allows to optimize the performance of the +transformation if you have a lot of conditions that uses or (||) or and (&&) operators.

+

Example: Chose random value and execute one of

+

In the following example, the RandomChoice transformer is used to choose a random value from the list of values. +Depending on the chosen value, the Replace transformer is executed to set the activeflag column to true or +false.

+

In this case the condition scope is on the transformer level.

+
- schema: "purchasing"
+  name: "vendor"
+  transformers:
+    - name: "RandomChoice"
+      params:
+        column: "name"
+        values:
+          - "test1"
+          - "test2"
+
+    - name: "Replace"
+      when: 'record.name == "test1"'
+      params:
+        column: "activeflag"
+        value: "false"
+
+    - name: "Replace"
+      when: 'record.name == "test2"'
+      params:
+        column: "activeflag"
+        value: "true"
+
+

Example: Do not transform specific columns

+

In the following example, the RandomString transformer is executed only if the businessentityid column value is not +equal to 1492 or 1.

+
  - schema: "purchasing"
+    name: "vendor"
+    when: '!(record.businessentityid | has([1492, 1]))'
+    transformers:
+      - name: "RandomString"
+        params:
+          column: "accountnumber"
+          min_length: 9
+          max_length: 12
+          symbols: "1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
+

Example: Check the json attribute value

+

In the following example, the RandomString transformer is executed only if the a attribute in the json_data column +is equal to 1.

+
- schema: "public"
+  name: "jsondata"
+  when: 'raw_record.json_data | jsonGet("a") == 1'
+  transformers:
+    - name: "RandomString"
+      params:
+        column: "accountnumber"
+        min_length: 9
+        max_length: 12
+        symbols: "1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ"
+
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/transformation_engines/index.html b/v0.2.5/built_in_transformers/transformation_engines/index.html new file mode 100644 index 00000000..47b9ffc7 --- /dev/null +++ b/v0.2.5/built_in_transformers/transformation_engines/index.html @@ -0,0 +1,3471 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Transformation engines - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
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+ + + +
+
+ + + + + + + +

Transformation engine

+

The greenmask provides two engines random and hash. Most of the transformers has engine parameters that +by default is set to random. Use hash engine when you need to generate deterministic data - the same input +will always produce the same output.

+
+

Info

+

Greenmask employs the SHA-3 algorithm to hash input values. While this function is cryptographically secure, it does +exhibit lower performance. We plan to introduce additional hash functions in the future to offer a balance between +security and performance. For example, SipHash, which provides a good trade-off between security and performance, is +currently in development and is expected to be included in the stable v0.2 release of Greenmask.

+
+
+

Warning

+

The hash engine does not guarantee the uniqueness of generated values. Although transformers such as Hash, +RandomEmail, and RandomUuid typically have a low probability of producing duplicate values The feature to +ensure uniqueness is currently under development at Greenmask and is expected to be released in future updates. +For the latest status, please visit the Greenmask roadmap.

+
+

Details

+

Example schema

+

The next examples will be run on the following schema and sample data:

+
CREATE TABLE account
+(
+    id         SERIAL PRIMARY KEY,
+    gender     VARCHAR(1) NOT NULL,
+    email      TEXT       NOT NULL NOT NULL UNIQUE,
+    first_name TEXT       NOT NULL,
+    last_name  TEXT       NOT NULL,
+    birth_date DATE,
+    created_at TIMESTAMP  NOT NULL DEFAULT NOW()
+);
+
+INSERT INTO account (first_name, gender, last_name, birth_date, email)
+VALUES ('John', 'M', 'Smith', '1980-01-01', 'john.smith@gmail.com');
+
+CREATE TABLE orders
+(
+    id          SERIAL PRIMARY KEY,
+    account_id  INTEGER REFERENCES account (id),
+    total_price NUMERIC(10, 2),
+    created_at  TIMESTAMP NOT NULL DEFAULT NOW(),
+    paid_at     TIMESTAMP
+);
+
+INSERT INTO orders (account_id, total_price, created_at, paid_at)
+VALUES (1, 100.50, '2024-05-01', '2024-05-02'),
+       (1, 200.75, '2024-05-03', NULL);
+
+

Random engine

+

The random engine serves as the default engine for the greenmask. It operates using a pseudo-random number generator, +which is initialized with a random seed sourced from a cryptographically secure random number generator. Employ the +random engine when you need to generate random data and do not require reproducibility of the same transformation +results with the same input.

+

The following example demonstrates how to configure the RandomDate transformer to generate random.

+
- schema: "public"
+  name: "account"
+  transformers:
+    - name: "RandomDate"
+      params:
+        column: "birth_date"
+        engine: "random" # (1)
+        min: '1970-01-01'
+        max: '2000-01-01'
+
+
    +
  1. random engine is explicitly specified, although it is the default value.
    2. +
+

Results:

+ + + + + + + +
ColumnOriginalValueTransformedValue
birth_date1980-01-011970-02-23
+ +

Keep in mind that the random engine is always generates different values for the same input. For instance in we run +the previous example multiple times we will get different results.

+

Hash engine

+

The hash engine is designed to generate deterministic data. It uses the SHA-3 algorithm to hash the input value. The +hash engine is particularly useful when you need to generate the same output for the same input. For example, when you +want to transform values that are used as primary or foreign keys in a database.

+

For secure reason it is suggested set global greenmask salt via GREENMASK_GLOBAL_SALT environment variable. The salt +is added to the hash input to prevent the possibility of reverse engineering the original value from the hashed output. +The value is hex encoded with variadic length. For example, GREENMASK_GLOBAL_SALT=a5eddc84e762e810. +Generate a strong random salt and keep it secret.

+

The following example demonstrates how to configure the RandomInt transformer to generate deterministic data using the +hash engine. The public.account.id and public.orders.account_id columns will have the same values.

+
- schema: "public"
+  name: "account"
+  transformers:
+
+    - name: "RandomInt"
+      params:
+        column: "id"
+        engine: hash
+        min: 1
+        max: 2147483647
+
+- schema: "public"
+  name: "orders"
+  transformers:
+
+    - name: "RandomInt"
+      params:
+        column: "account_id"
+        engine: hash
+        min: 1
+        max: 2147483647
+
+

Result:

+
    +
  • public.account
    • +
+ + + + + + + +
ColumnOriginalValueTransformedValue
id1130162079
+ +
    +
  • public.orders
    • +
+ + + + + + + +
ColumnOriginalValueTransformedValue
account_id1130162079
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/built_in_transformers/transformation_inheritance/index.html b/v0.2.5/built_in_transformers/transformation_inheritance/index.html new file mode 100644 index 00000000..5f4402e1 --- /dev/null +++ b/v0.2.5/built_in_transformers/transformation_inheritance/index.html @@ -0,0 +1,3714 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Transformation inheritance - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +
+
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+ + + +
+
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+ + + +
+
+
+ + + +
+
+ + + + + + + +

Transformation Inheritance

+

Description

+

If you have partitioned tables or want to apply a transformation to a primary key and propagate it to all tables +referencing that column, you can do so with Greenmask.

+

Apply for inherited

+

Using apply_for_inherited, you can apply transformations to all partitions of a partitioned table, including any +subpartitions.

+

Configuration conflicts

+

When a partition has a transformation defined manually via config, and apply_for_inherited is set on the parent table, +Greenmask will merge both the inherited and manually defined configurations. The manually defined transformation will +execute last, giving it higher priority.

+

If this situation occurs, you will see the following information in the log:

+
{
+  "level": "info",
+  "ParentTableSchema": "public",
+  "ParentTableName": "sales",
+  "ChildTableSchema": "public",
+  "ChildTableName": "sales_2022_feb",
+  "ChildTableConfig": [
+    {
+      "name": "RandomDate",
+      "params": {
+        "column": "sale_date",
+        "engine": "random",
+        "max": "2005-01-01",
+        "min": "2001-01-01"
+      }
+    }
+  ],
+  "time": "2024-11-03T22:14:01+02:00",
+  "message": "config will be merged: found manually defined transformers on the partitioned table"
+}
+
+

Apply for references

+

Using apply_for_references, you can apply transformations to columns involved in a primary key or in tables with a +foreign key that references that column. This simplifies the transformation process by requiring you to define the +transformation only on the primary key column, which will then be applied to all tables referencing that column.

+

The transformer must be deterministic or support hash engine and the hash engin must be set in the +configuration file.

+

List of transformers that supports apply_for_references:

+
    +
  • Hash
    • +
  • NoiseDate
    • +
  • NoiseFloat
    • +
  • NoiseInt
    • +
  • NoiseNumeric
    • +
  • RandomBool
    • +
  • RandomDate
    • +
  • RandomEmail
    • +
  • RandomFloat
    • +
  • RandomInt
    • +
  • RandomIp
    • +
  • RandomMac
    • +
  • RandomNumeric
    • +
  • RandomString
    • +
  • RandomUuid
    • +
  • RandomUnixTimestamp
    • +
+

End-to-End Identifiers

+

End-to-end identifiers in databases are unique identifiers that are consistently used across multiple tables in a +relational database schema, allowing for a seamless chain of references from one table to another. These identifiers +typically serve as primary keys in one table and are propagated as foreign keys in other tables, creating a direct, +traceable link from one end of a data relationship to the other.

+

Greenmask can detect end-to-end identifiers and apply transformations across the entire sequence of tables. These +identifiers are detected when the following condition is met: the foreign key serves as both a primary key and a foreign +key in the referenced table.

+

Configuration conflicts

+

When on the referenced column a transformation is manually defined via config, and the apply_for_references is set on +parent table, the transformation defined will be chosen and the inherited transformation will be ignored. You will +receive a INFO message in the logs.

+
{
+  "level": "info",
+  "TransformerName": "RandomInt",
+  "ParentTableSchema": "public",
+  "ParentTableName": "tablea",
+  "ChildTableSchema": "public",
+  "ChildTableName": "tablec",
+  "ChildColumnName": "id2",
+  "TransformerConfig": {
+    "name": "RandomInt",
+    "apply_for_references": true
+  },
+  "time": "2024-11-03T21:28:10+02:00",
+  "message": "skipping apply transformer for reference: found manually configured transformer"
+}
+
+

Limitations

+
    +
  • The transformation must be deterministic.
    • +
  • The transformation condition will not be applied to the referenced column.
    • +
  • Not all transformers support apply_for_references
    • +
+
+

Warning

+

We do not recommend using apply_for_references with transformation conditions, as these conditions are not +inherited by transformers on the referenced columns. This may lead to inconsistencies in the data.

+
+

Example 1. Partitioned tables

+

In this example, we have a partitioned table sales that is partitioned by year and then by month. Each partition +contains a subset of data based on the year and month of the sale. The sales table has a primary key sale_id and is +partitioned by sale_date. The sale_date column is transformed using the RandomDate transformer.

+
CREATE TABLE sales
+(
+    sale_id   SERIAL         NOT NULL,
+    sale_date DATE           NOT NULL,
+    amount    NUMERIC(10, 2) NOT NULL
+) PARTITION BY RANGE (EXTRACT(YEAR FROM sale_date));
+
+-- Step 2: Create first-level partitions by year
+CREATE TABLE sales_2022 PARTITION OF sales
+    FOR VALUES FROM (2022) TO (2023)
+    PARTITION BY LIST (EXTRACT(MONTH FROM sale_date));
+
+CREATE TABLE sales_2023 PARTITION OF sales
+    FOR VALUES FROM (2023) TO (2024)
+    PARTITION BY LIST (EXTRACT(MONTH FROM sale_date));
+
+-- Step 3: Create second-level partitions by month for each year, adding PRIMARY KEY on each partition
+
+-- Monthly partitions for 2022
+CREATE TABLE sales_2022_jan PARTITION OF sales_2022 FOR VALUES IN (1)
+    WITH (fillfactor = 70);
+CREATE TABLE sales_2022_feb PARTITION OF sales_2022 FOR VALUES IN (2);
+CREATE TABLE sales_2022_mar PARTITION OF sales_2022 FOR VALUES IN (3);
+-- Continue adding monthly partitions for 2022...
+
+-- Monthly partitions for 2023
+CREATE TABLE sales_2023_jan PARTITION OF sales_2023 FOR VALUES IN (1);
+CREATE TABLE sales_2023_feb PARTITION OF sales_2023 FOR VALUES IN (2);
+CREATE TABLE sales_2023_mar PARTITION OF sales_2023 FOR VALUES IN (3);
+-- Continue adding monthly partitions for 2023...
+
+-- Step 4: Insert sample data
+INSERT INTO sales (sale_date, amount)
+VALUES ('2022-01-15', 100.00);
+INSERT INTO sales (sale_date, amount)
+VALUES ('2022-02-20', 150.00);
+INSERT INTO sales (sale_date, amount)
+VALUES ('2023-03-10', 200.00);
+
+

To transform the sale_date column in the sales table and all its partitions, you can use the following +configuration:

+
- schema: public
+  name: sales
+  apply_for_inherited: true
+  transformers:
+    - name: RandomDate
+      params:
+        min: "2022-01-01"
+        max: "2022-03-01"
+        column: "sale_date"
+        engine: "random"
+
+

Example 2. Simple table references

+

This is ordinary table references where the primary key of the users table is referenced in the orders table.

+
-- Enable the extension for UUID generation (if not enabled)
+CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
+
+CREATE TABLE users
+(
+    user_id  UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
+    username VARCHAR(50) NOT NULL
+);
+
+CREATE TABLE orders
+(
+    order_id   UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
+    user_id    UUID REFERENCES users (user_id),
+    order_date DATE NOT NULL
+);
+
+INSERT INTO users (username)
+VALUES ('john_doe');
+INSERT INTO users (username)
+VALUES ('jane_smith');
+
+INSERT INTO orders (user_id, order_date)
+VALUES ((SELECT user_id FROM users WHERE username = 'john_doe'), '2024-10-31'),
+       ((SELECT user_id FROM users WHERE username = 'jane_smith'), '2024-10-30');
+
+

To transform the username column in the users table, you can use the following configuration:

+
- schema: public
+  name: users
+  apply_for_inherited: true
+  transformers:
+    - name: RandomUuid
+      apply_for_references: true
+      params:
+        column: "user_id"
+        engine: "hash"
+
+

This will apply the RandomUuid transformation to the user_id column in the orders table automatically.

+

Example 3. References on tables with end-to-end identifiers

+

In this example, we have three tables: tablea, tableb, and tablec. All tables have a composite primary key. +In the tables tableb and tablec, the primary key is also a foreign key that references the primary key of tablea. +This means that all PKs are end-to-end identifiers.

+
CREATE TABLE tablea
+(
+    id1  INT,
+    id2  INT,
+    data VARCHAR(50),
+    PRIMARY KEY (id1, id2)
+);
+
+CREATE TABLE tableb
+(
+    id1    INT,
+    id2    INT,
+    detail VARCHAR(50),
+    PRIMARY KEY (id1, id2),
+    FOREIGN KEY (id1, id2) REFERENCES tablea (id1, id2) ON DELETE CASCADE
+);
+
+CREATE TABLE tablec
+(
+    id1         INT,
+    id2         INT,
+    description VARCHAR(50),
+    PRIMARY KEY (id1, id2),
+    FOREIGN KEY (id1, id2) REFERENCES tableb (id1, id2) ON DELETE CASCADE
+);
+
+INSERT INTO tablea (id1, id2, data)
+VALUES (1, 1, 'Data A1'),
+       (2, 1, 'Data A2'),
+       (3, 1, 'Data A3');
+
+INSERT INTO tableb (id1, id2, detail)
+VALUES (1, 1, 'Detail B1'),
+       (2, 1, 'Detail B2'),
+       (3, 1, 'Detail B3');
+
+INSERT INTO tablec (id1, id2, description)
+VALUES (1, 1, 'Description C1'),
+       (2, 1, 'Description C2'),
+       (3, 1, 'Description C3');
+
+

To transform the data column in tablea, you can use the following configuration:

+
- schema: public
+  name: "tablea"
+  apply_for_inherited: true
+  transformers:
+    - name: RandomInt
+      apply_for_references: true
+      params:
+        min: 0
+        max: 100
+        column: "id1"
+        engine: "hash"
+    - name: RandomInt
+      apply_for_references: true
+      params:
+        min: 0
+        max: 100
+        column: "id2"
+        engine: "hash"
+
+

This will apply the RandomInt transformation to the id1 and id2 columns in tableb and tablec automatically.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/commands/delete/index.html b/v0.2.5/commands/delete/index.html new file mode 100644 index 00000000..2102df49 --- /dev/null +++ b/v0.2.5/commands/delete/index.html @@ -0,0 +1,3239 @@ + + + + + + + + + + + + + + + + + + + + + + + + + delete - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

delete command

+

Delete dump from the storage with a specific ID

+
Supported flags
Usage:
+  greenmask delete [flags] [dumpId]
+
+Flags:
+      --before-date string   delete dumps older than the specified date in RFC3339Nano format: 2021-01-01T00:00.0:00Z
+      --dry-run              do not delete anything, just show what would be deleted
+      --prune-failed         prune failed dumps
+      --prune-unsafe         prune dumps with "unknown-or-failed" statuses. Works only with --prune-failed
+      --retain-for string    retain dumps for the specified duration in format: 1w2d3h4m5s6ms7us8ns
+      --retain-recent int    retain the most recent N completed dumps (default -1)
+
+
delete dump by id
greenmask --config config.yml delete 1723643249862
+
+
delete dumps older than the specified date
greenmask --config config.yml delete --before-date 2021-01-01T00:00.0:00Z --dry-run 
+
+
prune failed dumps
greenmask --config config.yml delete --prune-failed --dry-run 
+
+
prune dumps with 'unknown-or-failed' statuses
greenmask --config config.yml delete --prune-failed --prune-unsafe --dry-run
+
+
retain dumps for the specified duration
greenmask --config config.yml delete --retain-for 1w5d --dry-run
+
+
retain the most recent N completed dumps
greenmask --config config.yml delete --retain-recent 5 --dry-run
+
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/commands/dump/index.html b/v0.2.5/commands/dump/index.html new file mode 100644 index 00000000..3e5d2e34 --- /dev/null +++ b/v0.2.5/commands/dump/index.html @@ -0,0 +1,3362 @@ + + + + + + + + + + + + + + + + + + + + + + + + + dump - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

dump

+ +

dump command

+

The dump command operates in the following way:

+
    +
  1. Dumps the data from the source database.
    2. +
  2. Validates the data for potential issues.
    3. +
  3. Applies the defined transformations.
    4. +
  4. Stores the transformed data in the specified storage location.
    5. +
+

Note that the dump command shares the same parameters and environment variables as pg_dump, +allowing you to configure the restoration process as needed.

+

Mostly it supports the same flags as the pg_dump utility, with some extra flags for Greenmask-specific features.

+
Supported flags
  -b, --blobs                           include large objects in dump
+  -c, --clean                           clean (drop) database objects before recreating
+  -Z, --compress int                    compression level for compressed formats (default -1)
+  -C, --create                          include commands to create database in dump
+  -a, --data-only                       dump only the data, not the schema
+  -d, --dbname string                   database to dump (default "postgres")
+      --disable-dollar-quoting          disable dollar quoting, use SQL standard quoting
+      --disable-triggers                disable triggers during data-only restore
+      --enable-row-security             enable row security (dump only content user has access to)
+  -E, --encoding string                 dump the data in encoding ENCODING
+  -N, --exclude-schema strings          dump the specified schema(s) only
+  -T, --exclude-table strings           do NOT dump the specified table(s)
+      --exclude-table-data strings      do NOT dump data for the specified table(s)
+  -e, --extension strings               dump the specified extension(s) only
+      --extra-float-digits string       override default setting for extra_float_digits
+  -f, --file string                     output file or directory name
+  -h, --host string                     database server host or socket directory (default "/var/run/postgres")
+      --if-exists                       use IF EXISTS when dropping objects
+      --include-foreign-data strings    use IF EXISTS when dropping objects
+  -j, --jobs int                        use this many parallel jobs to dump (default 1)
+      --load-via-partition-root         load partitions via the root table
+      --lock-wait-timeout int           fail after waiting TIMEOUT for a table lock (default -1)
+  -B, --no-blobs                        exclude large objects in dump
+      --no-comments                     do not dump comments
+  -O, --no-owner string                 skip restoration of object ownership in plain-text format
+  -X, --no-privileges                   do not dump privileges (grant/revoke)
+      --no-publications                 do not dump publications
+      --no-security-labels              do not dump security label assignments
+      --no-subscriptions                do not dump subscriptions
+      --no-sync                         do not wait for changes to be written safely to dis
+      --no-synchronized-snapshots       do not use synchronized snapshots in parallel jobs
+      --no-tablespaces                  do not dump tablespace assignments
+      --no-toast-compression            do not dump TOAST compression methods
+      --no-unlogged-table-data          do not dump unlogged table data
+      --pgzip                           use pgzip compression instead of gzip
+  -p, --port int                        database server port number (default 5432)
+      --quote-all-identifiers           quote all identifiers, even if not key words
+  -n, --schema strings                  dump the specified schema(s) only
+  -s, --schema-only string              dump only the schema, no data
+      --section string                  dump named section (pre-data, data, or post-data)
+      --serializable-deferrable         wait until the dump can run without anomalies
+      --snapshot string                 use given snapshot for the dump
+      --strict-names                    require table and/or schema include patterns to match at least one entity each
+  -S, --superuser string                superuser user name to use in plain-text format
+  -t, --table strings                   dump the specified table(s) only
+      --test string                     connect as specified database user (default "postgres")
+      --use-set-session-authorization   use SET SESSION AUTHORIZATION commands instead of ALTER OWNER commands to set ownership
+  -U, --username string                 connect as specified database user (default "postgres")
+  -v, --verbose string                  verbose mode
+
+

Pgzip compression

+

By default, Greenmask uses gzip compression to restore data. In mist cases it is quite slow and does not utilize all +available resources and is a bootleneck for IO operations. To speed up the restoration process, you can use +the --pgzip flag to use pgzip compression instead of gzip. This method splits the data into blocks, which are +compressed in parallel, making it ideal for handling large volumes of data. The output remains a standard gzip file.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + +
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+ + + +
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+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/commands/index.html b/v0.2.5/commands/index.html new file mode 100644 index 00000000..a973b891 --- /dev/null +++ b/v0.2.5/commands/index.html @@ -0,0 +1,3253 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Commands - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
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+ + + + + + + +

Commands

+

Introduction

+
Greenmask available commands
greenmask \
+--log-format=[json|text] \
+--log-level=[debug|info|error] \
+--config=config.yml \
+[dump|list-dumps|delete|list-transformers|show-transformer|restore|show-dump]`
+
+

You can use the following commands within Greenmask:

+
    +
  • list-transformers — displays a list of available transformers along with their documentation
    • +
  • show-transformer — displays information about the specified transformer
    • +
  • validate - performs a validation procedure by testing config, comparing transformed data, identifying +potential issues, and checking for schema changes.
    • +
  • dump — initiates the data dumping process
    • +
  • restore — restores data to the target database either by specifying a dumpId or using the latest available dump
    • +
  • list-dumps — lists all available dumps stored in the system
    • +
  • show-dump — provides metadata information about a particular dump, offering insights into its structure and + attributes
    • +
  • delete — deletes a specific dump from the storage
    • +
+

For any of the commands mentioned above, you can include the following common flags:

+
    +
  • --log-format — specifies the desired format for log output, which can be either json or text. This parameter is +optional, with the default format set to text.
    • +
  • --log-level — sets the desired level for log output, which can be one of debug, info, or error. This parameter +is optional, with the default log level being info.
    • +
  • --config — requires the specification of a configuration file in YAML format. This configuration file is mandatory +for Greenmask to operate correctly.
    • +
  • --help — displays comprehensive help information for Greenmask, providing guidance on its usage and available +commands.
    • +
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/commands/list-dumps/index.html b/v0.2.5/commands/list-dumps/index.html new file mode 100644 index 00000000..df6420ce --- /dev/null +++ b/v0.2.5/commands/list-dumps/index.html @@ -0,0 +1,3295 @@ + + + + + + + + + + + + + + + + + + + + + + + + + list-dumps - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

list-dumps

+ +

list-dumps command

+

The list-dumps command provides a list of all dumps stored in the storage. The list includes the following attributes:

+
    +
  • ID — the unique identifier of the dump, used for operations like restore, delete, and show-dump
    • +
  • DATE — the date when the snapshot was created
    • +
  • DATABASE — the name of the database associated with the dump
    • +
  • SIZE — the original size of the dump
    • +
  • COMPRESSED SIZE — the size of the dump after compression
    • +
  • DURATION — the duration of the dump procedure
    • +
  • TRANSFORMED — indicates whether the dump has been transformed
    • +
  • STATUS — the status of the dump, which can be one of the following:
      +
    • done — the dump was completed successfully
      • +
    • in progress — the dump is currently being created
      • +
    • failed — the dump creation process failed
      • +
    • unknown or failed — the deprecated status of the dump that is used for failed dumps or dumps in progress for + version v0.1.14 and earlier
      • +
    +
    • +
+

Example of list-dumps output: +list_dumps_screen.png

+
+

Info

+

Greenmask uses a heartbeat mechanism to determine the status of a dump. +A dump is considered failed if it lacks a "done" heartbeat or if the last heartbeat timestamp exceeds 30 minutes. +Heartbeats are recorded every 15 minutes by the dump command while it is in progress. If greenmask fails unexpectedly, +the heartbeat stops being updated, and after 30 minutes (twice the interval), the dump is classified as failed. +The in progress status indicates that a dump is still ongoing.

+
+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/commands/list-transformers/index.html b/v0.2.5/commands/list-transformers/index.html new file mode 100644 index 00000000..e2670492 --- /dev/null +++ b/v0.2.5/commands/list-transformers/index.html @@ -0,0 +1,3315 @@ + + + + + + + + + + + + + + + + + + + + + + + + + list-transformers - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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list-transformers

+ +

list-transformers command

+

The list-transformers command provides a list of all the allowed transformers, including both standard and advanced +transformers. This list can be helpful for searching for an appropriate transformer for your data transformation needs.

+

To show a list of available transformers, use the following command:

+
greenmask --config=config.yml list-transformers
+
+

Supported flags:

+
    +
  • --format — allows to select the output format. There are two options available: text or json. The + default setting is text.
    • +
+

Example of list-transformers output:

+

list_transformers_screen.png

+

When using the list-transformers command, you receive a list of available transformers with essential information +about each of them. Below are the key parameters for each transformer:

+
    +
  • NAME — the name of the transformer
    • +
  • DESCRIPTION — a brief description of what the transformer does
    • +
  • COLUMN PARAMETER NAME — name of a column or columns affected by transformation
    • +
  • SUPPORTED TYPES — list the supported value types
    • +
+

The JSON call greenmask --config=config.yml list-transformers --format=json has the same attributes:

+
JSON format output
[
+  {
+    "name": "Cmd",
+    "description": "Transform data via external program using stdin and stdout interaction",
+    "parameters": [
+      {
+        "name": "columns",
+        "supported_types": [
+          "any"
+        ]
+      }
+    ]
+  },
+  {
+    "name": "Dict",
+    "description": "Replace values matched by dictionary keys",
+    "parameters": [
+      {
+        "name": "column",
+        "supported_types": [
+          "any"
+        ]
+      }
+    ]
+  }
+]
+
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
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+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/commands/restore/index.html b/v0.2.5/commands/restore/index.html new file mode 100644 index 00000000..ee5f95ad --- /dev/null +++ b/v0.2.5/commands/restore/index.html @@ -0,0 +1,3493 @@ + + + + + + + + + + + + + + + + + + + + + + + + + restore - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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restore

+ +

restore command

+

The restore command is used to restore a database from a previously created dump. You can specify the dump to restore +by providing the dump ID or use the latest keyword to restore the latest completed dump.

+
greenmask --config=config.yml restore DUMP_ID
+
+

Alternatively, to restore the latest completed dump, use the following command:

+
greenmask --config=config.yml restore latest
+
+

Note that the restore command shares the same parameters and environment variables as pg_restore, +allowing you to configure the restoration process as needed.

+

Mostly it supports the same flags as the pg_restore utility, with some extra flags for Greenmask-specific features.

+
Supported flags
      --batch-size int                  the number of rows to insert in a single batch during the COPY command (0 - all rows will be inserted in a single batch)
+  -c, --clean                           clean (drop) database objects before recreating
+  -C, --create                          create the target database
+  -a, --data-only                       restore only the data, no schema
+  -d, --dbname string                   connect to database name (default "postgres")
+      --disable-triggers                disable triggers during data-only restore
+      --enable-row-security             enable row security
+  -N, --exclude-schema strings          do not restore objects in this schema
+  -e, --exit-on-error                   exit on error, default is to continue
+  -f, --file string                     output file name (- for stdout)
+  -P, --function strings                restore named function
+  -h, --host string                     database server host or socket directory (default "/var/run/postgres")
+      --if-exists                       use IF EXISTS when dropping objects
+  -i, --index strings                   restore named index
+      --inserts                         restore data as INSERT commands, rather than COPY
+  -j, --jobs int                        use this many parallel jobs to restore (default 1)
+      --list-format string              use table of contents in format of text, json or yaml (default "text")
+      --no-comments                     do not restore comments
+      --no-data-for-failed-tables       do not restore data of tables that could not be created
+  -O, --no-owner string                 skip restoration of object ownership
+  -X, --no-privileges                   skip restoration of access privileges (grant/revoke)
+      --no-publications                 do not restore publications
+      --no-security-labels              do not restore security labels
+      --no-subscriptions                ddo not restore subscriptions
+      --no-table-access-method          do not restore table access methods
+      --no-tablespaces                  do not restore tablespace assignments
+      --on-conflict-do-nothing          add ON CONFLICT DO NOTHING to INSERT commands
+      --overriding-system-value         use OVERRIDING SYSTEM VALUE clause for INSERTs
+      --pgzip                           use pgzip decompression instead of gzip
+  -p, --port int                        database server port number (default 5432)
+      --restore-in-order                restore tables in topological order, ensuring that dependent tables are not restored until the tables they depend on have been restored
+  -n, --schema strings                  restore only objects in this schema
+  -s, --schema-only                     restore only the schema, no data
+      --section string                  restore named section (pre-data, data, or post-data)
+  -1, --single-transaction              restore as a single transaction
+      --strict-names                    restore named section (pre-data, data, or post-data) match at least one entity each
+  -S, --superuser string                superuser user name to use for disabling triggers
+  -t, --table strings                   restore named relation (table, view, etc.)
+  -T, --trigger strings                 restore named trigger
+  -L, --use-list string                 use table of contents from this file for selecting/ordering output
+      --use-set-session-authorization   use SET SESSION AUTHORIZATION commands instead of ALTER OWNER commands to set ownership
+  -U, --username string                 connect as specified database user (default "postgres")
+  -v, --verbose string                  verbose mode
+
+

Extra features

+

Inserts and error handling

+
+

Warning

+

Insert commands are a lot slower than COPY commands. Use this feature only when necessary.

+
+

By default, Greenmask restores data using the COPY command. If you prefer to restore data using INSERT commands, you +can +use the --inserts flag. This flag allows you to manage errors that occur during the execution of INSERT commands. By +configuring an error and constraint exclusion list in the config, +you can skip certain errors and continue inserting subsequent rows from the dump.

+

This can be useful when adding new records to an existing dump, but you don't want the process to stop if some records +already exist in the database or violate certain constraints.

+

By adding the --on-conflict-do-nothing flag, it generates INSERT statements with the ON CONFLICT DO NOTHING +clause, similar to the original pg_dump option. However, this approach only works for unique or exclusion constraints. +If a foreign key is missing in the referenced table or any other constraint is violated, the insertion will still fail. +To handle these issues, you can define +anexclusion list in the config.

+
example with inserts and error handling
```shell title="example with inserts and on conflict do nothing"
+greenmask --config=config.yml restore DUMP_ID --inserts --on-conflict-do-nothing
+
+

By adding the --overriding-system-value flag, it generates INSERT statements with the OVERRIDING SYSTEM VALUE +clause, which allows you to insert data into identity columns.

+
example of GENERATED ALWAYS AS IDENTITY column
CREATE TABLE people (
+    id integer GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
+    generated text GENERATED ALWAYS AS (id || first_name) STORED,
+    first_name text
+);
+
+
example with inserts
greenmask --config=config.yml restore DUMP_ID --inserts --overriding-system-value
+
+

Restoration in topological order

+

By default, Greenmask restores tables in the order they are listed in the dump file. To restore tables in topological +order, use the --restore-in-order flag. This flag ensures that dependent tables are not restored until the tables they +depend on have been restored.

+

This is useful when you have the schema already created with foreign keys and other constraints, and you want to insert +data into the tables in the correct order or catch-up the target database with the new data.

+
+

Warning

+

Greenmask cannot guarantee restoration in topological order when the schema contains cycles. The only way to restore +tables with cyclic dependencies is to temporarily remove the foreign key constraint (to break the cycle), restore the +data, and then re-add the foreign key constraint once the data restoration is complete.

+
+

If your database has cyclic dependencies you will be notified about it but the restoration will continue.

+
2024-08-16T21:39:50+03:00 WRN cycle between tables is detected: cannot guarantee the order of restoration within cycle cycle=["public.employees","public.departments","public.projects","public.employees"]
+
+

Pgzip decompression

+

By default, Greenmask uses gzip decompression to restore data. In mist cases it is quite slow and does not utilize all +available resources and is a bootleneck for IO operations. To speed up the restoration process, you can use +the --pgzip flag to use pgzip decompression instead of gzip. This method splits the data into blocks, which are +decompressed in parallel, making it ideal for handling large volumes of data.

+
example with pgzip decompression
greenmask --config=config.yml restore latest --pgzip
+
+

Restore data batching

+

The COPY command returns the error only on transaction commit. This means that if you have a large dump and an error +occurs, you will have to wait until the end of the transaction to see the error message. To avoid this, you can use the +--batch-size flag to specify the number of rows to insert in a single batch during the COPY command. If an error +occurs during the batch insertion, the error message will be displayed immediately. The data will be committed only +if all batches are inserted successfully.

+

This is useful when you want to be notified of errors as immediately as possible without waiting for the entire +table to be restored.

+
+

Warning

+

The batch size should be chosen carefully. If the batch size is too small, the restoration process will be slow. If +the batch size is too large, you may not be able to identify the error row.

+
+

In the example below, the batch size is set to 1000 rows. This means that 1000 rows will be inserted in a single batch, +so you will be notified of any errors immediately after each batch is inserted.

+
example with batch size
greenmask --config=config.yml restore latest --batch-size 1000
+
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/commands/show-dump/index.html b/v0.2.5/commands/show-dump/index.html new file mode 100644 index 00000000..2243360d --- /dev/null +++ b/v0.2.5/commands/show-dump/index.html @@ -0,0 +1,3874 @@ + + + + + + + + + + + + + + + + + + + + + + + + + show-dump - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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show-dump

+ +

show-dump command

+

This command provides details about all objects and data that can be restored, similar to the pg_restore -l command in +PostgreSQL. It helps you inspect the contents of the dump before performing the actual restoration.

+

Parameters:

+
    +
  • --format — format of printing. Can be text or json.
    • +
+

To display metadata information about a dump, use the following command:

+
greenmask --config=config.yml show-dump dumpID
+
+
+
+
+
+
+
;
+; Archive created at 2023-10-30 12:52:38 UTC
+; dbname: demo
+; TOC Entries: 17
+; Compression: -1
+; Dump Version: 15.4
+; Format: DIRECTORY
+; Integer: 4 bytes
+; Offset: 8 bytes
+; Dumped from database version: 15.4
+; Dumped by pg_dump version: 15.4
+;
+;
+; Selected TOC Entries:
+;
+3444; 0 0 ENCODING - ENCODING
+3445; 0 0 STDSTRINGS - STDSTRINGS
+3446; 0 0 SEARCHPATH - SEARCHPATH
+3447; 1262 24970 DATABASE - demo postgres
+3448; 0 0 DATABASE PROPERTIES - demo postgres
+222; 1259 24999 TABLE bookings flights postgres
+223; 1259 25005 SEQUENCE bookings flights_flight_id_seq postgres
+3460; 0 0 SEQUENCE OWNED BY bookings flights_flight_id_seq postgres
+3281; 2604 25030 DEFAULT bookings flights flight_id postgres
+3462; 0 24999 TABLE DATA bookings flights postgres
+3289; 2606 25044 CONSTRAINT bookings flights flights_flight_no_scheduled_departure_key postgres
+3291; 2606 25046 CONSTRAINT bookings flights flights_pkey postgres
+3287; 1259 42848 INDEX bookings flights_aircraft_code_status_idx postgres
+3292; 1259 42847 INDEX bookings flights_status_aircraft_code_idx postgres
+3293; 2606 25058 FK CONSTRAINT bookings flights flights_aircraft_code_fkey postgres
+3294; 2606 25063 FK CONSTRAINT bookings flights flights_arrival_airport_fkey postgres
+3295; 2606 25068 FK CONSTRAINT bookings flights flights_departure_airport_fkey postgres
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{
+  "startedAt": "2023-10-29T20:50:19.948017+02:00", // (1)
+  "completedAt": "2023-10-29T20:50:22.19333+02:00", // (2)
+  "originalSize": 4053842, // (3)
+  "compressedSize": 686557, // (4)
+  "transformers": [ // (5)
+    {
+      "Schema": "bookings", // (6)
+      "Name": "flights", // (7)
+      "Query": "", // (8)
+      "Transformers": [ // (9)
+        {
+          "Name": "RandomDate", // (10)
+          "Params": { // (11)
+            "column": "c2NoZWR1bGVkX2RlcGFydHVyZQ==",
+            "max": "MjAyMy0wMS0wMiAwMDowMDowMC4wKzAz",
+            "min": "MjAyMy0wMS0wMSAwMDowMDowMC4wKzAz"
+          }
+        }
+      ],
+      "ColumnsTypeOverride": null // (12)
+    }
+  ],
+  "header": { // (13)
+    "creationDate": "2023-10-29T20:50:20+02:00",
+    "dbName": "demo",
+    "tocEntriesCount": 15,
+    "dumpVersion": "16.0 (Homebrew)",
+    "format": "TAR",
+    "integer": 4,
+    "offset": 8,
+    "dumpedFrom": "16.0 (Debian 16.0-1.pgdg120+1)",
+    "dumpedBy": "16.0 (Homebrew)",
+    "tocFileSize": 8090,
+    "compression": 0
+  },
+  "entries": [ // (14)
+    {
+      "dumpId": 3416,
+      "databaseOid": 0,
+      "objectOid": 0,
+      "objectType": "ENCODING",
+      "schema": "",
+      "name": "ENCODING",
+      "owner": "",
+      "section": "PreData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": null
+    },
+    {
+      "dumpId": 3417,
+      "databaseOid": 0,
+      "objectOid": 0,
+      "objectType": "STDSTRINGS",
+      "schema": "",
+      "name": "STDSTRINGS",
+      "owner": "",
+      "section": "PreData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": null
+    },
+    {
+      "dumpId": 3418,
+      "databaseOid": 0,
+      "objectOid": 0,
+      "objectType": "SEARCHPATH",
+      "schema": "",
+      "name": "SEARCHPATH",
+      "owner": "",
+      "section": "PreData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": null
+    },
+    {
+      "dumpId": 3419,
+      "databaseOid": 16384,
+      "objectOid": 1262,
+      "objectType": "DATABASE",
+      "schema": "",
+      "name": "demo",
+      "owner": "postgres",
+      "section": "PreData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": null
+    },
+    {
+      "dumpId": 3420,
+      "databaseOid": 0,
+      "objectOid": 0,
+      "objectType": "DATABASE PROPERTIES",
+      "schema": "",
+      "name": "demo",
+      "owner": "postgres",
+      "section": "PreData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": null
+    },
+    {
+      "dumpId": 222,
+      "databaseOid": 16414,
+      "objectOid": 1259,
+      "objectType": "TABLE",
+      "schema": "bookings",
+      "name": "flights",
+      "owner": "postgres",
+      "section": "PreData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": null
+    },
+    {
+      "dumpId": 223,
+      "databaseOid": 16420,
+      "objectOid": 1259,
+      "objectType": "SEQUENCE",
+      "schema": "bookings",
+      "name": "flights_flight_id_seq",
+      "owner": "postgres",
+      "section": "PreData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": [
+        222
+      ]
+    },
+    {
+      "dumpId": 3432,
+      "databaseOid": 0,
+      "objectOid": 0,
+      "objectType": "SEQUENCE OWNED BY",
+      "schema": "bookings",
+      "name": "flights_flight_id_seq",
+      "owner": "postgres",
+      "section": "PreData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": [
+        223
+      ]
+    },
+    {
+      "dumpId": 3254,
+      "databaseOid": 16445,
+      "objectOid": 2604,
+      "objectType": "DEFAULT",
+      "schema": "bookings",
+      "name": "flights flight_id",
+      "owner": "postgres",
+      "section": "PreData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": [
+        223,
+        222
+      ]
+    },
+    {
+      "dumpId": 3434,
+      "databaseOid": 16414,
+      "objectOid": 0,
+      "objectType": "TABLE DATA",
+      "schema": "\"bookings\"",
+      "name": "\"flights\"",
+      "owner": "\"postgres\"",
+      "section": "Data",
+      "originalSize": 4045752,
+      "compressedSize": 678467,
+      "fileName": "3434.dat.gz",
+      "dependencies": []
+    },
+    {
+      "dumpId": 3261,
+      "databaseOid": 16461,
+      "objectOid": 2606,
+      "objectType": "CONSTRAINT",
+      "schema": "bookings",
+      "name": "flights flights_flight_no_scheduled_departure_key",
+      "owner": "postgres",
+      "section": "PostData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": [
+        222,
+        222
+      ]
+    },
+    {
+      "dumpId": 3263,
+      "databaseOid": 16463,
+      "objectOid": 2606,
+      "objectType": "CONSTRAINT",
+      "schema": "bookings",
+      "name": "flights flights_pkey",
+      "owner": "postgres",
+      "section": "PostData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": [
+        222
+      ]
+    },
+    {
+      "dumpId": 3264,
+      "databaseOid": 16477,
+      "objectOid": 2606,
+      "objectType": "FK CONSTRAINT",
+      "schema": "bookings",
+      "name": "flights flights_aircraft_code_fkey",
+      "owner": "postgres",
+      "section": "PostData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": [
+        222
+      ]
+    },
+    {
+      "dumpId": 3265,
+      "databaseOid": 16482,
+      "objectOid": 2606,
+      "objectType": "FK CONSTRAINT",
+      "schema": "bookings",
+      "name": "flights flights_arrival_airport_fkey",
+      "owner": "postgres",
+      "section": "PostData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": [
+        222
+      ]
+    },
+    {
+      "dumpId": 3266,
+      "databaseOid": 16487,
+      "objectOid": 2606,
+      "objectType": "FK CONSTRAINT",
+      "schema": "bookings",
+      "name": "flights flights_departure_airport_fkey",
+      "owner": "postgres",
+      "section": "PostData",
+      "originalSize": 0,
+      "compressedSize": 0,
+      "fileName": "",
+      "dependencies": [
+        222
+      ]
+    }
+  ]
+}
+

+
    +
  1. The date when the backup has been initiated, also indicating the snapshot date.
    2. +
  2. The date when the backup process was successfully completed.
    3. +
  3. The original size of the backup in bytes.
    4. +
  4. The size of the backup after compression in bytes.
    5. +
  5. A list of tables that underwent transformation during the backup.
    6. +
  6. The schema name of the table.
    7. +
  7. The name of the table.
    8. +
  8. Custom query override, if applicable.
    9. +
  9. A list of transformers that were applied during the backup.
    10. +
  10. The name of the transformer.
    11. +
  11. The parameters provided for the transformer.
    12. +
  12. A mapping of overridden column types.
    13. +
  13. The header information in the table of contents file. This provides the same details as the --format=text output in the previous snippet.
    14. +
  14. The list of restoration entries. This offers the same information as the --format=text output in the previous snippet.
    15. +
+
+
+
+
+

Note

+

The json format provides more detailed information compared to the text format. The text format is primarily used for backward compatibility and for generating a restoration list that can be used with pg_restore -L listfile. On the other hand, the json format provides comprehensive metadata about the dump, including information about the applied transformers and their parameters. The json format is especially useful for detailed dump introspection.

+
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/commands/show-transformer/index.html b/v0.2.5/commands/show-transformer/index.html new file mode 100644 index 00000000..b8a247c3 --- /dev/null +++ b/v0.2.5/commands/show-transformer/index.html @@ -0,0 +1,3362 @@ + + + + + + + + + + + + + + + + + + + + + + + + + show-transformer - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

show-transformer

+ +

show-transformer command

+

This command prints out detailed information about a transformer by a provided name, including specific attributes to +help you understand and configure the transformer effectively.

+

To show detailed information about a transformer, use the following command:

+
greenmask --config=config.yml show-transformer TRANSFORMER_NAME
+
+

Supported flags:

+
    +
  • --format — allows to select the output format. There are two options available: text or json. The + default setting is text.
    • +
+

Example of show-transformer output:

+

show_transformer.png

+

When using the show-transformer command, you receive detailed information about the transformer and its parameters and +their possible attributes. Below are the key parameters for each transformer:

+
    +
  • Name — the name of the transformer
    • +
  • Description — a brief description of what the transformer does
    • +
  • +

    Parameters — a list of transformer parameters, each with its own set of attributes. Possible attributes include:

    +
      +
    • description — a brief description of the parameter's purpose
      • +
    • required — a flag indicating whether the parameter is required when configuring the transformer
      • +
    • link_parameter — specifies whether the value of the parameter will be encoded using a specific parameter type + encoder. For example, if a parameter named column is linked to another parameter start, the start + parameter's value will be encoded according to the column type when the transformer is initialized.
      • +
    • cast_db_type — indicates that the value should be encoded according to the database type. For example, when + dealing with the INTERVAL data type, you must provide the interval value in PostgreSQL format.
      • +
    • default_value — the default value assigned to the parameter if it's not provided during configuration.
      • +
    • column_properties — if a parameter represents the name of a column, it may contain additional properties, + including:
        +
      • nullable — indicates whether the transformer may produce NULL values, potentially violating the NOT NULL + constraint
        • +
      • unique — specifies whether the transformer guarantees unique values for each call. If set to true, it + means that the transformer cannot produce duplicate values, ensuring compliance with the UNIQUE constraint.
        • +
      • affected — indicates whether the column is affected during the transformation process. If not affected, the + column's value might still be required for transforming another column.
        • +
      • allowed_types — a list of data types that are compatible with this parameter
        • +
      • skip_original_data — specifies whether the original value of the column, before transformation, is relevant + for the transformation process
        • +
      • skip_on_null — indicates whether the transformer should skip the transformation when the input column value + is NULL. If the column value is NULL, interaction with the transformer is unnecessary.
        • +
      +
      • +
    +
    • +
+
+

Warning

+

The default value in JSON format is base64 encoded. This might be changed in later version of Greenmask.

+
+
JSON output example
[
+  {
+    "properties": {
+      "name": "NoiseFloat",
+      "description": "Make noise float for int",
+      "is_custom": false
+    },
+    "parameters": [
+      {
+        "name": "column",
+        "description": "column name",
+        "required": true,
+        "is_column": true,
+        "is_column_container": false,
+        "column_properties": {
+          "max_length": -1,
+          "affected": true,
+          "allowed_types": [
+            "float4",
+            "float8",
+            "numeric"
+          ],
+          "skip_on_null": true
+        }
+      },
+      {
+        "name": "ratio",
+        "description": "max random percentage for noise",
+        "required": false,
+        "is_column": false,
+        "is_column_container": false,
+        "default_value": "MC4x"
+      },
+      {
+        "name": "decimal",
+        "description": "decimal of noised float value (number of digits after coma)",
+        "required": false,
+        "is_column": false,
+        "is_column_container": false,
+        "default_value": "NA=="
+      }
+    ]
+  }
+]
+
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/commands/validate/index.html b/v0.2.5/commands/validate/index.html new file mode 100644 index 00000000..2ec0cfd2 --- /dev/null +++ b/v0.2.5/commands/validate/index.html @@ -0,0 +1,3447 @@ + + + + + + + + + + + + + + + + + + + + + + + + + validate - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

validate command

+

The validate command allows you to perform a validation procedure and compare transformed data.

+

Below is a list of all supported flags for the validate command:

+
Supported flags
Usage:
+  greenmask validate [flags]
+
+Flags:
+      --data                  Perform test dump for --rows-limit rows and print it pretty
+      --diff                  Find difference between original and transformed data
+      --format string         Format of output. possible values [text|json] (default "text")
+      --rows-limit uint       Check tables dump only for specific tables (default 10)
+      --schema                Make a schema diff between previous dump and the current state
+      --table strings         Check tables dump only for specific tables
+      --table-format string   Format of table output (only for --format=text). Possible values [vertical|horizontal] (default "vertical")
+      --transformed-only      Print only transformed column and primary key
+      --warnings              Print warnings
+
+

Validate command can exit with non-zero code when:

+
    +
  • Any error occurred
    • +
  • Validate was called with --warnings flag and there are warnings
    • +
  • Validate was called with --schema flag and there are schema differences
    • +
+

All of those cases may be used for CI/CD pipelines to stop the process when something went wrong. This is especially +useful when --schema flag is used - this allows to avoid data leakage when schema changed.

+

You can use the --table flag multiple times to specify the tables you want to check. Tables can be written with +or without schema names (e. g., public.table_name or table_name). If you specify multiple tables from different +schemas, an error will be thrown.

+

To start validation, use the following command:

+
greenmask --config=config.yml validate \
+  --warnings \
+  --data \
+  --diff \
+  --schema \
+  --format=text \
+  --table-format=vertical \
+  --transformed-only \
+  --rows-limit=1
+
+
Validation output example
2024-03-15T19:46:12+02:00 WRN ValidationWarning={"hash":"aa808fb574a1359c6606e464833feceb","meta":{"ColumnName":"birthdate","ConstraintDef":"CHECK (birthdate \u003e= '1930-01-01'::date AND birthdate \u003c= (now() - '18 years'::interval))","ConstraintName":"humanresources","ConstraintSchema":"humanresources","ConstraintType":"Check","ParameterName":"column","SchemaName":"humanresources","TableName":"employee","TransformerName":"NoiseDate"},"msg":"possible constraint violation: column has Check constraint","severity":"warning"}
+
+

The validation output will provide detailed information about potential constraint violations and schema issues. Each +line contains nested JSON data under the ValidationWarning key, offering insights into the affected part of the +configuration and potential constraint violations.

+

Pretty formatted validation warning
{ 
+  "hash": "aa808fb574a1359c6606e464833feceb", // (13)
+  "meta": { // (1)
+    "ColumnName": "birthdate", // (2)
+    "ConstraintDef": "CHECK (birthdate >= '1930-01-01'::date AND birthdate <= (now() - '18 years'::interval))", // (3)
+    "ConstraintName": "humanresources", // (4)
+    "ConstraintSchema": "humanresources", // (5)
+    "ConstraintType": "Check", // (6)
+    "ParameterName": "column", // (7)
+    "SchemaName": "humanresources", // (8)
+    "TableName": "employee", // (9)
+    "TransformerName": "NoiseDate" // (10)
+  },
+  "msg": "possible constraint violation: column has Check constraint", // (11)
+  "severity": "warning" // (12)
+}
+

+
    +
  1. Detailed metadata. The validation output provides comprehensive metadata to pinpoint the source of problems.
    2. +
  2. Column name indicates the name of the affected column.
    3. +
  3. Constraint definition specifies the definition of the constraint that may be violated.
    4. +
  4. Constraint name identifies the name of the constraint that is potentially violated.
    5. +
  5. Constraint schema name indicates the schema in which the constraint is defined.
    6. +
  6. Type of constraint represents the type of constraint and can be one of the following: + 
    * ForeignKey
+* Check
+* NotNull
+* PrimaryKey
+* PrimaryKeyReferences
+* Unique
+* Length
+* Exclusion
+* TriggerConstraint
+
    7. +
  7. Table schema name specifies the schema name of the affected table.
    8. +
  8. Table name identifies the name of the table where the problem occurs.
    9. +
  9. Transformer name indicates the name of the transformer responsible for the transformation.
    10. +
  10. Name of affected parameter typically, this is the name of the column parameter that is relevant to the + validation warning.
    11. +
  11. Validation warning description provides a detailed description of the validation warning and the reason behind + it.
    12. +
  12. Severity of validation warning indicates the severity level of the validation warning and can be one of the + following: + 
    * error
+* warning
+* info
+* debug
+
    13. +
  13. Hash is a unique identifier of the validation warning. It is used to resolve the warning in the config file
    14. +
+
+

Note

+

A validation warning with a severity level of "error" is considered critical and must be addressed before the dump operation can proceed. Failure to resolve such warnings will prevent the dump operation from being executed.

+
+
Schema diff changed output example
2024-03-15T19:46:12+02:00 WRN Database schema has been changed Hint="Check schema changes before making new dump" PreviousDumpId=1710520855501
+2024-03-15T19:46:12+02:00 WRN Column renamed Event=ColumnRenamed Signature={"CurrentColumnName":"id1","PreviousColumnName":"id","TableName":"test","TableSchema":"public"}
+2024-03-15T19:46:12+02:00 WRN Column type changed Event=ColumnTypeChanged Signature={"ColumnName":"id","CurrentColumnType":"bigint","CurrentColumnTypeOid":"20","PreviousColumnType":"integer","PreviousColumnTypeOid":"23","TableName":"test","TableSchema":"public"}
+2024-03-15T19:46:12+02:00 WRN Column created Event=ColumnCreated Signature={"ColumnName":"name","ColumnType":"text","TableName":"test","TableSchema":"public"}
+2024-03-15T19:46:12+02:00 WRN Table created Event=TableCreated Signature={"SchemaName":"public","TableName":"test1","TableOid":"20563"}
+
+

Example of validation diff:

+

img.png

+

The validation diff is presented in a neatly formatted table. In this table:

+
    +
  • Columns that are affected by the transformation are highlighted with a red background.
    • +
  • The pre-transformation values are displayed in green.
    • +
  • The post-transformation values are shown in red.
    • +
  • The result in --format=text can be displayed in either horizontal (--table-format=horizontal) or + vertical (--table-format=vertical) format, making it easy to visualize and understand the + differences between the original and transformed data.
    • +
+

The whole validate command may be run in json format including logging making easy to parse the structure.

+
greenmask --config=config.yml validate \
+  --warnings \
+  --data \
+  --diff \
+  --schema \
+  --format=json \
+  --table-format=vertical \
+  --transformed-only \
+  --rows-limit=1 \
+  --log-format=json
+
+

The json object result

+
+
+
+
{
+  "level": "warn",
+  "ValidationWarning": {
+    "msg": "possible constraint violation: column has Check constraint",
+    "severity": "warning",
+    "meta": {
+      "ColumnName": "birthdate",
+      "ConstraintDef": "CHECK (birthdate >= '1930-01-01'::date AND birthdate <= (now() - '18 years'::interval))",
+      "ConstraintName": "humanresources",
+      "ConstraintSchema": "humanresources",
+      "ConstraintType": "Check",
+      "ParameterName": "column",
+      "SchemaName": "humanresources",
+      "TableName": "employee",
+      "TransformerName": "NoiseDate"
+    },
+    "hash": "aa808fb574a1359c6606e464833feceb"
+  },
+  "time": "2024-03-15T20:01:51+02:00"
+}
+
+
+
+
{
+  "level": "warn",
+  "PreviousDumpId": "1710520855501",
+  "Diff": [
+    {
+      "event": "ColumnRenamed",
+      "signature": {
+        "CurrentColumnName": "id1",
+        "PreviousColumnName": "id",
+        "TableName": "test",
+        "TableSchema": "public"
+      }
+    },
+    {
+      "event": "ColumnTypeChanged",
+      "signature": {
+        "ColumnName": "id",
+        "CurrentColumnType": "bigint",
+        "CurrentColumnTypeOid": "20",
+        "PreviousColumnType": "integer",
+        "PreviousColumnTypeOid": "23",
+        "TableName": "test",
+        "TableSchema": "public"
+      }
+    },
+    {
+      "event": "ColumnCreated",
+      "signature": {
+        "ColumnName": "name",
+        "ColumnType": "text",
+        "TableName": "test",
+        "TableSchema": "public"
+      }
+    },
+    {
+      "event": "TableCreated",
+      "signature": {
+        "SchemaName": "public",
+        "TableName": "test1",
+        "TableOid": "20563"
+      }
+    }
+  ],
+  "Hint": "Check schema changes before making new dump",
+  "time": "2024-03-15T20:01:51+02:00",
+  "message": "Database schema has been changed"
+}
+
+
+
+
{
+  "schema": "humanresources",
+  "name": "employee",
+  "primary_key_columns": [
+    "businessentityid"
+  ],
+  "with_diff": true,
+  "transformed_only": true,
+  "records": [
+    {
+      "birthdate": {
+        "original": "1969-01-29",
+        "transformed": "1964-10-20",
+        "equal": false,
+        "implicit": true
+      },
+      "businessentityid": {
+        "original": "1",
+        "transformed": "1",
+        "equal": true,
+        "implicit": true
+      }
+    }
+  ]
+}
+
+
+
+
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/configuration/index.html b/v0.2.5/configuration/index.html new file mode 100644 index 00000000..0b7844f5 --- /dev/null +++ b/v0.2.5/configuration/index.html @@ -0,0 +1,3821 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Configuration - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

Configuration

+ +
# Configuration
+
+

The configuration is organized into six sections:

+
    +
  • common — settings that can be used for both the dump and restore commands
    • +
  • log — settings for the logging subsystem
    • +
  • storage — settings for the storage locations where dumps are stored
    • +
  • dump — settings for the dump command. This section includes pg_dump options and transformation parameters.
    • +
  • restore — settings for the restore command. It contains pg_restore options and additional restoration + scripts.
    • +
  • custom_transformers — definitions of the custom transformers that interact through stdin and stdout. Once a custom transformer is configured, it becomes accessible via the greenmask list-transformers command.
    • +
+

common section

+

In the common section of the configuration, you can specify the following settings:

+
    +
  • pg_bin_path — path to the PostgreSQL binaries. Note that the PostgreSQL server version must match the provided binaries.
    • +
  • tmp_dir — temporary directory for storing the table of contents files. Default value is /tmp
    • +
+
+

Note

+

Greenmask exclusively manages data dumping and data restoration processes, delegating schema dumping to the pg_dumputility and schema restoration to the pg_restore utility. Both pg_dump and pg_restore rely on a toc.dat file located in a specific directory, which contains metadata and object definitions. Therefore, the tmp_dir parameter is essential for storing the toc.dat file during the dumping or restoration procedure. It is important to note that all artifacts in this directory will be automatically deleted once the Greenmask command is completed.

+
+

log section

+

In the log section of the configuration, you can specify the following settings:

+
    +
  • level — specifies the level of logging, which can be one of the following: debug, info, or error. The default level is info.
    • +
  • format — defines the logging format, which can be either json or text. The default format is text.
    • +
+

storage section

+

In the storage section, you can configure the storage driver for storing the dumped data. Currently, +two storage type options are supported: directory and s3.

+
+
+
+

The directory storage option refers to a filesystem directory where the dump data will be stored.

+

Parameters include path which specifies the path to the directory in the filesystem where the dumps will be stored.

+
directory storage config example
storage:
+  type: "directory"
+  directory:
+    path: "/home/user_name/storage_dir" # (1)
+
+
+
+

By choosing the s3 storage option, you can store dump data in an S3-like remote storage service, +such as Amazon S3 or Azure Blob Storage. Here are the parameters you can configure for S3 storage:

+
    +
  • endpoint — overrides the default AWS endpoint to a custom one for making requests
    • +
  • bucket — the name of the bucket where the dump data will be stored
    • +
  • prefix — a prefix for objects in the bucket, specified in path format
    • +
  • region — the S3 service region
    • +
  • storage_class — the storage class for performing object requests
    • +
  • no_verify_ssl — disable SSL certificate verification
    • +
  • access_key_id — access key for authentication
    • +
  • secret_access_key — secret access key for authentication
    • +
  • session_token — session token for authentication
    • +
  • role_arn — Amazon resource name for role-based authentication
    • +
  • session_name — role session name to uniquely identify a session
    • +
  • max_retries — the number of retries on request failures
    • +
  • cert_file — the path to the SSL certificate for making requests
    • +
  • max_part_size — the maximum part length for one request
    • +
  • concurrency — the number of goroutines to use in parallel for each upload call when sending parts
    • +
  • use_list_objects_v1 — use the old v1 ListObjects request instead of v2 one
    • +
  • force_path_style — force the request to use path-style addressing (e. g., http://s3.amazonaws.com/BUCKET/KEY) instead of virtual hosted bucket addressing (e. g., http://BUCKET.s3.amazonaws.com/KEY)
    • +
  • use_accelerate — enable S3 Accelerate feature
    • +
+
s3 storage config example for Minio running in Docker
storage:  
+  type: "s3"
+  s3:
+    endpoint: "http://localhost:9000"
+    bucket: "testbucket"
+    region: "us-east-1"
+    access_key_id: "Q3AM3UQ867SPQQA43P2F"
+    secret_access_key: "zuf+tfteSlswRu7BJ86wekitnifILbZam1KYY3TG"
+
+
+
+
+

dump section

+

In the dump section of the configuration, you configure the greenmask dump command. It includes the following parameters:

+
    +
  • pg_dump_options — a map of pg_dump options to configure the behavior of the command itself. You can refer to the list of supported pg_dump options in the Greenmask dump command documentation.
    • +
  • +

    transformation — this section contains configuration for applying transformations to table columns during the dump operation. It includes the following sub-parameters:

    +
      +
    • schema — the schema name of the table
      • +
    • name — the name of the table
      • +
    • subset_conds - list of the conditions to filter the rows to be dumped. The conditions are combined with AND operator. For details read Database subset
      • +
    • +

      query — an optional parameter for specifying a custom query to be used in the COPY command. By default, the entire table is dumped, but you can use this parameter to set a custom query.

      +
      +

      Warning

      +

      Be cautious when using the query parameter, as it may lead to constraint violation errors during restoration, and Greenmask currently cannot handle query validation.

      +
      +
      • +
    • +

      columns_type_override — allows you to override the column types explicitly. You can associate a column with another type that is supported by your transformer. This is useful when the transformer works strictly with specific types of columns. For example, if a column named post_code is of the TEXT type, but the RandomInt transformer works only with INT family types, you can override it as shown in the example provided. +

      column type overridden example
        columns_type_override:
+    post_code: "int4"  # (1)
+

      +
        +
      1. Change the data type of the post_code column to INT4 (INTEGER)
        2. +
      +
      • +
    • +

      apply_for_inherited — an optional parameter to apply the same transformation to all partitions if the table is partitioned. This can save you from defining the transformation for each partition manually.

      +
      +

      Warning

      +

      It is recommended to use the --load-via-partition-root parameter when dealing with partitioned tables, as the partition key value might change.

      +
      +
      • +
    • +

      transformers — a list of transformers to apply to the table, along with their parameters. Each transformation item includes the following sub-parameters:

      +
        +
      • name — the name of the transformer
        • +
      • params — a map of the provided transformer parameters
        • +
      +
      transformers config example
         transformers:
+    - name: "RandomDate"
+      params:
+        min: "2023-01-01 00:00:00.0+03"
+        max: "2023-01-02 00:00:00.0+03"
+        column: "scheduled_departure"
+
+    - name: "NoiseDate"
+      params:
+        ratio: "01:00:00"
+        column: "scheduled_arrival"
+
      +
      • +
    +
    • +
+

Here is an example configuration for the dump section:

+

dump section config example
dump:
+  pg_dump_options:
+    dbname: "host=/run/postgresql user=postgres dbname=demo"
+    jobs: 10
+    exclude-schema: "(\"teSt\"*|test*)"
+    table: "bookings.flights"
+    load-via-partition-root: true
+
+  transformation:
+    - schema: "bookings"
+      name: "flights"
+      query: "select * from bookings.flights3 limit 1000000"
+      columns_type_override:
+        post_code: "int4" # (1)
+      transformers:
+        - name: "RandomDate"
+          params:
+            min: "2023-01-01 00:00:00.0+03"
+            max: "2023-01-02 00:00:00.0+03"
+            column: "scheduled_departure"
+
+        - name: "NoiseDate"
+          params:
+            ratio: "01:00:00"
+            column: "scheduled_arrival"
+
+        - name: "RegexpReplace"
+          params:
+            column: "status"
+            regexp: "On Time"
+            replace: "Delayed"
+
+        - name: "RandomInt" # (2)
+          params:
+            column: "post_code"
+            min: "11"
+            max: "99"
+
+    - schema: "bookings"
+      name: "aircrafts_data"
+      subset_conds: # (3)
+        - "bookings.aircrafts_data.model = 'Boeing 777-300-2023'"
+      transformers:
+        - name: "Json"
+          params:
+            column: "model"
+            operations:
+              - operation: "set"
+                path: "en"
+                value: "Boeing 777-300-2023"
+              - operation: "set"
+                path: "crewSize"
+                value: 10
+
+        - name: "NoiseInt"
+          params:
+            ratio: 0.9
+            column: "range"
+

+
    +
  1. Override the post_code column type to int4 (INTEGER). This is necessary because the post_code column + originally has a TEXT type, but it contains values that resemble integers. By explicitly overriding the type to int4, we ensure compatibility with transformers that work with integer types, such as RandomInt.
    2. +
  2. After the type is overridden, we can apply a compatible transformer.
    3. +
  3. Database subset condition applied to the aircrafts_data table. The subset condition filters the data based on the model column.
    4. +
+

validate section

+

In the validate section of the configuration, you can specify parameters for the greenmask validate +command. Here is an example of the validate section configuration:

+

validate section config example
validate:
+  tables: # (1)
+    - "orders"
+    - "public.cart"
+  data: true # (2)
+  diff: true # (3)
+  rows_limit: 10 # (4)
+  resolved_warnings: # (5)
+    - "8d436fae67b2b82b36bd3afeb0c93f30"
+  table_format: "horizontal" # (7)
+  format: "text" # (6)
+  schema: true # (8)
+  transformed_only: true # (9)
+  warnings: true # (10)
+

+
    +
  1. A list of tables to validate. If this list is not empty, the validation operation will only be performed for the specified tables. Tables can be written with or without the schema name (e. g., "public.cart" or "orders").
    2. +
  2. Specifies whether to perform data transformation for a limited set of rows. If set to true, data transformation will be performed, and the number of rows transformed will be limited to the value specified in the rows_limit parameter (default is 10).
    3. +
  3. Specifies whether to perform diff operations for the transformed data. If set to true, the validation process will find the differences between the original and transformed data. See more details in the validate command documentation.
    4. +
  4. Limits the number of rows to be transformed during validation. The default limit is 10 rows, but you can change it by modifying this parameter.
    5. +
  5. A hash list of resolved warnings. These warnings have been addressed and resolved in a previous validation run.
    6. +
  6. Specifies the format of the transformation output. Possible values are [horizontal|vertical]. The default format is horizontal. You can choose the format that suits your needs. See more details in the validate command documentation.
    7. +
  7. The output format (json or text)
    8. +
  8. Specifies whether to validate the schema current schema with the previous and print the differences if any.
    9. +
  9. If set to true, transformation output will be only with the transformed columns and primary keys
    10. +
  10. If set to then all the warnings be printed
    11. +
+

restore section

+

In the restore section of the configuration, you can specify parameters for the greenmask restore command. It contains pg_restore settings and custom script execution settings. Below you can find the available parameters:

+
    +
  • pg_restore_options — a map of pg_restore options that are used to configure the behavior of + the pg_restore utility during the restoration process. You can refer to the list of supported pg_restore options in the Greenmask restore command documentation.
    • +
  • scripts — a map of custom scripts to be executed during different restoration stages. Each script is associated with a specific restoration stage and includes the following attributes:
      +
    • [pre-data|data|post-data] — the name of the restoration stage when the script should be executed; has the following parameters:
        +
      • name — the name of the script
        • +
      • when — specifies when to execute the script, which can be either "before" or "after" the + specified restoration stage
        • +
      • query — an SQL query string to be executed
        • +
      • query_file — the path to an SQL query file to be executed
        • +
      • command — a command with parameters to be executed. It is provided as a list, where the first item is the command name.
        • +
      +
      • +
    +
    • +
  • insert_error_exclusions — a list of error codes that should be ignored during the restoration process. This is +useful when you want to skip specific errors that are not critical for the restoration process.
    • +
+

As mentioned in the architecture, a backup contains three sections: pre-data, data, and post-data. The custom script execution allows you to customize and control the restoration process by executing scripts or commands at specific stages. The available restoration stages and their corresponding execution conditions are as follows:

+
    +
  • pre-data — scripts or commands can be executed before or after restoring the pre-data section
    • +
  • data — scripts or commands can be executed before or after restoring the data section
    • +
  • post-data — scripts or commands can be executed before or after restoring the post-data section
    • +
+

Each stage can have a "when" condition with one of the following possible values:

+
    +
  • before — execute the script or SQL command before the mentioned restoration stage
    • +
  • after — execute the script or SQL command after the mentioned restoration stage
    • +
+

Below you can find one of the possible versions for the scripts part of the restore section:

+

scripts definition example
scripts:
+  pre-data: # (1)
+    - name: "pre-data before script [1] with query"
+      when: "before"
+      query: "create table script_test(stage text)"
+    - name: "pre-data before script [2]"
+      when: "before"
+      query: "insert into script_test values('pre-data before')"
+    - name: "pre-data after test script [1]"
+      when: "after"
+      query: "insert into script_test values('pre-data after')"
+    - name: "pre-data after script with query_file [1]"
+      when: "after"
+      query_file: "pre-data-after.sql"
+  data: # (2)
+    - name: "data before script with command [1]"
+      when: "before"
+      command: # (4)
+        - "data-after.sh"
+        - "param1"
+        - "param2"
+    - name: "data after script [1]"
+      when: "after"
+      query_file: "data-after.sql"
+  post-data: # (3)
+    - name: "post-data before script [1]"
+      when: "before"
+      query: "insert into script_test values('post-data before')"
+    - name: "post-data after script with query_file [1]"
+      when: "after"
+      query_file: "post-data-after.sql"
+

+
    +
  1. List of pre-data stage scripts. This section contains scripts that are executed before or after the restoration of the pre-data section. The scripts include SQL queries and query files.
    2. +
  2. List of data stage scripts. This section contains scripts that are executed before or after the restoration of the data section. The scripts include shell commands with parameters and SQL query files.
    3. +
  3. List of post-data stage scripts. This section contains scripts that are executed before or after the restoration of the post-data section. The scripts include SQL queries and query files.
    4. +
  4. Command in the first argument and the parameters in the rest of the list. When specifying a command to be executed in the scripts section, you provide the command name as the first item in a list, followed by any parameters or arguments for that command. The command and its parameters are provided as a list within the script configuration.
    5. +
+

restoration error exclusion

+

You can configure which errors to ignore during the restoration process by setting the insert_error_exclusions +parameter. This parameter can be applied globally or per table. If both global and table-specific settings are defined, +the table-specific settings will take precedence. Below is an example of how to configure the insert_error_exclusions +parameter. You can specify constraint names from your database schema or the error codes returned by PostgreSQL. +codes in the PostgreSQL documentation.

+
parameter defintion
insert_error_exclusions:
+
+  global:
+    error_codes: ["23505"] # (1)
+    constraints: ["PK_ProductReview_ProductReviewID"] # (2)
+  tables: # (3)
+    - schema: "production"
+      name: "productreview"
+      constraints: ["PK_ProductReview_ProductReviewID"]
+      error_codes: ["23505"]
+
+
    +
  1. List of strings that contains postgresql error codes
    2. +
  2. List of strings that contains constraint names (globally)
    3. +
  3. List of tables with their schema, name, constraints, and error codes
    4. +
+

Here is an example configuration for the restore section:

+
restore:
+  scripts:
+      pre-data: # (1)
+        - name: "pre-data before script [1] with query"
+          when: "before"
+          query: "create table script_test(stage text)"
+
+  insert_error_exclusions:
+    tables:
+      - schema: "production"
+        name: "productreview"
+        constraints:
+          - "PK_ProductReview_ProductReviewID"
+        error_codes:
+          - "23505"
+    global:
+      error_codes:
+        - "23505"
+
+  pg_restore_options:
+    jobs: 10
+    exit-on-error: false
+    dbname: "postgresql://postgres:example@localhost:54316/transformed"
+    table: 
+      - "productreview"
+    pgzip: true
+    inserts: true
+    on-conflict-do-nothing: true
+    restore-in-order: true
+
+

Environment variable configuration

+

It's also possible to configure Greenmask through environment variables.

+

Greenmask will automatically parse any environment variable that matches the configuration in the config file by substituting the dot (.) separator for an underscore (_) and uppercasing it. As an example, the config file below would apply the same configuration as defining the LOG_LEVEL=debug environment variable

+
config.yaml
log:
+  level: debug
+
+

Global configuration variables

+
    +
  • GREENMASK_GLOBAL_SALT - global salt value hex encoded with variadic length, used for the hash engine. For details + read Transformation engines section.
    • +
+

Postgres connection variables

+

Additionaly, there are some environment variables exposed by the dump and restore commands to facilitate the connection configuration with a Postgres database

+
    +
  • PGHOST - host used to connect to the postgres database
    • +
  • PGPORT - port where postgres is exposed
    • +
  • PGDATABASE - name of the database to dump/restore
    • +
  • PGUSER - username used to connect to the postgres database
    • +
  • PGPASSWORD - password used to authenticate to the postgres database
    • +
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/database_subset/index.html b/v0.2.5/database_subset/index.html new file mode 100644 index 00000000..2319f41e --- /dev/null +++ b/v0.2.5/database_subset/index.html @@ -0,0 +1,4101 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Database subset - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + +
+
+
+ + + +
+
+ + + + + + + +

Database subset

+

Greenmask allows you to define a subset condition for filtering data during the dump process. This feature is useful +when you need to dump only a part of the database, such as a specific table or a set of tables. It automatically +ensures data consistency by including all related data from other tables that are required to maintain the integrity of +the subset. The subset condition can be defined using subset_conds attribute that can be defined on the table in the +transformation section (see examples).

+
+

Info

+

Greenmask genrates queries for subset conditions based on the introspected schema using joins and recursive queries. +It cannot be responsible for query optimization. The subset quries might be slow due to the complexity of +the queries and/or lack of indexes. Circular are resolved using recursive queries.

+
+

Detail

+

The subset is a list of SQL conditions that are applied to table. The conditions are combined with AND operator. You +need to specify the schema, table and column name when pointing out the column to filter by to avoid +ambiguity. The subset condition must be a valid SQL condition.

+
Subset condition example
subset_conds:
+  - 'person.businessentity.businessentityid IN (274, 290, 721, 852)'
+
+

Use cases

+
    +
  • Database scale down - create anonymized dump but for the limited and consistent set of tables
    • +
  • Data migration - migrate only some records from one database to another
    • +
  • Data anonymization - dump and anonymize only a specific records in the database
    • +
  • Database catchup - catchup your another instance of database logically by adding a new records. In this case it + is recommended to restore tables in topological order using + --restore-in-order.
    • +
+

References with NULL values

+

For references that do not have NOT NULL constraints, Greenmask will automatically generate LEFT JOIN queries +with the appropriate conditions to ensure integrity checks. You can rely on Greenmask to handle such cases correctly—no +special configuration is needed, as it performs this automatically based on the introspected schema.

+

Circular reference

+

Greenmask supports circular references between tables. You can define a subset condition for any table, and +Greenmask will automatically generate the appropriate queries for the table subset using recursive queries. The subset +system ensures data consistency by validating all records found through the recursive queries. If a record does not meet +the subset condition, it will be excluded along with its parent records, preventing constraint violations.

+
+

Warning

+

Currently (v0.2b2), Greenmask can resolve multi-cylces in one strogly connected component, but only for one group +of vertexes. If you have SSC that contains 2 groups of vertexes, Greenmask will not be able to +resolve it. For instance we have 2 cycles with tables A, B, C (first group) and B, C, E (second group). +Greenmask will not be able to resolve it. But if you have only one group of vertexes one and more cycles in the +same group of tables (for instance A, B, C), Greenmask works with it. This will be fixed in the future. +See second example below. In practice this is quite rare situation and 99% of people will not face this issue.

+
+

You can read the Wikipedia article about Circular reference here.

+

Virtual references

+

During the development process, there are situations where foreign keys need to be removed. The reasons can +vary—from improving performance to simplifying the database structure. Additionally, some foreign keys may exist within +loosely structured data, such as JSON, where PostgreSQL cannot create foreign keys at all. These limitations could +significantly hinder the capabilities of a subset system. Greenmask offers a flexible solution to this problem by +allowing the declaration of virtual references in the configuration, enabling the preservation and management of logical +relationships between tables, even in the absence of explicit foreign keys. Virtual reference can be called virtual +foreign key as well.

+

The virtual_references can be defined in dump section. It contains the list of virtual references. First you set +the table where you want to define virtual reference. In the attribute references define the list of tables that are +referenced by the table. In the columns attribute define the list of columns that are used in the foreign key +reference. The not_null attribute is optional and defines if the FK has not null constraint. If true Greenmask will +generate INNER JOIN instead of LEFT JOIN by default it is false. The expression needs to be used when you +want to use some expression to get the value of the column in the referencing table. For instance, if you have JSONB +column in the audit_logs table that contains order_id field, you can use this field as FK reference.

+
+

Info

+

You do not need to define primry key of the referenced table. Greenmask will automatically resolve it and use it in +the join condition.

+
+
Virtual references example
dump:
+  virtual_references:
+    - schema: "public" # (1)
+      name: "orders" # (2)
+      references: # (3)
+        - schema: "public" # (4) 
+          name: "customers" # (5)
+          columns: # (6)
+            - name: "customer_id"
+          not_null: false # (7)
+
+    - schema: "public"
+      name: "audit_logs"
+      references:
+        - schema: "public"
+          name: "orders"
+          columns:
+            - expression: "(public.audit_logs.log_data ->> 'order_id')::INT" # (8)
+
+
    +
  1. The schema name of table that has foreign key reference (table that own FK reference)
    2. +
  2. The table name that has foreign key reference (table that own FK reference)
    3. +
  3. List of virtual references
    4. +
  4. The schema name of the table that has foreign key reference (referencing table)
    5. +
  5. The table name that has foreign key reference (referencing table)
    6. +
  6. +

    List of columns that are used in the foreign key reference. Each column has one of property defined at the same time:

    +
      +
    • name - column name in the referencing table
      • +
    • expression - expression that is used to get the value of the column in the referencing table
      • +
    +
    7. +
  7. +

    not_null - is FK has not null constraint. If true Default it is false

    +
    8. +
  8. expression - expression that is used to get the value of the column in the referencing table
    9. +
+

Polymorphic references

+

Greenmask supports polymorphic references. You can define a virtual reference for a table with polymorphic references +using polymorphic_exprs attribute. The polymorphic_exprs attribute is a list of expressions that are used to make +a polymorphic reference. For instance we might have a table comments that has polymorphic reference to posts and +videos. The table comments might have commentable_id and commentable_type columns. The commentable_type column +contains the type of the table that is referenced by the commentable_id column. The example of the config:

+
Polymorphic references example
dump:
+  virtual_references:
+    - schema: "public"
+      name: "comments"
+      references:
+        - schema: "public"
+          name: "videos"
+          polymorphic_exprs:
+            - "public.comments.commentable_type = 'video'"
+          columns:
+            - name: "commentable_id"
+        - schema: "public"
+          name: "posts"
+          polymorphic_exprs:
+            - "public.comments.commentable_type = 'post'"
+          columns:
+            - name: "commentable_id"
+
+
+

Warning

+

The plimorphic references cannot be non_null because the commentable_id column can be NULL if the +commentable_type is not set or different that the values defined in the polymorphic_exprs attribute.

+
+

Troubleshooting

+

Exclude the records that has NULL values in the referenced column

+

If you want to exclude records that have NULL values in the referenced column, you can manually add this condition to +the subset condition for the table. Greenmask does not automatically exclude records with NULL values because it applies +a LEFT OUTER JOIN on nullable foreign keys.

+

Some table is not filtered by the subset condition

+

Greenmask builds a table dependency graph based on the introspected schema and existing foreign keys. If a table is not +filtered by the subset condition, it means that the table either does not reference another table that is filtered by +the subset condition or the table itself does not have a subset condition applied.

+

If you have a table with a removed foreign key and want to filter it by the subset condition, you need to define a +virtual reference. For more information on virtual references, refer to the Virtual References +section.

+
+

Info

+

If you find any issues related to the code or greenmask is not working as expected, do not hesitate to contact us + directly or by creating an issue in the repository.

+
+

ERROR: column reference "id" is ambiguous

+

If you see the error message ERROR: column reference "{column name}" is ambiguous, you have specified the column name +without the table and/or schema name. To avoid ambiguity, always specify the schema and table name when pointing out the +column to filter by. For instance if you want to filter employees by employee_id column, you should +use public.employees.employee_id instead of employee_id.

+
Valid subset condition
public.employees.employee_id IN (1, 2, 3)
+
+

The subset condition is not working correctly. How can I verify it?

+

Run greenmask with --log-level=debug to see the generated SQL queries. You will find the generated SQL queries in the +log output. Validate this query in your database client to ensure that the subset condition is working as expected.

+

For example:

+
$ greenmask dump --config config.yaml --log-level=debug
+
+2024-08-29T19:06:18+03:00 DBG internal/db/postgres/context/context.go:202 > Debug query Schema=person Table=businessentitycontact pid=1638339
+2024-08-29T19:06:18+03:00 DBG internal/db/postgres/context/context.go:203 > SELECT "person"."businessentitycontact".* FROM "person"."businessentitycontact"  INNER JOIN "person"."businessentity" ON "person"."businessentitycontact"."businessentityid" = "person"."businessentity"."businessentityid" AND ( person.businessentity.businessentityid between 400 and 800 OR person.businessentity.businessentityid between 800 and 900 ) INNER JOIN "person"."person" ON "person"."businessentitycontact"."personid" = "person"."person"."businessentityid" WHERE TRUE AND (("person"."person"."businessentityid") IN (SELECT "person"."businessentity"."businessentityid" FROM "person"."businessentity"   WHERE ( ( person.businessentity.businessentityid between 400 and 800 OR person.businessentity.businessentityid between 800 and 900 ) )))
+ pid=1638339
+
+

Dump is too slow

+

If the dump process is too slow the generated query might be too complex. In this case you can:

+
    +
  • Check if the database has indexes on the columns used in the subset condition. Create them if possible.
    • +
  • Move database dumping on the replica to avoid the performance impact on the primary.
    • +
+

Example: Dump a subset of the database

+
+

Info

+

All examples based on playground database. Read more about the playground database in the +Playground section.

+
+

The following example demonstrates how to dump a subset of the person schema. The subset condition is applied to the +businessentity and password tables. The subset condition filters the data based on the businessentityid and +passwordsalt columns, respectively.

+
Subset configuration example
transformation:
+  - schema: "person"
+    name: "businessentity"
+    subset_conds:
+      - 'person.businessentity.businessentityid IN (274, 290, 721, 852)'
+    transformers:
+      - name: "RandomDate"
+        params:
+          column: "modifieddate"
+          min: "2020-01-01 00:00:00"
+          max: "2024-06-26 00:00:00"
+          truncate: "day"
+          keep_null: false
+
+  - schema: "person"
+    name: "password"
+    subset_conds:
+      - >
+        person.password.passwordsalt = '329eacbe-c883-4f48-b8b6-17aa4627efff'
+
+

Example: Dump a subset with circular reference

+
Create tables with multi cyles
-- Step 1: Create tables without foreign keys
+DROP TABLE IF EXISTS employees CASCADE;
+CREATE TABLE employees
+(
+    employee_id   SERIAL PRIMARY KEY,
+    name          VARCHAR(100) NOT NULL,
+    department_id INT -- Will reference departments(department_id)
+);
+
+DROP TABLE IF EXISTS departments CASCADE;
+CREATE TABLE departments
+(
+    department_id SERIAL PRIMARY KEY,
+    name          VARCHAR(100) NOT NULL,
+    project_id    INT -- Will reference projects(project_id)
+);
+
+DROP TABLE IF EXISTS projects CASCADE;
+CREATE TABLE projects
+(
+    project_id       SERIAL PRIMARY KEY,
+    name             VARCHAR(100) NOT NULL,
+    lead_employee_id INT, -- Will reference employees(employee_id)
+    head_employee_id INT  -- Will reference employees(employee_id)
+);
+
+-- Step 2: Alter tables to add foreign key constraints
+ALTER TABLE employees
+    ADD CONSTRAINT fk_department
+        FOREIGN KEY (department_id) REFERENCES departments (department_id);
+
+ALTER TABLE departments
+    ADD CONSTRAINT fk_project
+        FOREIGN KEY (project_id) REFERENCES projects (project_id);
+
+ALTER TABLE projects
+    ADD CONSTRAINT fk_lead_employee
+        FOREIGN KEY (lead_employee_id) REFERENCES employees (employee_id);
+
+ALTER TABLE projects
+    ADD CONSTRAINT fk_lead_employee2
+        FOREIGN KEY (head_employee_id) REFERENCES employees (employee_id);
+
+-- Insert projects
+INSERT INTO projects (name, lead_employee_id)
+SELECT 'Project ' || i, NULL
+FROM generate_series(1, 10) AS s(i);
+
+-- Insert departments
+INSERT INTO departments (name, project_id)
+SELECT 'Department ' || i, i
+FROM generate_series(1, 10) AS s(i);
+
+-- Insert employees and assign 10 of them as project leads
+INSERT INTO employees (name, department_id)
+SELECT 'Employee ' || i, (i / 10) + 1
+FROM generate_series(1, 99) AS s(i);
+
+-- Assign 10 employees as project leads
+UPDATE projects
+SET lead_employee_id = (SELECT employee_id
+                        FROM employees
+                        WHERE employees.department_id = projects.project_id
+                        LIMIT 1),
+    head_employee_id = 3
+WHERE project_id <= 10;
+
+

This schema has two cycles:

+
    +
  • employees (department_id) -> departments (project_id) -> projects (lead_employee_id) -> employees (employee_id)
    • +
  • employees (department_id) -> departments (project_id) -> projects (head_employee_id) -> employees (employee_id)
    • +
+

Greenmask can simply resolve it by generating a recursive query with integrity checks for subset and join conditions.

+

The example below will fetch the data for both 3 employees and related departments and projects.

+
Subset configuration example
transformation:
+  - schema: "public"
+    name: "employees"
+    subset_conds:
+      - "public.employees.employee_id in (1, 2, 3)"
+
+

But this will return empty result, because the subset condition is not met for all related tables because project with +project_id=1 has reference to employee with employee_id=3 that is invalid for subset condition.

+
Subset configuration example
transformation:
+  - schema: "public"
+    name: "employees"
+    subset_conds:
+      - "public.employees.employee_id in (1, 2)"
+
+

Example: Dump a subset with virtual references

+

In this example, we will create a subset of the tables with virtual references. The subset will include the +orders table and its related tables customers and audit_logs. The orders table has a virtual reference to the +customers table, and the audit_logs table has a virtual reference to the orders table.

+
Create tables with virtual references
-- Create customers table
+CREATE TABLE customers
+(
+    customer_id   SERIAL PRIMARY KEY,
+    customer_name VARCHAR(100)
+);
+
+-- Create orders table
+CREATE TABLE orders
+(
+    order_id    SERIAL PRIMARY KEY,
+    customer_id INT, -- This should reference customers.customer_id, but no FK constraint is defined
+    order_date  DATE
+);
+
+-- Create payments table
+CREATE TABLE payments
+(
+    payment_id     SERIAL PRIMARY KEY,
+    order_id       INT, -- This should reference orders.order_id, but no FK constraint is defined
+    payment_amount DECIMAL(10, 2),
+    payment_date   DATE
+);
+
+-- Insert test data into customers table
+INSERT INTO customers (customer_name)
+VALUES ('John Doe'),
+       ('Jane Smith'),
+       ('Alice Johnson');
+
+-- Insert test data into orders table
+INSERT INTO orders (customer_id, order_date)
+VALUES (1, '2023-08-01'), -- Related to customer John Doe
+       (2, '2023-08-05'), -- Related to customer Jane Smith
+       (3, '2023-08-07');
+-- Related to customer Alice Johnson
+
+-- Insert test data into payments table
+INSERT INTO payments (order_id, payment_amount, payment_date)
+VALUES (1, 100.00, '2023-08-02'), -- Related to order 1 (John Doe's order)
+       (2, 200.50, '2023-08-06'), -- Related to order 2 (Jane Smith's order)
+       (3, 300.75, '2023-08-08');
+-- Related to order 3 (Alice Johnson's order)
+
+
+-- Create a table with a multi-key reference (composite key reference)
+CREATE TABLE order_items
+(
+    order_id     INT,               -- Should logically reference orders.order_id
+    item_id      INT,               -- Composite part of the key
+    product_name VARCHAR(100),
+    quantity     INT,
+    PRIMARY KEY (order_id, item_id) -- Composite primary key
+);
+
+-- Create a table with a JSONB column that contains a reference value
+CREATE TABLE audit_logs
+(
+    log_id   SERIAL PRIMARY KEY,
+    log_data JSONB -- This JSONB field will contain references to other tables
+);
+
+-- Insert data into order_items table with multi-key reference
+INSERT INTO order_items (order_id, item_id, product_name, quantity)
+VALUES (1, 1, 'Product A', 3), -- Related to order_id = 1 from orders table
+       (1, 2, 'Product B', 5), -- Related to order_id = 1 from orders table
+       (2, 1, 'Product C', 2), -- Related to order_id = 2 from orders table
+       (3, 1, 'Product D', 1);
+-- Related to order_id = 3 from orders table
+
+-- Insert data into audit_logs table with JSONB reference value
+INSERT INTO audit_logs (log_data)
+VALUES ('{
+  "event": "order_created",
+  "order_id": 1,
+  "details": {
+    "customer_name": "John Doe",
+    "total": 100.00
+  }
+}'),
+       ('{
+         "event": "payment_received",
+         "order_id": 2,
+         "details": {
+           "payment_amount": 200.50,
+           "payment_date": "2023-08-06"
+         }
+       }'),
+       ('{
+         "event": "item_added",
+         "order_id": 1,
+         "item": {
+           "item_id": 2,
+           "product_name": "Product B",
+           "quantity": 5
+         }
+       }');
+
+

The following example demonstrates how to make a subset for keys that does not have FK constraints but a data +relationship exists.

+
    +
  • The orders table has a virtual reference to the customers table, and the audit_logs table + has a virtual reference to the orders table.
    • +
  • The payments table has a virtual reference to the orders table.
    • +
  • The order_items table has two keys that reference the orders and products tables.
    • +
  • The audit_logs table has a JSONB column that contains two references to the orders and order_items tables.
    • +
+
dump:
+  virtual_references:
+    - schema: "public"
+      name: "orders"
+      references:
+        - schema: "public"
+          name: "customers"
+          columns:
+            - name: "customer_id"
+          not_null: true
+
+    - schema: "public"
+      name: "payments"
+      references:
+        - schema: "public"
+          name: "orders"
+          columns:
+            - name: "order_id"
+          not_null: true
+
+    - schema: "public"
+      name: "order_items"
+      references:
+        - schema: "public"
+          name: "orders"
+          columns:
+            - name: "order_id"
+          not_null: true
+        - schema: "public"
+          name: "products"
+          columns:
+            - name: "product_id"
+          not_null: true
+
+    - schema: "public"
+      name: "audit_logs"
+      references:
+        - schema: "public"
+          name: "orders"
+          columns:
+            - expression: "(public.audit_logs.log_data ->> 'order_id')::INT"
+          not_null: false
+        - schema: "public"
+          name: "order_items"
+          columns:
+            - expression: "(public.audit_logs.log_data -> 'item' ->> 'item_id')::INT"
+            - expression: "(public.audit_logs.log_data ->> 'order_id')::INT"
+          not_null: false
+
+  transformation:
+
+    - schema: "public"
+      name: "customers"
+      subset_conds:
+        - "public.customers.customer_id in (1)"
+
+

As a result, the customers table will be dumped with the orders table and its related tables payments, +order_items, and audit_logs. The subset condition will be applied to the customers table, and the data will be +filtered based on the customer_id column.

+

Example: Dump a subset with polymorphic references

+

In this example, we will create a subset of the tables with polymorphic references. This example includes the +comments table and its related tables posts and videos.

+
Create tables with polymorphic references and insert data
-- Create the Posts table
+CREATE TABLE posts
+(
+    id      SERIAL PRIMARY KEY,
+    title   VARCHAR(255) NOT NULL,
+    content TEXT         NOT NULL
+);
+
+-- Create the Videos table
+CREATE TABLE videos
+(
+    id    SERIAL PRIMARY KEY,
+    title VARCHAR(255) NOT NULL,
+    url   VARCHAR(255) NOT NULL
+);
+
+-- Create the Comments table with a polymorphic reference
+CREATE TABLE comments
+(
+    id               SERIAL PRIMARY KEY,
+    commentable_id   INT         NOT NULL, -- Will refer to either posts.id or videos.id
+    commentable_type VARCHAR(50) NOT NULL, -- Will store the type of the associated record
+    body             TEXT        NOT NULL,
+    created_at       TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+);
+
+
+-- Insert data into the Posts table
+INSERT INTO posts (title, content)
+VALUES ('First Post', 'This is the content of the first post.'),
+       ('Second Post', 'This is the content of the second post.');
+
+-- Insert data into the Videos table
+INSERT INTO videos (title, url)
+VALUES ('First Video', 'https://example.com/video1'),
+       ('Second Video', 'https://example.com/video2');
+
+-- Insert data into the Comments table, associating some comments with posts and others with videos
+-- For posts:
+INSERT INTO comments (commentable_id, commentable_type, body)
+VALUES (1, 'post', 'This is a comment on the first post.'),
+       (2, 'post', 'This is a comment on the second post.');
+
+-- For videos:
+INSERT INTO comments (commentable_id, commentable_type, body)
+VALUES (1, 'video', 'This is a comment on the first video.'),
+       (2, 'video', 'This is a comment on the second video.');
+
+

The comments table has a polymorphic reference to the posts and videos tables. Depending on the value of the +commentable_type column, the commentable_id column will reference either the posts.id or videos.id column.

+

The following example demonstrates how to make a subset for tables with polymorphic references.

+
Subset configuration example
dump:
+  virtual_references:
+    - schema: "public"
+      name: "comments"
+      references:
+        - schema: "public"
+          name: "posts"
+          polymorphic_exprs:
+            - "public.comments.commentable_type = 'post'"
+          columns:
+            - name: "commentable_id"
+        - schema: "public"
+          name: "videos"
+          polymorphic_exprs:
+            - "public.comments.commentable_type = 'video'"
+          columns:
+            - name: "commentable_id"
+
+  transformation:
+    - schema: "public"
+      name: "posts"
+      subset_conds:
+        - "public.posts.id in (1)"
+
+

This example selects only the first post from the posts table and its related comments from the comments table. +The comments are associated with videos are included without filtering because the subset condition is applied only to +the posts table and related comments.

+

The resulted records will be:

+
transformed=# select * from comments;
+ id | commentable_id | commentable_type |                 body                  |         created_at         
+----+----------------+------------------+---------------------------------------+----------------------------
+  1 |              1 | post             | This is a comment on the first post.  | 2024-09-18 05:27:54.217405
+  2 |              2 | post             | This is a comment on the second post. | 2024-09-18 05:27:54.217405
+  3 |              1 | video            | This is a comment on the first video. | 2024-09-18 05:27:54.229794
+(3 rows)
+
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/index.html b/v0.2.5/index.html new file mode 100644 index 00000000..9a653be9 --- /dev/null +++ b/v0.2.5/index.html @@ -0,0 +1,3273 @@ + + + + + + + + + + + + + + + + + + + + + + + + + About - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

About Greenmask

+

Dump anonymization and synthetic data generation tool

+

Greenmask is a powerful open-source utility that is designed for logical database backup dumping, +anonymization, synthetic data generation and restoration. It has ported PostgreSQL libraries, making it reliable. +It is stateless and does not require any changes to your database schema. It is designed to be highly customizable and +backward-compatible with existing PostgreSQL utilities, fast and reliable.

+

Key features

+
    +
  • Deterministic transformers + — deterministic approach to data transformation based on the hash + functions. This ensures that the same input data will always produce the same output data. Almost each transformer + supports either random or hash engine making it universal for any use case.
    • +
  • Dynamic parameters — almost each + transformer supports dynamic parameters, allowing to parametrize the + transformer dynamically from the table column value. This is helpful for resolving the functional dependencies + between columns and satisfying the constraints.
    • +
  • Transformation validation and easy maintainable - During + configuration process, Greenmask provides validation + warnings, data transformation diff and schema diff features, allowing you to monitor and maintain transformations + effectively + throughout the software lifecycle. Schema diff helps to avoid data leakage when schema changed.
    • +
  • Partitioned tables transformation inheritance + — Define transformation configurations once and apply them to all + partitions within partitioned tables (using apply_for_inherited parameter), simplifying the anonymization process.
    • +
  • Stateless - Greenmask operates as a logical dump and does not impact your existing database schema.
    • +
  • Cross-platform - Can be easily built and executed on any platform, thanks to its Go-based architecture, + which eliminates platform dependencies.
    • +
  • Database type safe - Ensures data integrity by validating data and utilizing the database driver for + encoding and decoding operations. This approach guarantees the preservation of data formats.
    • +
  • Backward compatible - It fully supports the same features and protocols as existing vanilla PostgreSQL utilities. + Dumps created by Greenmask can be successfully restored using the pg_restore utility.
    • +
  • Extensible - Users have the flexibility + to implement domain-based transformations + in any programming language or + use predefined templates.
    • +
  • Integrable - Integrate seamlessly into your CI/CD system for automated database anonymization and + restoration.
    • +
  • Parallel execution - Take advantage of parallel dumping and restoration, significantly reducing the time required + to deliver results.
    • +
  • Provide variety of storages - offers a variety of storage options for local and remote data storage, + including directories and S3-like storage solutions.
    • +
  • Pgzip support for faster compression — by + setting --pgzip, it can speeds up the dump and restoration + processes through parallel compression.
    • +
+

Use cases

+

Greenmask is ideal for various scenarios, including:

+
    +
  • Backup and restoration. Use Greenmask for your daily routines involving logical backup dumping and restoration. It + seamlessly handles tasks like table restoration after truncation. Its functionality closely mirrors that of pg_dump + and pg_restore, making it a straightforward replacement.
    • +
  • Anonymization, transformation, and data masking. Employ Greenmask for anonymizing, transforming, and masking + backups, especially when setting up a staging environment or for analytical purposes. It simplifies the deployment of + a pre-production environment with consistently anonymized data, facilitating faster time-to-market in the development + lifecycle.
    • +
+ + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/installation/index.html b/v0.2.5/installation/index.html new file mode 100644 index 00000000..8b1cf2e7 --- /dev/null +++ b/v0.2.5/installation/index.html @@ -0,0 +1,3392 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Installation - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Installation

+

Prerequisites

+
    +
  • +

    Ensure that you have PostgreSQL utilities preinstalled, matching the major version + of your destination server.

    +
    • +
  • +

    If you are building Greenmask from source, make sure you have the make utility installed.

    +
    • +
+

Via docker

+

You can find the docker images in the:

+
    +
  1. Docker-hub page
    2. +
+

To run the greenmask container from DockerHub, use the following command: +

docker run -it greenmask/greenmask:latest
+

+
    +
  1. GitHub container registry
    2. +
+

To run the greenmask container from Github registry, use the following command: +

docker run -it ghcr.io/greenmaskio/greenmask:latest
+

+
+

Info

+

For pre-releases (rc, beta, etc.), use explicit tags like v0.2.0b2.

+
+

Via brew

+

The greenmask build is available in brew, +but only a production build is available. To install the greenmask via brew, use the following command:

+
brew install greenmask
+
+

From source

+
    +
  1. +

    Clone the Greenmask repository by using the following command:

    +
    git clone git@github.com:GreenmaskIO/greenmask.git
+
    +
    2. +
  2. +

    Once the repository is cloned, execute the following command to build Greenmask:

    +
    make build
+
    +
    3. +
+

After completing the build process, you will find the binary named greenmask in the root directory of the repository. +Execute the binary to start using Greenmask.

+

Playground

+

Greenmask Playground is a sandbox environment for your experiments in Docker with sample databases included to help you +try Greenmask without any additional actions. Read the Playground guide to learn more.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/overrides/main.html b/v0.2.5/overrides/main.html new file mode 100644 index 00000000..b8053afc --- /dev/null +++ b/v0.2.5/overrides/main.html @@ -0,0 +1,12 @@ +{% extends "base.html" %} + +{% block announce %} + A new version 0.2.5 (2024.11.16) is released +{% endblock %} + +{% block outdated %} + You're not viewing the latest version. + + Click here to go to latest. + +{% endblock %} \ No newline at end of file diff --git a/v0.2.5/playground/index.html b/v0.2.5/playground/index.html new file mode 100644 index 00000000..a7702d76 --- /dev/null +++ b/v0.2.5/playground/index.html @@ -0,0 +1,3368 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Playground - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask Playground

+

Greenmask Playground is a sandbox environment in Docker with sample databases included to help you try Greenmask without any additional actions. It includes the following components:

+
    +
  • Original database — the source database you'll be working with.
    • +
  • Empty database for restoration — an empty database where the restored data will be placed.
    • +
  • MinIO storage — used for storage purposes.
    • +
  • Greenmask Utility — Greenmask itself, ready for use.
    • +
+
+

Warning

+

To complete this guide, you must have Docker and docker-compose installed.

+
+

Setting up Greenmask Playground

+
    +
  1. +

    Clone the greenmask repository and navigate to its directory by running the following commands:

    +
    git clone git@github.com:GreenmaskIO/greenmask.git && cd greenmask
+
    +
    2. +
  2. +

    Once you have cloned the repository, start the environment by running Docker Compose:

    +
    docker-compose run greenmask
+
    +
    3. +
+
+

Tip

+

If you're experiencing problems with pulling images from Docker Hub, you can build the Greenmask image from source by running the following command:

+
docker-compose run greenmask-from-source
+
+
+

Now you have Greenmask Playground up and running with a shell prompt inside the container. All further operations will be carried out within this container's shell.

+

Commands

+

Below you can see Greenmask commands:

+
    +
  • +

    dump — performs a logical data dump, transforms the data, and stores it in the designated storage.

    +
    • +
  • +

    list-dumps — retrieves a list of all stored dumps within the chosen storage.

    +
    • +
  • +

    delete — removes a dump with a specific ID from the storage.

    +
    • +
  • +

    list-transformers — displays a list of approved transformers and their documentation.

    +
    • +
  • +

    restore — restores a dump either by specifying its ID or using the latest available dump to the target database.

    +
    • +
  • +

    show-dump — presents metadata information about a specific dump (equivalent to pg_restore -l ./).

    +
    • +
  • +

    validate — executes a validation process and generates a data diff for the transformation.

    +
    • +
  • +

    completion — generates the autocompletion script for the specified shell.

    +
    • +
+

To learn more about them, see Commands.

+

Transformers

+

A configuration file is mandatory for Greenmask functioning. The pre-defined configuration file is stored at the repository root directory (./playground/config.yml). It also serves to define transformers which you can update to your liking in order to use Greenmask Playground more effectively and to get better understanding of the tool itself. To learn how to customize a configuration file, see Configuration

+

The pre-defined configuration file uses the NoiseDate transformer as an example. To learn more about other transformers and how to use them, see Transformers.

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Greenmask 0.1.0

+

We are excited to announce the release of Greenmask v0.1.0, marking the first production-ready version. This release addresses various bug fixes, introduces improvements, and includes documentation refactoring for enhanced clarity.

+

New features

+
    +
  • +

    Added positional arguments for the list-transformers command, allowing specific transformer information retrieval (e.g., greenmask list-transformers RandomDate).

    +
    • +
  • +

    Added a version parameter --version that prints Greenmask version.

    +
    • +
  • +

    Added numeric parameters support for -Int and -Float transformers.

    +
    • +
+

Improvements

+
    +
  • +

    Improved verbosity in custom transformer interaction, accumulating stderr data and forwarding it in batches instead of writing it one by one.

    +
    • +
  • +

    Updated dependencies to newer versions.

    +
    • +
  • +

    Enhanced the stability of the JSON line interaction protocol by utilizing the stdlib JSON encoder/decoder.

    +
    • +
  • +

    Modified the method for sending table metadata to custom transformers; now, it is sent via stdin in the first line in JSON format instead of providing it via command arguments.

    +
    • +
  • +

    Refactored template functions naming.

    +
    • +
  • +

    Refactored NoiseDate transformer implementation for improved stability and predictability.

    +
    • +
  • +

    Changed the default value for the Dict transformer: fail_not_matched parameter: true.

    +
    • +
  • +

    Refactored the Hash transformer to provide a salt parameter and receive a base64 encoded salt. If salt is not provided, it generates one randomly.

    +
    • +
  • +

    Added validation for the truncate parameter of NoiseDate and RandomDate transformers that issues a warning if the provided value is invalid.

    +
    • +
  • +

    Increased verbosity of parameter validation warnings, now properly forwarding warnings to stdout.

    +
    • +
+

Fixes

+
    +
  • +

    Resolved pgx driver connection leakage issue.

    +
    • +
  • +

    Fixed deletion failure of dumps for S3 storage.

    +
    • +
  • +

    Corrected cobra autocompletion for the Greenmask utility.

    +
    • +
  • +

    Fixed NOT NULL constraint validation.

    +
    • +
  • +

    Addressed JSON API interaction issues that previously caused deadlocks and timeouts.

    +
    • +
  • +

    Fixed encode-decoding for binary parameters, ensuring accurate forwarding of values to custom transformers.

    +
    • +
  • +

    Fixed the RandomChoice transformer to correctly marshal and unmarshal values during validation.

    +
    • +
  • +

    Introduced the nullable property for the SetNull transformer to enhance NOT NULL constraint validation.

    +
    • +
  • +

    Resolved text wrapping issues for the validate command.

    +
    • +
  • +

    Fixed build failures on Windows due to Linux platform dependencies.

    +
    • +
  • +

    Corrected stdout readline buffer reading during interaction with custom transformers.

    +
    • +
  • +

    Fixed integration tests.

    +
    • +
+

Ecosystem changes

+
    +
  • +

    Implemented CI/CD pipelines for the entire project.

    +
    • +
  • +

    Established a user-friendly playground in Docker compose, including:

    +
    • +
  • +

    Deployed Minio storage container.

    +
    • +
  • PostgreSQL container containing both the original database (Adventure Works) and the transformed (empty DB).
    • +
  • +

    Greenmask container itself.

    +
    • +
  • +

    Refactored current readme files.

    +
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_0_beta/index.html b/v0.2.5/release_notes/greenmask_0_1_0_beta/index.html new file mode 100644 index 00000000..42458b69 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_0_beta/index.html @@ -0,0 +1,3299 @@ + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.0 Beta - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.0.1 Beta

+

We are excited to announce the beta release of Greenmask, a versatile and open-source utility for PostgreSQL logical backup dumping, anonymization, and restoration. Greenmask is perfect for routine backup and restoration tasks. It facilitates anonymization and data masking for staging environments and analytics.

+

This release introduces a range of features aimed at enhancing database management and security.

+

Key features

+
    +
  • Cross-platform support — fully written in Go without platform dependencies.
    • +
  • Type-safe database operations — validates and encodes data, maintaining integrity.
    • +
  • Transformation validation — ensures data transformations are correct and maintainable.
    • +
  • Partitioned table support — simplifies configuration for partitioned tables.
    • +
  • Stateless and backward compatible — works alongside standard PostgreSQL utilities.
    • +
  • Parallel execution — enhances efficiency in dumping and restoration processes.
    • +
  • Multiple storage options — supports both local (directory) and remote (S3-like) storage solutions.
    • +
+

Download

+

To download the Greenmask binary compatible with your system, see the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_1/index.html b/v0.2.5/release_notes/greenmask_0_1_1/index.html new file mode 100644 index 00000000..ae08f114 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_1/index.html @@ -0,0 +1,3442 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.1 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.1

+

This release introduces a suite of new transformers, significantly enhancing Greenmask's capabilities for obfuscating PostgreSQL databases.

+

New features

+

Added the following new transformers:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
TransformerDescription
RandomLatitudeGenerates a random latitude value
RandomLongitudeGenerates a random longitude value
RandomUnixTimeGenerates a random Unix timestamp
RandomMonthNameGenerates the name of a random month
RandomYearStringGenerates a random year as a string
RandomDayOfWeekGenerates a random day of the week
RandomDayOfMonthGenerates a random day of the month
RandomCenturyGenerates a random century
RandomTimezoneGenerates a random timezone
RandomEmailGenerates a random email address
RandomMacAddressGenerates a random MAC address
RandomDomainNameGenerates a random domain name
RandomURLGenerates a random URL
RandomUsernameGenerates a random username
RandomIPv4Generates a random IPv4 address
RandomIPv6Generates a random IPv6 address
RandomPasswordGenerates a random password
RandomWordGenerates a random word
RandomSentenceGenerates a random sentence
RandomParagraphGenerates a random paragraph
RandomCCTypeGenerates a random credit card type
RandomCCNumberGenerates a random credit card number
RandomCurrencyGenerates a random currency code
RandomAmountWithCurrencyGenerates a random monetary amount with currency
RandomTitleMaleGenerates a random title for males
RandomTitleFemaleGenerates a random title for females
RandomFirstNameGenerates a random first name
RandomFirstNameMaleGenerates a random male first name
RandomFirstNameFemaleGenerates a random female first name
RandomLastNameGenerates a random last name
RandomNameGenerates a full random name
RandomPhoneNumberGenerates a random phone number
RandomTollFreePhoneNumberGenerates a random toll-free phone number
RandomE164PhoneNumberGenerates a random phone number in E.164 format
RealAddressGenerates a real address
+

Assets

+

To download the Greenmask binary compatible with your system, see the release's assets list.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_10/index.html b/v0.2.5/release_notes/greenmask_0_1_10/index.html new file mode 100644 index 00000000..f3f5d618 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_10/index.html @@ -0,0 +1,3299 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.10 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.10

+

This release introduces improvements and bug fixes

+

Changes

+
    +
  • Fixed panic caused in RandomString transformer
    • +
  • Fixed wrong table size calculation. Now the table size includes TOAST table size
    • +
  • Added custom transformer interaction API defaults if not set
    • +
  • Changed docker workdir to greenmask home
    • +
  • Removed bucket name from object path prefix
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see +the release's assets list.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_11/index.html b/v0.2.5/release_notes/greenmask_0_1_11/index.html new file mode 100644 index 00000000..531c67f5 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_11/index.html @@ -0,0 +1,3298 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.11 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.11

+

This release introduces improvements and bug fixes

+

Changes

+
    +
  • Added support for generated columns in the table
    • +
  • Fixed transformer parameters encoding issue caused by spf13/viper
    • +
  • Fixed table scoring for transformed table
    • +
  • Refactored connection management logic in restore command - fixes connection idle timeout
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see +the release's assets list.

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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_12/index.html b/v0.2.5/release_notes/greenmask_0_1_12/index.html new file mode 100644 index 00000000..cae130b1 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_12/index.html @@ -0,0 +1,3297 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.12 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.12

+

This release introduces improvements and bug fixes

+

Changes

+
    +
  • Fixed config decoding issue caused
    • +
  • Fixed TOC entries merge behavior when data section is empty
    • +
  • Fixed integration tests for S3 storage
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see +the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.13

+

This release introduces only improvements in documentation deployment. The core greenmask utility does not contain any changes.

+

Changes

+
    +
  • Added documentation deployment with versioning
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see +the release's assets list.

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Greenmask 0.1.14

+

This release introduces bug fixes.

+

Changes

+
    +
  • Fixed large panic caused in Large Object dumper
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see +the release's assets list.

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Greenmask 0.1.2

+

This release introduces bug fixes.

+

Fixes

+
    +
  • Fixed bug when raw COPY lines were parsed incorrectly
    • +
  • Fixed --version parameter behavior
    • +
  • Fixed --dbname parameter - now it correctly works with PostgreSQL connection string in URI format postgresql:///
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.3

+

This release introduces bug fixes.

+

Fixes

+
    +
  • Fixed the JSON transformer's parsing for the operations fields
    • +
  • Fixed database connection string builder in pg_restore and pg_dump
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_4/index.html b/v0.2.5/release_notes/greenmask_0_1_4/index.html new file mode 100644 index 00000000..9013912c --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_4/index.html @@ -0,0 +1,3294 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.4 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.4

+

This release introduces bug fixes.

+

Fixes

+
    +
  • Fixed database connection string behavior fields
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_5/index.html b/v0.2.5/release_notes/greenmask_0_1_5/index.html new file mode 100644 index 00000000..682ca586 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_5/index.html @@ -0,0 +1,3342 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.5 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.5

+

This release introduces a new Greenmask command, improvements, bug fixes, and numerous documentation updates.

+

New features

+

Added a new Greenmask CLI command—show-transformer that shows detailed information about a specified transformer.

+

Improvements

+
    +
  • The Hash transformer has been completely remastered and now has the function parameter to choose from several hash algorithm options and the max_length parameter to truncate the hash tail.
    • +
  • Split information about transformers between the list-transformers and new show-transformer CLI commands, which allows for more comprehensible and useful outputs for both commands
    • +
  • Added error severity for the Cmd parameter validator
    • +
  • Improved UX for the Greenmask release binaries
    • +
+

Fixes

+
    +
  • Fixed metadata enrichment for validation warnings caused by RawValueValidator
    • +
  • Fixed a typo in the credit_card value for the type parameter of the Masking transformer
    • +
  • Fixed Greenmask Playground environment variables and the cleanup command
    • +
  • Fixed list-dump, list-transformers, and restore commands exit code on error
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_6/index.html b/v0.2.5/release_notes/greenmask_0_1_6/index.html new file mode 100644 index 00000000..e6146e53 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_6/index.html @@ -0,0 +1,3294 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.6 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.6

+

This is a minor release that introduces a bug hotfix

+

Fixes

+
    +
  • Fixed uncontrolled buffer growth in the restore command
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_7/index.html b/v0.2.5/release_notes/greenmask_0_1_7/index.html new file mode 100644 index 00000000..4811ab0b --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_7/index.html @@ -0,0 +1,3372 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.7 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.7

+

This release introduces a new Greenmask command, improvements, bug fixes, and documentation update.

+

New features

+
    +
  • Added restoration filtering by --table, --schema and --exclude-schema parameters
    • +
  • Validate parameters without parameters validates only configuration file
    • +
  • Added the --schema parameter, which allows to make a schema diff between the previous dump and the current. This + is useful when you want to check if the schema has changed after the migration. By controlling it we can exclude + data leakage after migration
    • +
  • Validate command divided by many stages that can be controlled using parameters
      +
    • Configuration validation
      • +
    • Transformer validation
      • +
    • Constraint violation check
      • +
    • Data difference check
      • +
    +
    • +
+

Improvements

+
    +
  • Improved Hash transformer
      +
    • Added salt parameter that can be set via config or via GREENMASK_GLOBAL_SALT
      • +
    • Added sha3 functions support in different modes (sha3-224, sha3-256, sha3-384, sha3-512)
      • +
    +
    • +
  • Refactored Cmd transformer logic
      +
    • Json API: Now it allows to use of column names instead of column indexes in JSON format
      • +
    • Csv API: Now it can use the column order from config via column remapping
      • +
    +
    • +
  • The validate command was rewritten almost from scratch.
      +
    • New option --transformed-only - displays only columns that are transformed with primary key (if exists). This + allows to reduce the output data and make it more readable
      • +
    • Implemented json format for output
      • +
    • Added the --table-format parameter which is responsible for the vertical and horizontal table orientation. + This works only when --format=text
      • +
    • Added the --warnings parameter, if it is specified then not only fatal-warnings will be displayed, but also + those with a lower severity
      • +
    +
    • +
+

Fixes

+
    +
  • Fixed --use-list option - now it applies toc entries according to the order in list file
    • +
  • Fixed --use-list option behaviour together with --list-format option (json or text). Now it + generates temporal list file in text format for providing it to the pg_restore call
    • +
  • Updated documentation according to the latest changes
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see +the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
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+ + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_1_8/index.html b/v0.2.5/release_notes/greenmask_0_1_8/index.html new file mode 100644 index 00000000..3874eeb7 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_1_8/index.html @@ -0,0 +1,3320 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.1.8 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.8

+

This release introduces improvements and bug fixes

+

Improvements

+
    +
  • Implemented --exit-on-error parameter for pg_restore run. But it does not play for "data" section restoration now. If any error is caused in data section greenmask exits with the error whether --exit-on-error was provided or not. This might be fixed later
    • +
+

Fixes

+
    +
  • Fixed dependent objects dropping when running with the restore command with the --clean parameter. Useful when restoring and overriding only required tables
    • +
  • Fixed show-dump command output in text mode
    • +
  • Disabled CGO. Fixes problem when downloaded binary from repo cannot run
    • +
  • Fixed delete dump operation
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see +the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.1.9

+

This release introduces improvements and bug fixes

+

Improvements

+
    +
  • Implemented tables scoring according to the table size and transformation costs. This correctly spread the tables + dumping between the requested workers pool and reduces the execution time. Now greenmask introspects the table size, + adds the transformation scoring using the formula + score = tableSizeInBytes + (tableSizeInBytes * 0.03 * tableTransformationsCount), and uses the strategy "Largest + First". The problem is described here
    • +
  • Introduced no_verify_ssl parameter for S3 storage
    • +
  • Adjusted Dockerfile
      +
    • Changed entrypoint to greenmask binary
      • +
    • The greenmask container now runs under greenmask user and groups
      • +
    +
    • +
  • Refactored storage config structure. Now it contains the type that is used for the storage type determination
    • +
  • Most of the attributes may be overridden with environment variables where the letters are capitalized and the dots + are replaced with underscores. For instance, the setting storage.type might be represented with the environment + variable STORAGE_TYPE
    • +
  • Parameter --config is not required anymore. This simplifies the greenmask utility user experience
    • +
  • Directory storage set as the default
    • +
  • Set the default temporary directory as /tmp
    • +
  • Added environment variable section to the configuration docs
    • +
+

Fixes

+
    +
  • Fixed S3_REGION environment variable usage. Tested cases where the S3 storage is set up using S3 variables that + uses by github.com/aws/aws-sdk-go
    • +
  • Updated project dependencies to the latest version
    • +
+

Assets

+

To download the Greenmask binary compatible with your system, see +the release's assets list.

+ + + + + + + + + + + + + + + + + + + + +
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+ + + +
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+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_2_0/index.html b/v0.2.5/release_notes/greenmask_0_2_0/index.html new file mode 100644 index 00000000..dbf34d00 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_2_0/index.html @@ -0,0 +1,3661 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.2.0 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.2.0

+

This is one of the biggest releases since Greenmask was founded. We've been in close contact with our users, gathering +feedback, and working hard to make Greenmask more flexible, reliable, and user-friendly.

+

This major release introduces exciting new features such as database subsetting, pgzip support, restoration in +topological order, and refactored transformers, significantly enhancing Greenmask's flexibility to better meet business +needs. It also includes several fixes and improvements.

+

Preface

+

This release is a major milestone that significantly expands Greenmask's functionality, transforming it into a simple, +extensible, and reliable solution for database security, data anonymization, and everyday operations. Our goal is to +create a core system that can serve as a foundation for comprehensive dynamic staging environments and robust data +security.

+

Notable changes

+
    +
  • +

    PostgreSQL 17 support - revised ported library to support PostgreSQL 17

    +
    • +
  • +

    Database Subset - a new feature that allows you to define a subset of the database, + allowing you to scale down the dump size (#110). This is + robust for multipurpose and especially useful for testing and development environments. It supports:

    +
      +
    • References with NULL values - generate the LEFT JOIN query + for the FK reference with NULL values to include them in the subset.
      • +
    • Supports virtual references (virtual foreign keys) - create a logical + FK in Greenmask that will be used for subset dependencies graph. The virtual reference can be defined for a column + or an expression, allowing you to get the value from JSON and similar.
      • +
    • Supports circular references - Greenmask will automatically resolve + circular dependencies in the subset by generating a recursive query. The query is generated with integrity checks + of the subset ensuring that the data gathered from circular dependencies is consistent.
      • +
    • Fully covered with documentation including troubleshooting + and examples.
      • +
    • Supports FK and PK that have more than one column (or expression).
      • +
    • Multi-cycles resolution in one strong connected component (SCC) is supported - Greenmask will generate a + recursive query for the SCC whether it is a single cycle or multiple cycles, making the subset system universal + for any database schema.
      • +
    • Supports polymorphic relationships - You can define +a virtual reference for a table with polymorphic references +using polymorphic_exprs attribute and use greenmask to generate a subset for such tables.
      • +
    +
    • +
  • +

    pgzip support for faster compression + and decompression — setting --pgzip can speed up the dump and + restoration processes through parallel compression. In some tests, it shows up to 5x faster dump and restore + operations.

    +
    • +
  • Restoration in topological order - This flag ensures + that dependent tables are not restored until the tables they depend on have been restored. This is useful when you + want to be notified of errors as immediately as possible without waiting for the entire table to be restored.
    • +
  • +

    Insert format restoration - For a flexible restoration + process, Greenmask now supports data restoration in the INSERT format. It generates the insert statements based on + COPY records from the dump. You do not need to re-dump your data to use this feature; it can be defined in the + restore command. The list of new features related to the INSERT format:

    +
      +
    • Generate INSERT statements with the **ON CONFLICT DO NOTHING** clause if the flag --on-conflict-do-nothing + is set.
      • +
    • Error exclusion list in the config to skip + certain errors and continue inserting subsequent rows from the dump.
      • +
    • Use cases - incremental dump and restoration for logical data. For example, if you have a database, and you + want to insert data periodically from another source, this can be used together with the database subset and + transformations to catch up the target database.
      • +
    +
    • +
  • +

    Restore data batching (#173) - + By default, the COPY protocol returns the error only on transaction commit. To override this behavior, use the + --batch-size flag to specify the number of rows to insert in a single batch during the COPY command. This is useful + when you want to control the transaction size and commit.

    +
    • +
  • +

    Introduced keep_null parameter for RandomPerson transformer.

    +
    • +
  • +

    Introduced dynamic parameters in the transformers

    +
      +
    • Most transformers now support dynamic parameters where applicable.
      • +
    • Dynamic parameters are strictly enforced. If you need to cast values to another type, Greenmask provides templates + and predefined cast functions accessible via cast_to. These functions cover frequent operations such as + UnixTimestampToDate and IntToBool.
      • +
    +
    • +
  • The transformation logic has been significantly refactored, making transformers more customizable and flexible than + before.
    • +
  • +

    Introduced transformation engines

    +
      +
    • random - generates transformer values based on pseudo-random algorithms.
      • +
    • hash - generates transformer values using hash functions. Currently, it utilizes sha3 hash functions, which + are secure but perform slowly. In the stable release, there will be an option to choose between sha3 and + SipHash.
      • +
    +
    • +
  • +

    Introduced static parameters value template

    +
    • +
  • +

    Dumps retention management - Introduced retention + parameters (#201) for the delete command. Introduced two new + statuses: failed and in progress. A dump is considered failed if it lacks a "done" heartbeat or + if the last heartbeat timestamp exceeds 30 minutes. The delete command now supports the following retention + parameters:

    +
      +
    • --dry-run: Runs the deletion operation in test mode with verbose output, without actually deleting anything.
      • +
    • --before-date 2024-08-27T23:50:54+00:00: Deletes dumps older than the specified date. The date must be provided + in RFC3339Nano format, for example: 2021-01-01T00:00:00Z.
      • +
    • --retain-recent 10: Retains the N most recent dumps, where N is specified by the user.
      • +
    • --retain-for 1w2d3h4m5s6ms7us8ns: Retains dumps for the specified duration. The format supports weeks (w), + days (d), hours (h), minutes (m), seconds (s), milliseconds (ms), microseconds (us), and nanoseconds (ns).
      • +
    • --prune-failed: Prunes (removes) all dumps that have failed.
      • +
    • --prune-unsafe: Prunes dumps with "unknown-or-failed" statuses. This option only works in conjunction with + --prune-failed.
      • +
    +
    • +
  • +

    Docker image mirroring into the GitHub Container Registry

    +
    • +
+

Core

+
    +
  • Introduced the Parametrizer interface, now implemented for both dynamic and static parameters.
    • +
  • Renamed most of the toolkit types for enhanced clarity and comprehensive documentation coverage.
    • +
  • Refactored the Driver initialization logic.
    • +
  • Added validation warnings for overridden types in the Driver.
    • +
  • Migrated existing built-in transformers to utilize the new Parametrizer interface.
    • +
  • Implemented a new abstraction, TransformationContext, as the first step towards enabling new feature transformation + conditions (#34).
    • +
  • Optimized most transformers for performance in both dynamic and static modes. While dynamic mode offers flexibility, + static mode ensures performance remains high. Using only the necessary transformation features helps keep + transformation time predictable.
    • +
+

Transformers

+
    +
  • +

    RandomEmail - Introduces a new transformer that + supports both random and deterministic engines. It allows for flexible email value generation; you can use column + values in the template and choose to keep the original domain or select any from the domains parameter.

    +
    • +
  • +

    NoiseDate, NoiseFloat, NoiseInt - + These transformers support both random and deterministic engines, offering dynamic mode parameters that control the + noise thresholds within the min and max range. Unlike previous implementations which used a single ratio + parameter, the new release features min_ratio and max_ratio parameters to define noise values more precisely. + Utilizing the hash engine in these transformers enhances security by complicating statistical analysis for + attackers, especially when the same salt is used consistently over long periods.

    +
    • +
  • +

    NoiseNumeric - A newly implemented transformer, + sharing features with NoiseInt and NoiseFloat, but specifically designed for numeric values (large integers or + floats). It provides a decimal parameter to handle values with fractions.

    +
    • +
  • +

    RandomChoice - Now supports the hash engine

    +
    • +
  • +

    RandomDate, RandomFloat, RandomInt - + Now enhanced with hash engine support. Threshold parameters min and max have been updated to support dynamic mode, + allowing for more flexible configurations.

    +
    • +
  • +

    RandomNumeric - A new transformer specifically + designed for numeric types (large integers or floats), sharing similar features with RandomInt and RandomFloat, + but tailored for handling huge numeric values.

    +
    • +
  • +

    RandomString - Now supports hash engine mode

    +
    • +
  • +

    RandomUnixTimestamp - This new transformer + generates Unix timestamps with selectable units (second, millisecond, microsecond, nanosecond). Similar in + function to RandomDate, it supports the hash engine and dynamic parameters for min and max thresholds, with the + ability to override these units using min_unit and max_unit parameters.

    +
    • +
  • +

    RandomUuid - Added hash engine support

    +
    • +
  • +

    RandomPerson - Implemented a new transformer that + replaces RandomName, RandomLastName, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, + RandomTitleMale, and RandomTitleFemale. This new transformer offers enhanced customizability while providing + similar functionalities as the previous versions. It generates personal data such as FirstName, LastName, and + Title, based on the provided gender parameter, which now supports dynamic mode. Future minor versions will allow + for overriding the default names database.

    +
    • +
  • +

    Added tsModify - a new + template function for time.Time objects modification

    +
    • +
  • +

    Introduced a new RandomIp transformer capable of + generating a random IP address based on the specified netmask.

    +
    • +
  • +

    Added a new RandomMac transformer for generating + random Mac addresses.

    +
    • +
  • +

    Deleted transformers include RandomMacAddress, RandomIPv4, RandomIPv6, RandomUnixTime, RandomTitleMale, + RandomTitleFemale, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, RandomLastName, and + RandomName due to the introduction of more flexible and unified options.

    +
    • +
+

Fixes and improvements

+
    +
  • Fixed validate command with the --table flag, which had the + wrong order of the table name representation {{ table_name }}.{{ schema }} instead of + {{ schema }}.{{ table_name }}.
    • +
  • Fixed + Row.SetColumn out of range validation.
    • +
  • Fixed + restoreWorker panic caused when the worker received an error from pgx.
    • +
  • Fixed error + handling in the restore command.
    • +
  • Fixed restore + jobs now start a transaction for each table restoration and commit it after the table restoration is done.
    • +
  • Fixed + --exit-on-error works incorrectly in the restore command. Now, the --exit-on-error flag works correctly with the + data section.
    • +
  • Fixed transaction rollback in the validate command.
    • +
  • Fixed typo in documentation.
    • +
  • Fixed a CI/CD bug related to retrieving current tags.
    • +
  • Fixed the Docker image tag for latest to exclude specific + keywords.
    • +
  • Fixed a case where the hashing value was not set for each column + in the RandomPerson transformer.
    • +
  • Fixed original email value parsing conditions.
    • +
  • Subset docs revision.
    • +
  • Fixes a case where data entries were excluded by exclusion + parameters such as --exclude-table, --table, etc.
    • +
  • Fixed zero bytes that were written in the buffer due to the wrong + buffer limit in the Email transformer.
    • +
  • Fixed a case where the overridden type of column via + columns_type_override did not work.
    • +
  • Fixed a case where an unknown option provided in the config was + just ignored instead of throwing an error.
    • +
  • Fixed a case where min and max parameter values were ignored + in transformers NoiseDate, NoiseNumeric, NoiseFloat, NoiseInt, RandomNumeric, RandomFloat, and + RandomInt.
    • +
  • Fixed TOC entry COPY restoration statement - added missing + newline and semicolon. Now backward pg_dump call pg_restore 1724504511561 --file 1724504511561.sql is backward + compatible and works as expected.
    • +
  • Fixed a case where dump/restore fails when masking tables with a + generated column.
    • +
  • Updated go version (v1.22) and dependencies
    • +
  • Revised installation section of doc
    • +
  • PostgreSQL 17 support - revised ported library to support PostgreSQL 17
    • +
  • Fixed integration tests - reset the go test cache on each iteration
    • +
  • Push docker images to ghcr.io registry
    • +
  • A bunch of refactoring and code cleanup to make the codebase more maintainable and readable.
    • +
+

Full Changelog: v0.1.14...v0.2.0

+ +

Feel free to reach out to us if you have any questions or need assistance:

+ + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_2_0_b1/index.html b/v0.2.5/release_notes/greenmask_0_2_0_b1/index.html new file mode 100644 index 00000000..0225e02d --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_2_0_b1/index.html @@ -0,0 +1,3549 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.2.0b1 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

Greenmask 0.2.0b1 (pre-release)

+

This major beta release introduces new features and refactored transformers, significantly enhancing Greenmask's +flexibility to better meet business needs.

+

Changes overview

+
    +
  • Introduced dynamic parameters in the transformers
      +
    • Most transformers now support dynamic parameters where applicable.
      • +
    • Dynamic parameters are strictly enforced. If you need to cast values to another type, Greenmask provides templates + and predefined cast functions accessible via cast_to. These functions cover frequent operations such as + UnixTimestampToDate and IntToBool.
      • +
    +
    • +
  • The transformation logic has been significantly refactored, making transformers more customizable and flexible than + before.
    • +
  • +

    Introduced transformation engines

    +
      +
    • random - generates transformer values based on pseudo-random algorithms.
      • +
    • hash - generates transformer values using hash functions. Currently, it utilizes sha3 hash functions, which + are secure but perform slowly. In the stable release, there will be an option to choose between sha3 and + SipHash.
      • +
    +
    • +
  • +

    Introduced static parameters value template

    +
    • +
+

Notable changes

+

Core

+
    +
  • Introduced the Parametrizer interface, now implemented for both dynamic and static parameters.
    • +
  • Renamed most of the toolkit types for enhanced clarity and comprehensive documentation coverage.
    • +
  • Refactored the Driver initialization logic.
    • +
  • Added validation warnings for overridden types in the Driver.
    • +
  • Migrated existing built-in transformers to utilize the new Parametrizer interface.
    • +
  • Implemented a new abstraction, TransformationContext, as the first step towards enabling new feature transformation + conditions (#34).
    • +
  • Optimized most transformers for performance in both dynamic and static modes. While dynamic mode offers flexibility, + static mode ensures performance remains high. Using only the necessary transformation features helps keep + transformation time predictable.
    • +
+

Documentation

+

Documentation has been significantly refactored. New information about features and updates to transformer descriptions +have been added.

+

Transformers

+
    +
  • +

    RandomEmail - Introduces a new transformer that + supports both random and deterministic engines. It allows for flexible email value generation; you can use column + values in the template and choose to keep the original domain or select any from the domains parameter.

    +
    • +
  • +

    NoiseDate, NoiseFloat, NoiseInt - + These transformers support both random and deterministic engines, offering dynamic mode parameters that control the + noise thresholds within the min and max range. Unlike previous implementations which used a single ratio + parameter, the new release features min_ratio and max_ratio parameters to define noise values more precisely. + Utilizing the hash engine in these transformers enhances security by complicating statistical analysis for + attackers, especially when the same salt is used consistently over long periods.

    +
    • +
  • +

    NoiseNumeric - A newly implemented transformer, + sharing features with NoiseInt and NoiseFloat, but specifically designed for numeric values (large integers or + floats). It provides a decimal parameter to handle values with fractions.

    +
    • +
  • +

    RandomChoice - Now supports the hash engine

    +
    • +
  • +

    RandomDate, RandomFloat, RandomInt - + Now enhanced with hash engine support. Threshold parameters min and max have been updated to support dynamic mode, + allowing for more flexible configurations.

    +
    • +
  • +

    RandomNumeric - A new transformer specifically + designed for numeric types (large integers or floats), sharing similar features with RandomInt and RandomFloat, + but tailored for handling huge numeric values.

    +
    • +
  • +

    RandomString - Now supports hash engine mode

    +
    • +
  • +

    RandomUnixTimestamp - This new transformer + generates Unix timestamps with selectable units (second, millisecond, microsecond, nanosecond). Similar in + function to RandomDate, it supports the hash engine and dynamic parameters for min and max thresholds, with the + ability to override these units using min_unit and max_unit parameters.

    +
    • +
  • +

    RandomUuid - Added hash engine support

    +
    • +
  • +

    RandomPerson - Implemented a new transformer that + replaces RandomName, RandomLastName, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, + RandomTitleMale, and RandomTitleFemale. This new transformer offers enhanced customizability while providing + similar functionalities as the previous versions. It generates personal data such as FirstName, LastName, and + Title, based on the provided gender parameter, which now supports dynamic mode. Future minor versions will allow + for overriding the default names database.

    +
    • +
  • +

    Added tsModify - a new + template function for time.Time objects modification

    +
    • +
  • +

    Introduced a new RandomIp transformer capable of + generating a random IP address based on the specified netmask.

    +
    • +
  • +

    Added a new RandomMac transformer for generating + random Mac addresses.

    +
    • +
  • +

    Deleted transformers include RandomMacAddress, RandomIPv4, RandomIPv6, RandomUnixTime, RandomTitleMale, + RandomTitleFemale, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, RandomLastName, and + RandomName due to the introduction of more flexible and unified options.

    +
    • +
+

Full Changelog: v0.1.14...v0.2.0b1

+

Playground usage for beta version

+

If you want to run a Greenmask playground for the beta version v0.2.0b1 execute:

+
git checkout tags/v0.2.0b1 -b v0.2.0b1
+docker-compose run greenmask-from-source
+
+ +

Feel free to reach out to us if you have any questions or need assistance:

+ + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_2_0_b2/index.html b/v0.2.5/release_notes/greenmask_0_2_0_b2/index.html new file mode 100644 index 00000000..70c368c3 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_2_0_b2/index.html @@ -0,0 +1,3506 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.2.0b2 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
+
+ + + + + + + +

Greenmask 0.2.0b2 (pre-release)

+

This major beta release introduces new features such as the database subset, pgzip support, restoration in +topological and many more. It also includes fixes and improvements.

+

Preface

+

This release is a major milestone that significantly expands Greenmask's functionality, transforming it into a simple, +extensible, and reliable solution for database security, data anonymization, and everyday operations. Our goal is to +create a core system that can serve as a foundation for comprehensive dynamic staging environments and robust data +security.

+

Notable changes

+
    +
  • +

    Database Subset - a new feature that allows you to define a subset of the database, + allowing you to scale down the dump size (#110). This is + robust for multipurpose and especially useful for testing and development environments. It supports:

    +
      +
    • References with NULL values - generate the LEFT JOIN query + for the FK reference with NULL values to include them in the subset.
      • +
    • Supports virtual references (virtual foreign keys) - create a logical + FK in Greenmask that will be used for subset dependencies graph. The virtual reference can be defined for a column + or an expression, allowing you to get the value from JSON and similar.
      • +
    • Supports circular references - Greenmask will automatically resolve + circular dependencies in the subset by generating a recursive query. The query is generated with integrity checks + of the subset ensuring that the data gathered from circular dependencies is consistent.
      • +
    • Fully covered with documentation including troubleshooting + and examples.
      • +
    • Supports FK and PK that have more than one column (or expression).
      • +
    • Multi-cycles resolution in one strong connected component (SCC) is supported - Greenmask will generate a + recursive query for the SCC whether it is a single cycle or multiple cycles, making the subset system universal + for any database schema.
      • +
    +
    • +
  • +

    pgzip support for faster compression + and decompression — setting --pgzip can speed up the dump and + restoration processes through parallel compression. In some tests, it shows up to 5x faster dump and restore + operations.

    +
    • +
  • Restoration in topological order - This flag ensures + that dependent tables are not restored until the tables they depend on have been restored. This is useful when you + want to be notified of errors as immediately as possible without waiting for the entire table to be restored.
    • +
  • +

    Insert format restoration - For a flexible restoration + process, Greenmask now supports data restoration in the INSERT format. It generates the insert statements based on + COPY records from the dump. You do not need to re-dump your data to use this feature; it can be defined in the + restore command. The list of new features related to the INSERT format:

    +
      +
    • Generate INSERT statements with the **ON CONFLICT DO NOTHING** clause if the flag --on-conflict-do-nothing + is set.
      • +
    • Error exclusion list in the config to skip + certain errors and continue inserting subsequent rows from the dump.
      • +
    • Use cases - incremental dump and restoration for logical data. For example, if you have a database, and you + want to insert data periodically from another source, this can be used together with the database subset and + transformations to catch up the target database.
      • +
    +
    • +
  • +

    Restore data batching (#173) - + By default, the COPY protocol returns the error only on transaction commit. To override this behavior, use the + --batch-size flag to specify the number of rows to insert in a single batch during the COPY command. This is useful + when you want to control the transaction size and commit.

    +
    • +
  • Introduced keep_null parameter for RandomPerson transformer.
    • +
+

Fixes and improvements

+
    +
  • Fixed validate command with the --table flag, which had the + wrong order of the table name representation {{ table_name }}.{{ schema }} instead of + {{ schema }}.{{ table_name }}.
    • +
  • Fixed + Row.SetColumn out of range validation.
    • +
  • Fixed + restoreWorker panic caused when the worker received an error from pgx.
    • +
  • Fixed error + handling in the restore command.
    • +
  • Fixed restore + jobs now start a transaction for each table restoration and commit it after the table restoration is done.
    • +
  • Fixed + --exit-on-error works incorrectly in the restore command. Now, the --exit-on-error flag works correctly with the + data section.
    • +
  • Fixed transaction rollback in the validate command.
    • +
  • Fixed typo in documentation.
    • +
  • Fixed a CI/CD bug related to retrieving current tags.
    • +
  • Fixed the Docker image tag for latest to exclude specific + keywords.
    • +
  • Fixed a case where the hashing value was not set for each column + in the RandomPerson transformer.
    • +
  • Fixed original email value parsing conditions.
    • +
  • Subset docs revision.
    • +
  • Fixes a case where data entries were excluded by exclusion + parameters such as --exclude-table, --table, etc.
    • +
  • Fixed zero bytes that were written in the buffer due to the wrong + buffer limit in the Email transformer.
    • +
  • Fixed a case where the overridden type of column via + columns_type_override did not work.
    • +
  • Fixed a case where an unknown option provided in the config was + just ignored instead of throwing an error.
    • +
  • Fixed a case where min and max parameter values were ignored + in transformers NoiseDate, NoiseNumeric, NoiseFloat, NoiseInt, RandomNumeric, RandomFloat, and + RandomInt.
    • +
  • Fixed TOC entry COPY restoration statement - added missing + newline and semicolon. Now backward pg_dump call pg_restore 1724504511561 --file 1724504511561.sql is backward + compatible and works as expected.
    • +
  • Fixed a case where dump/restore fails when masking tables with a + generated column.
    • +
  • Updated go version (v1.22) and dependencies
    • +
  • Revised installation section of doc
    • +
  • A bunch of refactoring and code cleanup to make the codebase more maintainable and readable.
    • +
+

Full Changelog: v0.2.0b1...v0.2.0b2

+

Playground usage for beta version

+

If you want to run a Greenmask playground for the beta version v0.2.0b2 execute:

+
git checkout tags/v0.2.0b2 -b v0.2.0b2
+docker-compose run greenmask-from-source
+
+ +

Feel free to reach out to us if you have any questions or need assistance:

+ + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_2_1/index.html b/v0.2.5/release_notes/greenmask_0_2_1/index.html new file mode 100644 index 00000000..29d4bf13 --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_2_1/index.html @@ -0,0 +1,3351 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.2.1 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

Greenmask 0.2.1

+

This release introduces two new features transformation conditions and transformation inheritance for primary and +foreign keys. It also includes several bug fixes and improvements.

+

Changes

+
    +
  • Feat: Transformation conditions + execute a defined transformation only if a specified condition is + met. #133
    • +
  • Feat: Transformation inheritance - transformation + inheritance for partitioned tables and tables with foreign keys. Define once and apply to all.
    • +
  • CI/CD: Add golangci-lint job to pull request check #223
    • +
  • CI/CD: Deploy development version of the documentation (main branch) and divided jobs into separate blocks and made them + reusable #212
    • +
  • Fix: Fixed type in subset documentation #211
    • +
  • Fix: Bump go and python dependencies #219
    • +
  • Fix: Fatal validation error in playground #224
    • +
  • Fix: Code refactoring and golangci-lint warns fixes #226
    • +
  • Docs: Revised README.md - added badges, updated the description, added getting started section, added greenmask design + schema #216 #217 #218
    • +
  • Docs: main page errors in docs #221
    • +
  • Docs: Revised README.md according to the latest changes #225
    • +
  • Docs: moved documentation to docs.greenmask.io, added feedback form and GA + integration #220
    • +
+

Full Changelog: v0.2.0...v0.2.1

+ +

Feel free to reach out to us if you have any questions or need assistance:

+ + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_2_2/index.html b/v0.2.5/release_notes/greenmask_0_2_2/index.html new file mode 100644 index 00000000..83b3bd0b --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_2_2/index.html @@ -0,0 +1,3335 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.2.2 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
+
+ + + + + + + +

Greenmask 0.2.2

+

This release introduces bug fixes.

+

Changes

+
    +
  • Fixed a case when apply_for_references applies validation to all transformations even if they are not + marked as apply_for_references #236.
    • +
  • Fixed issue with the latest tag disappearing in the documentation #234.
    • +
+

Full Changelog: v0.2.1...v0.2.2

+ +

Feel free to reach out to us if you have any questions or need assistance:

+ + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_2_3/index.html b/v0.2.5/release_notes/greenmask_0_2_3/index.html new file mode 100644 index 00000000..69a298ec --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_2_3/index.html @@ -0,0 +1,3344 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.2.3 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + +
+
+ + + + + + + +

Greenmask 0.2.3

+

This release introduces bug fixes.

+

Changes

+
    +
  • Fixed an issue where the partitioned table itself was executed in the restore worker, resulting in a "file not found" + error in storage. Closes bug: restoring partitioned tables + fails #238 #242.
    • +
  • Fixed template function availability #239. Renamed methods + according to the documentation: GetColumnRawValue is now GetRawColumnValue, and SetColumnRawValue is now + SetRawColumnValue #242
    • +
  • Resolved an issue where Dump.createTocEntries processed partitioned tables as if they were physical entities, despite + being logical #241
    • +
  • Corrected merging in the pre-data, data, and post-data sections, which previously caused a panic in dump command when + the post-data section was excluded #241
    • +
  • Fixed an issue where dumps created with --load-via-partition-root did not use the root partition table in --inserts + generation during restoration #241
    • +
+

Full Changelog: v0.2.2...v0.2.3

+ +

Feel free to reach out to us if you have any questions or need assistance:

+ + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_2_4/index.html b/v0.2.5/release_notes/greenmask_0_2_4/index.html new file mode 100644 index 00000000..2680943b --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_2_4/index.html @@ -0,0 +1,3334 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.2.4 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Greenmask 0.2.4

+

This release introduces bug fixes.

+

Changes

+
    +
  • Fixed a bug #244 that caused incorrect subset and transformer + inheritance behavior. See the merge request #245.
    • +
+

Full Changelog: v0.2.3...v0.2.4

+ +

Feel free to reach out to us if you have any questions or need assistance:

+ + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/release_notes/greenmask_0_2_5/index.html b/v0.2.5/release_notes/greenmask_0_2_5/index.html new file mode 100644 index 00000000..19e39bdb --- /dev/null +++ b/v0.2.5/release_notes/greenmask_0_2_5/index.html @@ -0,0 +1,3333 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Greenmask 0.2.5 - Greenmask — PostgreSQL database anonymization and synthetic data generation tool + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + +

Greenmask 0.2.5

+

This release introduces bug fixes.

+

Changes

+
    +
  • Fixed a bug where a subset query was not generated when provided #247.
    • +
+

Full Changelog: v0.2.4...v0.2.5

+ +

Feel free to reach out to us if you have any questions or need assistance:

+ + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + + + + \ No newline at end of file diff --git a/v0.2.5/search/search_index.json b/v0.2.5/search/search_index.json new file mode 100644 index 00000000..2ea3ab2a --- /dev/null +++ b/v0.2.5/search/search_index.json @@ -0,0 +1 @@ +{"config":{"lang":["en"],"separator":"[\\s\\-]+","pipeline":["stopWordFilter"]},"docs":[{"location":"","title":"About Greenmask","text":""},{"location":"#dump-anonymization-and-synthetic-data-generation-tool","title":"Dump anonymization and synthetic data generation tool","text":"

Greenmask is a powerful open-source utility that is designed for logical database backup dumping, anonymization, synthetic data generation and restoration. It has ported PostgreSQL libraries, making it reliable. It is stateless and does not require any changes to your database schema. It is designed to be highly customizable and backward-compatible with existing PostgreSQL utilities, fast and reliable.

"},{"location":"#key-features","title":"Key features","text":"
  • Deterministic transformers \u2014 deterministic approach to data transformation based on the hash functions. This ensures that the same input data will always produce the same output data. Almost each transformer supports either random or hash engine making it universal for any use case.
  • Dynamic parameters \u2014 almost each transformer supports dynamic parameters, allowing to parametrize the transformer dynamically from the table column value. This is helpful for resolving the functional dependencies between columns and satisfying the constraints.
  • Transformation validation and easy maintainable - During configuration process, Greenmask provides validation warnings, data transformation diff and schema diff features, allowing you to monitor and maintain transformations effectively throughout the software lifecycle. Schema diff helps to avoid data leakage when schema changed.
  • Partitioned tables transformation inheritance \u2014 Define transformation configurations once and apply them to all partitions within partitioned tables (using apply_for_inherited parameter), simplifying the anonymization process.
  • Stateless - Greenmask operates as a logical dump and does not impact your existing database schema.
  • Cross-platform - Can be easily built and executed on any platform, thanks to its Go-based architecture, which eliminates platform dependencies.
  • Database type safe - Ensures data integrity by validating data and utilizing the database driver for encoding and decoding operations. This approach guarantees the preservation of data formats.
  • Backward compatible - It fully supports the same features and protocols as existing vanilla PostgreSQL utilities. Dumps created by Greenmask can be successfully restored using the pg_restore utility.
  • Extensible - Users have the flexibility to implement domain-based transformations in any programming language or use predefined templates.
  • Integrable - Integrate seamlessly into your CI/CD system for automated database anonymization and restoration.
  • Parallel execution - Take advantage of parallel dumping and restoration, significantly reducing the time required to deliver results.
  • Provide variety of storages - offers a variety of storage options for local and remote data storage, including directories and S3-like storage solutions.
  • Pgzip support for faster compression \u2014 by setting --pgzip, it can speeds up the dump and restoration processes through parallel compression.
"},{"location":"#use-cases","title":"Use cases","text":"

Greenmask is ideal for various scenarios, including:

  • Backup and restoration. Use Greenmask for your daily routines involving logical backup dumping and restoration. It seamlessly handles tasks like table restoration after truncation. Its functionality closely mirrors that of pg_dump and pg_restore, making it a straightforward replacement.
  • Anonymization, transformation, and data masking. Employ Greenmask for anonymizing, transforming, and masking backups, especially when setting up a staging environment or for analytical purposes. It simplifies the deployment of a pre-production environment with consistently anonymized data, facilitating faster time-to-market in the development lifecycle.
"},{"location":"#links","title":"Links","text":"
  • Greenmask Roadmap
  • Email
  • Twitter
  • Telegram
  • Discord
  • DockerHub
"},{"location":"architecture/","title":"Architecture","text":""},{"location":"architecture/#introduction","title":"Introduction","text":"

It is evident that the most appropriate approach for executing logical backup dumping and restoration is by leveraging the core PostgreSQL utilities, specifically pg_dump and pg_restore. Greenmask has been purposefully designed to align with PostgreSQL's native utilities, ensuring compatibility. Greenmask primarily handles data dumping operations independently and delegates the responsibilities of schema dumping and restoration to pg_dump and pg_restore respectively, maintaining seamless integration with PostgreSQL's standard tools.

"},{"location":"architecture/#backup-process","title":"Backup process","text":"

The process of backing up PostgreSQL databases is divided into three distinct sections:

  • Pre-data \u2014 this section encompasses the raw schema of tables, excluding primary keys (PK) and foreign keys (FK).
  • Data \u2014 the data section contains the actual table data in COPY format, including information about sequence current values and Large Objects data.
  • Post-data \u2014 in this section, you'll find the definitions of indexes, triggers, rules, and constraints (such as PK and FK).

Greenmask focuses exclusively on the data section during runtime. It delegates the handling of the pre-data and post-data sections to the core PostgreSQL utilities, pg_dump and pg_restore.

Greenmask employs the directory format of pg_dump and pg_restore. This format is particularly suitable for parallel execution and partial restoration, and it includes clear metadata files that aid in determining the backup and restoration steps. Greenmask has been optimized to work seamlessly with remote storage systems and anonymization procedures.

When performing data dumping, Greenmask utilizes the COPY command in TEXT format, maintaining reliability and compatibility with the vanilla PostgreSQL utilities.

Additionally, Greenmask supports parallel execution, significantly reducing the time required for the dumping process.

"},{"location":"architecture/#storage-options","title":"Storage options","text":"

The core PostgreSQL utilities, pg_dump and pg_restore, traditionally operate with files in a directory format, offering no alternative methods. To meet modern backup requirements and provide flexible approaches, Greenmask introduces the concept of storages.

  • s3 \u2014 this option supports any S3-like storage system, including AWS S3, which makes it versatile and adaptable to various cloud-based storage solutions.
  • directory \u2014 this is the standard choice, representing the ordinary filesystem directory for local storage.
"},{"location":"architecture/#restoration-process","title":"Restoration process","text":"

In the restoration process, Greenmask combines the capabilities of different tools:

  • For schema restoration Greenmask utilizes pg_restore to restore the database schema. This ensures that the schema is accurately reconstructed.
  • For data restoration Greenmask independently applies the data using the COPY protocol. This allows Greenmask to handle the data efficiently, especially when working with various storage solutions. Greenmask is aware of the restoration metadata, which enables it to download only the necessary data. This feature is particularly useful for partial restoration scenarios, such as restoring a single table from a complete backup.

Greenmask also supports parallel restoration, which can significantly reduce the time required to complete the restoration process. This parallel execution enhances the efficiency of restoring large datasets.

"},{"location":"architecture/#data-anonymization-and-validation","title":"Data anonymization and validation","text":"

Greenmask works with COPY lines, collects schema metadata using the Golang driver, and employs this driver in the encoding and decoding process. The validate command offers a way to assess the impact on both schema (validation warnings) and data (transformation and displaying differences). This command allows you to validate the schema and data transformations, ensuring the desired outcomes during the anonymization process.

"},{"location":"architecture/#customization","title":"Customization","text":"

If your table schema relies on functional dependencies between columns, you can address this challenge using the TemplateRecord transformer. This transformer enables you to define transformation logic for entire tables, offering type-safe operations when assigning new values.

Greenmask provides a framework for creating your custom transformers, which can be reused efficiently. These transformers can be seamlessly integrated without requiring recompilation, thanks to the PIPE (stdin/stdout) interaction.

Note

Furthermore, Greenmask's architecture is designed to be highly extensible, making it possible to introduce other interaction protocols, such as HTTP or Socket, for conducting anonymization procedures.

"},{"location":"architecture/#postgresql-version-compatibility","title":"PostgreSQL version compatibility","text":"

Greenmask is compatible with PostgreSQL versions 11 and higher.

"},{"location":"configuration/","title":"Configuration","text":"
# Configuration\n

The configuration is organized into six sections:

  • common \u2014 settings that can be used for both the dump and restore commands
  • log \u2014 settings for the logging subsystem
  • storage \u2014 settings for the storage locations where dumps are stored
  • dump \u2014 settings for the dump command. This section includes pg_dump options and transformation parameters.
  • restore \u2014 settings for the restore command. It contains pg_restore options and additional restoration scripts.
  • custom_transformers \u2014 definitions of the custom transformers that interact through stdin and stdout. Once a custom transformer is configured, it becomes accessible via the greenmask list-transformers command.
"},{"location":"configuration/#common-section","title":"common section","text":"

In the common section of the configuration, you can specify the following settings:

  • pg_bin_path \u2014 path to the PostgreSQL binaries. Note that the PostgreSQL server version must match the provided binaries.
  • tmp_dir \u2014 temporary directory for storing the table of contents files. Default value is /tmp

Note

Greenmask exclusively manages data dumping and data restoration processes, delegating schema dumping to the pg_dumputility and schema restoration to the pg_restore utility. Both pg_dump and pg_restore rely on a toc.dat file located in a specific directory, which contains metadata and object definitions. Therefore, the tmp_dir parameter is essential for storing the toc.dat file during the dumping or restoration procedure. It is important to note that all artifacts in this directory will be automatically deleted once the Greenmask command is completed.

"},{"location":"configuration/#log-section","title":"log section","text":"

In the log section of the configuration, you can specify the following settings:

  • level \u2014 specifies the level of logging, which can be one of the following: debug, info, or error. The default level is info.
  • format \u2014 defines the logging format, which can be either json or text. The default format is text.
"},{"location":"configuration/#storage-section","title":"storage section","text":"

In the storage section, you can configure the storage driver for storing the dumped data. Currently, two storage type options are supported: directory and s3.

directory options3 option

The directory storage option refers to a filesystem directory where the dump data will be stored.

Parameters include path which specifies the path to the directory in the filesystem where the dumps will be stored.

directory storage config example
storage:\n  type: \"directory\"\n  directory:\n    path: \"/home/user_name/storage_dir\" # (1)\n

By choosing the s3 storage option, you can store dump data in an S3-like remote storage service, such as Amazon S3 or Azure Blob Storage. Here are the parameters you can configure for S3 storage:

  • endpoint \u2014 overrides the default AWS endpoint to a custom one for making requests
  • bucket \u2014 the name of the bucket where the dump data will be stored
  • prefix \u2014 a prefix for objects in the bucket, specified in path format
  • region \u2014 the S3 service region
  • storage_class \u2014 the storage class for performing object requests
  • no_verify_ssl \u2014 disable SSL certificate verification
  • access_key_id \u2014 access key for authentication
  • secret_access_key \u2014 secret access key for authentication
  • session_token \u2014 session token for authentication
  • role_arn \u2014 Amazon resource name for role-based authentication
  • session_name \u2014 role session name to uniquely identify a session
  • max_retries \u2014 the number of retries on request failures
  • cert_file \u2014 the path to the SSL certificate for making requests
  • max_part_size \u2014 the maximum part length for one request
  • concurrency \u2014 the number of goroutines to use in parallel for each upload call when sending parts
  • use_list_objects_v1 \u2014 use the old v1 ListObjects request instead of v2 one
  • force_path_style \u2014 force the request to use path-style addressing (e. g., http://s3.amazonaws.com/BUCKET/KEY) instead of virtual hosted bucket addressing (e. g., http://BUCKET.s3.amazonaws.com/KEY)
  • use_accelerate \u2014 enable S3 Accelerate feature
s3 storage config example for Minio running in Docker
storage:  \n  type: \"s3\"\n  s3:\n    endpoint: \"http://localhost:9000\"\n    bucket: \"testbucket\"\n    region: \"us-east-1\"\n    access_key_id: \"Q3AM3UQ867SPQQA43P2F\"\n    secret_access_key: \"zuf+tfteSlswRu7BJ86wekitnifILbZam1KYY3TG\"\n
"},{"location":"configuration/#dump-section","title":"dump section","text":"

In the dump section of the configuration, you configure the greenmask dump command. It includes the following parameters:

  • pg_dump_options \u2014 a map of pg_dump options to configure the behavior of the command itself. You can refer to the list of supported pg_dump options in the Greenmask dump command documentation.

  • transformation \u2014 this section contains configuration for applying transformations to table columns during the dump operation. It includes the following sub-parameters:

    • schema \u2014 the schema name of the table
    • name \u2014 the name of the table
    • subset_conds - list of the conditions to filter the rows to be dumped. The conditions are combined with AND operator. For details read Database subset

    • query \u2014 an optional parameter for specifying a custom query to be used in the COPY command. By default, the entire table is dumped, but you can use this parameter to set a custom query.

      Warning

      Be cautious when using the query parameter, as it may lead to constraint violation errors during restoration, and Greenmask currently cannot handle query validation.

    • columns_type_override \u2014 allows you to override the column types explicitly. You can associate a column with another type that is supported by your transformer. This is useful when the transformer works strictly with specific types of columns. For example, if a column named post_code is of the TEXT type, but the RandomInt transformer works only with INT family types, you can override it as shown in the example provided. column type overridden example

        columns_type_override:\n    post_code: \"int4\"  # (1)\n

      1. Change the data type of the post_code column to INT4 (INTEGER)

    • apply_for_inherited \u2014 an optional parameter to apply the same transformation to all partitions if the table is partitioned. This can save you from defining the transformation for each partition manually.

      Warning

      It is recommended to use the --load-via-partition-root parameter when dealing with partitioned tables, as the partition key value might change.

    • transformers \u2014 a list of transformers to apply to the table, along with their parameters. Each transformation item includes the following sub-parameters:

      • name \u2014 the name of the transformer
      • params \u2014 a map of the provided transformer parameters
      transformers config example
         transformers:\n    - name: \"RandomDate\"\n      params:\n        min: \"2023-01-01 00:00:00.0+03\"\n        max: \"2023-01-02 00:00:00.0+03\"\n        column: \"scheduled_departure\"\n\n    - name: \"NoiseDate\"\n      params:\n        ratio: \"01:00:00\"\n        column: \"scheduled_arrival\"\n

Here is an example configuration for the dump section:

dump section config example

dump:\n  pg_dump_options:\n    dbname: \"host=/run/postgresql user=postgres dbname=demo\"\n    jobs: 10\n    exclude-schema: \"(\\\"teSt\\\"*|test*)\"\n    table: \"bookings.flights\"\n    load-via-partition-root: true\n\n  transformation:\n    - schema: \"bookings\"\n      name: \"flights\"\n      query: \"select * from bookings.flights3 limit 1000000\"\n      columns_type_override:\n        post_code: \"int4\" # (1)\n      transformers:\n        - name: \"RandomDate\"\n          params:\n            min: \"2023-01-01 00:00:00.0+03\"\n            max: \"2023-01-02 00:00:00.0+03\"\n            column: \"scheduled_departure\"\n\n        - name: \"NoiseDate\"\n          params:\n            ratio: \"01:00:00\"\n            column: \"scheduled_arrival\"\n\n        - name: \"RegexpReplace\"\n          params:\n            column: \"status\"\n            regexp: \"On Time\"\n            replace: \"Delayed\"\n\n        - name: \"RandomInt\" # (2)\n          params:\n            column: \"post_code\"\n            min: \"11\"\n            max: \"99\"\n\n    - schema: \"bookings\"\n      name: \"aircrafts_data\"\n      subset_conds: # (3)\n        - \"bookings.aircrafts_data.model = 'Boeing 777-300-2023'\"\n      transformers:\n        - name: \"Json\"\n          params:\n            column: \"model\"\n            operations:\n              - operation: \"set\"\n                path: \"en\"\n                value: \"Boeing 777-300-2023\"\n              - operation: \"set\"\n                path: \"crewSize\"\n                value: 10\n\n        - name: \"NoiseInt\"\n          params:\n            ratio: 0.9\n            column: \"range\"\n

  1. Override the post_code column type to int4 (INTEGER). This is necessary because the post_code column originally has a TEXT type, but it contains values that resemble integers. By explicitly overriding the type to int4, we ensure compatibility with transformers that work with integer types, such as RandomInt.
  2. After the type is overridden, we can apply a compatible transformer.
  3. Database subset condition applied to the aircrafts_data table. The subset condition filters the data based on the model column.
"},{"location":"configuration/#validate-section","title":"validate section","text":"

In the validate section of the configuration, you can specify parameters for the greenmask validate command. Here is an example of the validate section configuration:

validate section config example

validate:\n  tables: # (1)\n    - \"orders\"\n    - \"public.cart\"\n  data: true # (2)\n  diff: true # (3)\n  rows_limit: 10 # (4)\n  resolved_warnings: # (5)\n    - \"8d436fae67b2b82b36bd3afeb0c93f30\"\n  table_format: \"horizontal\" # (7)\n  format: \"text\" # (6)\n  schema: true # (8)\n  transformed_only: true # (9)\n  warnings: true # (10)\n

  1. A list of tables to validate. If this list is not empty, the validation operation will only be performed for the specified tables. Tables can be written with or without the schema name (e. g., \"public.cart\" or \"orders\").
  2. Specifies whether to perform data transformation for a limited set of rows. If set to true, data transformation will be performed, and the number of rows transformed will be limited to the value specified in the rows_limit parameter (default is 10).
  3. Specifies whether to perform diff operations for the transformed data. If set to true, the validation process will find the differences between the original and transformed data. See more details in the validate command documentation.
  4. Limits the number of rows to be transformed during validation. The default limit is 10 rows, but you can change it by modifying this parameter.
  5. A hash list of resolved warnings. These warnings have been addressed and resolved in a previous validation run.
  6. Specifies the format of the transformation output. Possible values are [horizontal|vertical]. The default format is horizontal. You can choose the format that suits your needs. See more details in the validate command documentation.
  7. The output format (json or text)
  8. Specifies whether to validate the schema current schema with the previous and print the differences if any.
  9. If set to true, transformation output will be only with the transformed columns and primary keys
  10. If set to then all the warnings be printed
"},{"location":"configuration/#restore-section","title":"restore section","text":"

In the restore section of the configuration, you can specify parameters for the greenmask restore command. It contains pg_restore settings and custom script execution settings. Below you can find the available parameters:

  • pg_restore_options \u2014 a map of pg_restore options that are used to configure the behavior of the pg_restore utility during the restoration process. You can refer to the list of supported pg_restore options in the Greenmask restore command documentation.
  • scripts \u2014 a map of custom scripts to be executed during different restoration stages. Each script is associated with a specific restoration stage and includes the following attributes:
    • [pre-data|data|post-data] \u2014 the name of the restoration stage when the script should be executed; has the following parameters:
      • name \u2014 the name of the script
      • when \u2014 specifies when to execute the script, which can be either \"before\" or \"after\" the specified restoration stage
      • query \u2014 an SQL query string to be executed
      • query_file \u2014 the path to an SQL query file to be executed
      • command \u2014 a command with parameters to be executed. It is provided as a list, where the first item is the command name.
  • insert_error_exclusions \u2014 a list of error codes that should be ignored during the restoration process. This is useful when you want to skip specific errors that are not critical for the restoration process.

As mentioned in the architecture, a backup contains three sections: pre-data, data, and post-data. The custom script execution allows you to customize and control the restoration process by executing scripts or commands at specific stages. The available restoration stages and their corresponding execution conditions are as follows:

  • pre-data \u2014 scripts or commands can be executed before or after restoring the pre-data section
  • data \u2014 scripts or commands can be executed before or after restoring the data section
  • post-data \u2014 scripts or commands can be executed before or after restoring the post-data section

Each stage can have a \"when\" condition with one of the following possible values:

  • before \u2014 execute the script or SQL command before the mentioned restoration stage
  • after \u2014 execute the script or SQL command after the mentioned restoration stage

Below you can find one of the possible versions for the scripts part of the restore section:

scripts definition example

scripts:\n  pre-data: # (1)\n    - name: \"pre-data before script [1] with query\"\n      when: \"before\"\n      query: \"create table script_test(stage text)\"\n    - name: \"pre-data before script [2]\"\n      when: \"before\"\n      query: \"insert into script_test values('pre-data before')\"\n    - name: \"pre-data after test script [1]\"\n      when: \"after\"\n      query: \"insert into script_test values('pre-data after')\"\n    - name: \"pre-data after script with query_file [1]\"\n      when: \"after\"\n      query_file: \"pre-data-after.sql\"\n  data: # (2)\n    - name: \"data before script with command [1]\"\n      when: \"before\"\n      command: # (4)\n        - \"data-after.sh\"\n        - \"param1\"\n        - \"param2\"\n    - name: \"data after script [1]\"\n      when: \"after\"\n      query_file: \"data-after.sql\"\n  post-data: # (3)\n    - name: \"post-data before script [1]\"\n      when: \"before\"\n      query: \"insert into script_test values('post-data before')\"\n    - name: \"post-data after script with query_file [1]\"\n      when: \"after\"\n      query_file: \"post-data-after.sql\"\n

  1. List of pre-data stage scripts. This section contains scripts that are executed before or after the restoration of the pre-data section. The scripts include SQL queries and query files.
  2. List of data stage scripts. This section contains scripts that are executed before or after the restoration of the data section. The scripts include shell commands with parameters and SQL query files.
  3. List of post-data stage scripts. This section contains scripts that are executed before or after the restoration of the post-data section. The scripts include SQL queries and query files.
  4. Command in the first argument and the parameters in the rest of the list. When specifying a command to be executed in the scripts section, you provide the command name as the first item in a list, followed by any parameters or arguments for that command. The command and its parameters are provided as a list within the script configuration.
"},{"location":"configuration/#restoration-error-exclusion","title":"restoration error exclusion","text":"

You can configure which errors to ignore during the restoration process by setting the insert_error_exclusions parameter. This parameter can be applied globally or per table. If both global and table-specific settings are defined, the table-specific settings will take precedence. Below is an example of how to configure the insert_error_exclusions parameter. You can specify constraint names from your database schema or the error codes returned by PostgreSQL. codes in the PostgreSQL documentation.

parameter defintion
insert_error_exclusions:\n\n  global:\n    error_codes: [\"23505\"] # (1)\n    constraints: [\"PK_ProductReview_ProductReviewID\"] # (2)\n  tables: # (3)\n    - schema: \"production\"\n      name: \"productreview\"\n      constraints: [\"PK_ProductReview_ProductReviewID\"]\n      error_codes: [\"23505\"]\n
  1. List of strings that contains postgresql error codes
  2. List of strings that contains constraint names (globally)
  3. List of tables with their schema, name, constraints, and error codes

Here is an example configuration for the restore section:

restore:\n  scripts:\n      pre-data: # (1)\n        - name: \"pre-data before script [1] with query\"\n          when: \"before\"\n          query: \"create table script_test(stage text)\"\n\n  insert_error_exclusions:\n    tables:\n      - schema: \"production\"\n        name: \"productreview\"\n        constraints:\n          - \"PK_ProductReview_ProductReviewID\"\n        error_codes:\n          - \"23505\"\n    global:\n      error_codes:\n        - \"23505\"\n\n  pg_restore_options:\n    jobs: 10\n    exit-on-error: false\n    dbname: \"postgresql://postgres:example@localhost:54316/transformed\"\n    table: \n      - \"productreview\"\n    pgzip: true\n    inserts: true\n    on-conflict-do-nothing: true\n    restore-in-order: true\n
"},{"location":"configuration/#environment-variable-configuration","title":"Environment variable configuration","text":"

It's also possible to configure Greenmask through environment variables.

Greenmask will automatically parse any environment variable that matches the configuration in the config file by substituting the dot (.) separator for an underscore (_) and uppercasing it. As an example, the config file below would apply the same configuration as defining the LOG_LEVEL=debug environment variable

config.yaml
log:\n  level: debug\n
"},{"location":"configuration/#global-configuration-variables","title":"Global configuration variables","text":"
  • GREENMASK_GLOBAL_SALT - global salt value hex encoded with variadic length, used for the hash engine. For details read Transformation engines section.
"},{"location":"configuration/#postgres-connection-variables","title":"Postgres connection variables","text":"

Additionaly, there are some environment variables exposed by the dump and restore commands to facilitate the connection configuration with a Postgres database

  • PGHOST - host used to connect to the postgres database
  • PGPORT - port where postgres is exposed
  • PGDATABASE - name of the database to dump/restore
  • PGUSER - username used to connect to the postgres database
  • PGPASSWORD - password used to authenticate to the postgres database
"},{"location":"database_subset/","title":"Database subset","text":"

Greenmask allows you to define a subset condition for filtering data during the dump process. This feature is useful when you need to dump only a part of the database, such as a specific table or a set of tables. It automatically ensures data consistency by including all related data from other tables that are required to maintain the integrity of the subset. The subset condition can be defined using subset_conds attribute that can be defined on the table in the transformation section (see examples).

Info

Greenmask genrates queries for subset conditions based on the introspected schema using joins and recursive queries. It cannot be responsible for query optimization. The subset quries might be slow due to the complexity of the queries and/or lack of indexes. Circular are resolved using recursive queries.

"},{"location":"database_subset/#detail","title":"Detail","text":"

The subset is a list of SQL conditions that are applied to table. The conditions are combined with AND operator. You need to specify the schema, table and column name when pointing out the column to filter by to avoid ambiguity. The subset condition must be a valid SQL condition.

Subset condition example
subset_conds:\n  - 'person.businessentity.businessentityid IN (274, 290, 721, 852)'\n
"},{"location":"database_subset/#use-cases","title":"Use cases","text":"
  • Database scale down - create anonymized dump but for the limited and consistent set of tables
  • Data migration - migrate only some records from one database to another
  • Data anonymization - dump and anonymize only a specific records in the database
  • Database catchup - catchup your another instance of database logically by adding a new records. In this case it is recommended to restore tables in topological order using --restore-in-order.
"},{"location":"database_subset/#references-with-null-values","title":"References with NULL values","text":"

For references that do not have NOT NULL constraints, Greenmask will automatically generate LEFT JOIN queries with the appropriate conditions to ensure integrity checks. You can rely on Greenmask to handle such cases correctly\u2014no special configuration is needed, as it performs this automatically based on the introspected schema.

"},{"location":"database_subset/#circular-reference","title":"Circular reference","text":"

Greenmask supports circular references between tables. You can define a subset condition for any table, and Greenmask will automatically generate the appropriate queries for the table subset using recursive queries. The subset system ensures data consistency by validating all records found through the recursive queries. If a record does not meet the subset condition, it will be excluded along with its parent records, preventing constraint violations.

Warning

Currently (v0.2b2), Greenmask can resolve multi-cylces in one strogly connected component, but only for one group of vertexes. If you have SSC that contains 2 groups of vertexes, Greenmask will not be able to resolve it. For instance we have 2 cycles with tables A, B, C (first group) and B, C, E (second group). Greenmask will not be able to resolve it. But if you have only one group of vertexes one and more cycles in the same group of tables (for instance A, B, C), Greenmask works with it. This will be fixed in the future. See second example below. In practice this is quite rare situation and 99% of people will not face this issue.

You can read the Wikipedia article about Circular reference here.

"},{"location":"database_subset/#virtual-references","title":"Virtual references","text":"

During the development process, there are situations where foreign keys need to be removed. The reasons can vary\u2014from improving performance to simplifying the database structure. Additionally, some foreign keys may exist within loosely structured data, such as JSON, where PostgreSQL cannot create foreign keys at all. These limitations could significantly hinder the capabilities of a subset system. Greenmask offers a flexible solution to this problem by allowing the declaration of virtual references in the configuration, enabling the preservation and management of logical relationships between tables, even in the absence of explicit foreign keys. Virtual reference can be called virtual foreign key as well.

The virtual_references can be defined in dump section. It contains the list of virtual references. First you set the table where you want to define virtual reference. In the attribute references define the list of tables that are referenced by the table. In the columns attribute define the list of columns that are used in the foreign key reference. The not_null attribute is optional and defines if the FK has not null constraint. If true Greenmask will generate INNER JOIN instead of LEFT JOIN by default it is false. The expression needs to be used when you want to use some expression to get the value of the column in the referencing table. For instance, if you have JSONB column in the audit_logs table that contains order_id field, you can use this field as FK reference.

Info

You do not need to define primry key of the referenced table. Greenmask will automatically resolve it and use it in the join condition.

Virtual references example
dump:\n  virtual_references:\n    - schema: \"public\" # (1)\n      name: \"orders\" # (2)\n      references: # (3)\n        - schema: \"public\" # (4) \n          name: \"customers\" # (5)\n          columns: # (6)\n            - name: \"customer_id\"\n          not_null: false # (7)\n\n    - schema: \"public\"\n      name: \"audit_logs\"\n      references:\n        - schema: \"public\"\n          name: \"orders\"\n          columns:\n            - expression: \"(public.audit_logs.log_data ->> 'order_id')::INT\" # (8)\n
  1. The schema name of table that has foreign key reference (table that own FK reference)
  2. The table name that has foreign key reference (table that own FK reference)
  3. List of virtual references
  4. The schema name of the table that has foreign key reference (referencing table)
  5. The table name that has foreign key reference (referencing table)

  6. List of columns that are used in the foreign key reference. Each column has one of property defined at the same time:

    • name - column name in the referencing table
    • expression - expression that is used to get the value of the column in the referencing table

  7. not_null - is FK has not null constraint. If true Default it is false

  8. expression - expression that is used to get the value of the column in the referencing table
"},{"location":"database_subset/#polymorphic-references","title":"Polymorphic references","text":"

Greenmask supports polymorphic references. You can define a virtual reference for a table with polymorphic references using polymorphic_exprs attribute. The polymorphic_exprs attribute is a list of expressions that are used to make a polymorphic reference. For instance we might have a table comments that has polymorphic reference to posts and videos. The table comments might have commentable_id and commentable_type columns. The commentable_type column contains the type of the table that is referenced by the commentable_id column. The example of the config:

Polymorphic references example
dump:\n  virtual_references:\n    - schema: \"public\"\n      name: \"comments\"\n      references:\n        - schema: \"public\"\n          name: \"videos\"\n          polymorphic_exprs:\n            - \"public.comments.commentable_type = 'video'\"\n          columns:\n            - name: \"commentable_id\"\n        - schema: \"public\"\n          name: \"posts\"\n          polymorphic_exprs:\n            - \"public.comments.commentable_type = 'post'\"\n          columns:\n            - name: \"commentable_id\"\n

Warning

The plimorphic references cannot be non_null because the commentable_id column can be NULL if the commentable_type is not set or different that the values defined in the polymorphic_exprs attribute.

"},{"location":"database_subset/#troubleshooting","title":"Troubleshooting","text":""},{"location":"database_subset/#exclude-the-records-that-has-null-values-in-the-referenced-column","title":"Exclude the records that has NULL values in the referenced column","text":"

If you want to exclude records that have NULL values in the referenced column, you can manually add this condition to the subset condition for the table. Greenmask does not automatically exclude records with NULL values because it applies a LEFT OUTER JOIN on nullable foreign keys.

"},{"location":"database_subset/#some-table-is-not-filtered-by-the-subset-condition","title":"Some table is not filtered by the subset condition","text":"

Greenmask builds a table dependency graph based on the introspected schema and existing foreign keys. If a table is not filtered by the subset condition, it means that the table either does not reference another table that is filtered by the subset condition or the table itself does not have a subset condition applied.

If you have a table with a removed foreign key and want to filter it by the subset condition, you need to define a virtual reference. For more information on virtual references, refer to the Virtual References section.

Info

If you find any issues related to the code or greenmask is not working as expected, do not hesitate to contact us directly or by creating an issue in the repository.

"},{"location":"database_subset/#error-column-reference-id-is-ambiguous","title":"ERROR: column reference \"id\" is ambiguous","text":"

If you see the error message ERROR: column reference \"{column name}\" is ambiguous, you have specified the column name without the table and/or schema name. To avoid ambiguity, always specify the schema and table name when pointing out the column to filter by. For instance if you want to filter employees by employee_id column, you should use public.employees.employee_id instead of employee_id.

Valid subset condition
public.employees.employee_id IN (1, 2, 3)\n
"},{"location":"database_subset/#the-subset-condition-is-not-working-correctly-how-can-i-verify-it","title":"The subset condition is not working correctly. How can I verify it?","text":"

Run greenmask with --log-level=debug to see the generated SQL queries. You will find the generated SQL queries in the log output. Validate this query in your database client to ensure that the subset condition is working as expected.

For example:

$ greenmask dump --config config.yaml --log-level=debug\n\n2024-08-29T19:06:18+03:00 DBG internal/db/postgres/context/context.go:202 > Debug query Schema=person Table=businessentitycontact pid=1638339\n2024-08-29T19:06:18+03:00 DBG internal/db/postgres/context/context.go:203 > SELECT \"person\".\"businessentitycontact\".* FROM \"person\".\"businessentitycontact\"  INNER JOIN \"person\".\"businessentity\" ON \"person\".\"businessentitycontact\".\"businessentityid\" = \"person\".\"businessentity\".\"businessentityid\" AND ( person.businessentity.businessentityid between 400 and 800 OR person.businessentity.businessentityid between 800 and 900 ) INNER JOIN \"person\".\"person\" ON \"person\".\"businessentitycontact\".\"personid\" = \"person\".\"person\".\"businessentityid\" WHERE TRUE AND ((\"person\".\"person\".\"businessentityid\") IN (SELECT \"person\".\"businessentity\".\"businessentityid\" FROM \"person\".\"businessentity\"   WHERE ( ( person.businessentity.businessentityid between 400 and 800 OR person.businessentity.businessentityid between 800 and 900 ) )))\n pid=1638339\n
"},{"location":"database_subset/#dump-is-too-slow","title":"Dump is too slow","text":"

If the dump process is too slow the generated query might be too complex. In this case you can:

  • Check if the database has indexes on the columns used in the subset condition. Create them if possible.
  • Move database dumping on the replica to avoid the performance impact on the primary.
"},{"location":"database_subset/#example-dump-a-subset-of-the-database","title":"Example: Dump a subset of the database","text":"

Info

All examples based on playground database. Read more about the playground database in the Playground section.

The following example demonstrates how to dump a subset of the person schema. The subset condition is applied to the businessentity and password tables. The subset condition filters the data based on the businessentityid and passwordsalt columns, respectively.

Subset configuration example
transformation:\n  - schema: \"person\"\n    name: \"businessentity\"\n    subset_conds:\n      - 'person.businessentity.businessentityid IN (274, 290, 721, 852)'\n    transformers:\n      - name: \"RandomDate\"\n        params:\n          column: \"modifieddate\"\n          min: \"2020-01-01 00:00:00\"\n          max: \"2024-06-26 00:00:00\"\n          truncate: \"day\"\n          keep_null: false\n\n  - schema: \"person\"\n    name: \"password\"\n    subset_conds:\n      - >\n        person.password.passwordsalt = '329eacbe-c883-4f48-b8b6-17aa4627efff'\n
"},{"location":"database_subset/#example-dump-a-subset-with-circular-reference","title":"Example: Dump a subset with circular reference","text":"Create tables with multi cyles
-- Step 1: Create tables without foreign keys\nDROP TABLE IF EXISTS employees CASCADE;\nCREATE TABLE employees\n(\n    employee_id   SERIAL PRIMARY KEY,\n    name          VARCHAR(100) NOT NULL,\n    department_id INT -- Will reference departments(department_id)\n);\n\nDROP TABLE IF EXISTS departments CASCADE;\nCREATE TABLE departments\n(\n    department_id SERIAL PRIMARY KEY,\n    name          VARCHAR(100) NOT NULL,\n    project_id    INT -- Will reference projects(project_id)\n);\n\nDROP TABLE IF EXISTS projects CASCADE;\nCREATE TABLE projects\n(\n    project_id       SERIAL PRIMARY KEY,\n    name             VARCHAR(100) NOT NULL,\n    lead_employee_id INT, -- Will reference employees(employee_id)\n    head_employee_id INT  -- Will reference employees(employee_id)\n);\n\n-- Step 2: Alter tables to add foreign key constraints\nALTER TABLE employees\n    ADD CONSTRAINT fk_department\n        FOREIGN KEY (department_id) REFERENCES departments (department_id);\n\nALTER TABLE departments\n    ADD CONSTRAINT fk_project\n        FOREIGN KEY (project_id) REFERENCES projects (project_id);\n\nALTER TABLE projects\n    ADD CONSTRAINT fk_lead_employee\n        FOREIGN KEY (lead_employee_id) REFERENCES employees (employee_id);\n\nALTER TABLE projects\n    ADD CONSTRAINT fk_lead_employee2\n        FOREIGN KEY (head_employee_id) REFERENCES employees (employee_id);\n\n-- Insert projects\nINSERT INTO projects (name, lead_employee_id)\nSELECT 'Project ' || i, NULL\nFROM generate_series(1, 10) AS s(i);\n\n-- Insert departments\nINSERT INTO departments (name, project_id)\nSELECT 'Department ' || i, i\nFROM generate_series(1, 10) AS s(i);\n\n-- Insert employees and assign 10 of them as project leads\nINSERT INTO employees (name, department_id)\nSELECT 'Employee ' || i, (i / 10) + 1\nFROM generate_series(1, 99) AS s(i);\n\n-- Assign 10 employees as project leads\nUPDATE projects\nSET lead_employee_id = (SELECT employee_id\n                        FROM employees\n                        WHERE employees.department_id = projects.project_id\n                        LIMIT 1),\n    head_employee_id = 3\nWHERE project_id <= 10;\n

This schema has two cycles:

  • employees (department_id) -> departments (project_id) -> projects (lead_employee_id) -> employees (employee_id)
  • employees (department_id) -> departments (project_id) -> projects (head_employee_id) -> employees (employee_id)

Greenmask can simply resolve it by generating a recursive query with integrity checks for subset and join conditions.

The example below will fetch the data for both 3 employees and related departments and projects.

Subset configuration example
transformation:\n  - schema: \"public\"\n    name: \"employees\"\n    subset_conds:\n      - \"public.employees.employee_id in (1, 2, 3)\"\n

But this will return empty result, because the subset condition is not met for all related tables because project with project_id=1 has reference to employee with employee_id=3 that is invalid for subset condition.

Subset configuration example
transformation:\n  - schema: \"public\"\n    name: \"employees\"\n    subset_conds:\n      - \"public.employees.employee_id in (1, 2)\"\n
"},{"location":"database_subset/#example-dump-a-subset-with-virtual-references","title":"Example: Dump a subset with virtual references","text":"

In this example, we will create a subset of the tables with virtual references. The subset will include the orders table and its related tables customers and audit_logs. The orders table has a virtual reference to the customers table, and the audit_logs table has a virtual reference to the orders table.

Create tables with virtual references
-- Create customers table\nCREATE TABLE customers\n(\n    customer_id   SERIAL PRIMARY KEY,\n    customer_name VARCHAR(100)\n);\n\n-- Create orders table\nCREATE TABLE orders\n(\n    order_id    SERIAL PRIMARY KEY,\n    customer_id INT, -- This should reference customers.customer_id, but no FK constraint is defined\n    order_date  DATE\n);\n\n-- Create payments table\nCREATE TABLE payments\n(\n    payment_id     SERIAL PRIMARY KEY,\n    order_id       INT, -- This should reference orders.order_id, but no FK constraint is defined\n    payment_amount DECIMAL(10, 2),\n    payment_date   DATE\n);\n\n-- Insert test data into customers table\nINSERT INTO customers (customer_name)\nVALUES ('John Doe'),\n       ('Jane Smith'),\n       ('Alice Johnson');\n\n-- Insert test data into orders table\nINSERT INTO orders (customer_id, order_date)\nVALUES (1, '2023-08-01'), -- Related to customer John Doe\n       (2, '2023-08-05'), -- Related to customer Jane Smith\n       (3, '2023-08-07');\n-- Related to customer Alice Johnson\n\n-- Insert test data into payments table\nINSERT INTO payments (order_id, payment_amount, payment_date)\nVALUES (1, 100.00, '2023-08-02'), -- Related to order 1 (John Doe's order)\n       (2, 200.50, '2023-08-06'), -- Related to order 2 (Jane Smith's order)\n       (3, 300.75, '2023-08-08');\n-- Related to order 3 (Alice Johnson's order)\n\n\n-- Create a table with a multi-key reference (composite key reference)\nCREATE TABLE order_items\n(\n    order_id     INT,               -- Should logically reference orders.order_id\n    item_id      INT,               -- Composite part of the key\n    product_name VARCHAR(100),\n    quantity     INT,\n    PRIMARY KEY (order_id, item_id) -- Composite primary key\n);\n\n-- Create a table with a JSONB column that contains a reference value\nCREATE TABLE audit_logs\n(\n    log_id   SERIAL PRIMARY KEY,\n    log_data JSONB -- This JSONB field will contain references to other tables\n);\n\n-- Insert data into order_items table with multi-key reference\nINSERT INTO order_items (order_id, item_id, product_name, quantity)\nVALUES (1, 1, 'Product A', 3), -- Related to order_id = 1 from orders table\n       (1, 2, 'Product B', 5), -- Related to order_id = 1 from orders table\n       (2, 1, 'Product C', 2), -- Related to order_id = 2 from orders table\n       (3, 1, 'Product D', 1);\n-- Related to order_id = 3 from orders table\n\n-- Insert data into audit_logs table with JSONB reference value\nINSERT INTO audit_logs (log_data)\nVALUES ('{\n  \"event\": \"order_created\",\n  \"order_id\": 1,\n  \"details\": {\n    \"customer_name\": \"John Doe\",\n    \"total\": 100.00\n  }\n}'),\n       ('{\n         \"event\": \"payment_received\",\n         \"order_id\": 2,\n         \"details\": {\n           \"payment_amount\": 200.50,\n           \"payment_date\": \"2023-08-06\"\n         }\n       }'),\n       ('{\n         \"event\": \"item_added\",\n         \"order_id\": 1,\n         \"item\": {\n           \"item_id\": 2,\n           \"product_name\": \"Product B\",\n           \"quantity\": 5\n         }\n       }');\n

The following example demonstrates how to make a subset for keys that does not have FK constraints but a data relationship exists.

  • The orders table has a virtual reference to the customers table, and the audit_logs table has a virtual reference to the orders table.
  • The payments table has a virtual reference to the orders table.
  • The order_items table has two keys that reference the orders and products tables.
  • The audit_logs table has a JSONB column that contains two references to the orders and order_items tables.
dump:\n  virtual_references:\n    - schema: \"public\"\n      name: \"orders\"\n      references:\n        - schema: \"public\"\n          name: \"customers\"\n          columns:\n            - name: \"customer_id\"\n          not_null: true\n\n    - schema: \"public\"\n      name: \"payments\"\n      references:\n        - schema: \"public\"\n          name: \"orders\"\n          columns:\n            - name: \"order_id\"\n          not_null: true\n\n    - schema: \"public\"\n      name: \"order_items\"\n      references:\n        - schema: \"public\"\n          name: \"orders\"\n          columns:\n            - name: \"order_id\"\n          not_null: true\n        - schema: \"public\"\n          name: \"products\"\n          columns:\n            - name: \"product_id\"\n          not_null: true\n\n    - schema: \"public\"\n      name: \"audit_logs\"\n      references:\n        - schema: \"public\"\n          name: \"orders\"\n          columns:\n            - expression: \"(public.audit_logs.log_data ->> 'order_id')::INT\"\n          not_null: false\n        - schema: \"public\"\n          name: \"order_items\"\n          columns:\n            - expression: \"(public.audit_logs.log_data -> 'item' ->> 'item_id')::INT\"\n            - expression: \"(public.audit_logs.log_data ->> 'order_id')::INT\"\n          not_null: false\n\n  transformation:\n\n    - schema: \"public\"\n      name: \"customers\"\n      subset_conds:\n        - \"public.customers.customer_id in (1)\"\n

As a result, the customers table will be dumped with the orders table and its related tables payments, order_items, and audit_logs. The subset condition will be applied to the customers table, and the data will be filtered based on the customer_id column.

"},{"location":"database_subset/#example-dump-a-subset-with-polymorphic-references","title":"Example: Dump a subset with polymorphic references","text":"

In this example, we will create a subset of the tables with polymorphic references. This example includes the comments table and its related tables posts and videos.

Create tables with polymorphic references and insert data
-- Create the Posts table\nCREATE TABLE posts\n(\n    id      SERIAL PRIMARY KEY,\n    title   VARCHAR(255) NOT NULL,\n    content TEXT         NOT NULL\n);\n\n-- Create the Videos table\nCREATE TABLE videos\n(\n    id    SERIAL PRIMARY KEY,\n    title VARCHAR(255) NOT NULL,\n    url   VARCHAR(255) NOT NULL\n);\n\n-- Create the Comments table with a polymorphic reference\nCREATE TABLE comments\n(\n    id               SERIAL PRIMARY KEY,\n    commentable_id   INT         NOT NULL, -- Will refer to either posts.id or videos.id\n    commentable_type VARCHAR(50) NOT NULL, -- Will store the type of the associated record\n    body             TEXT        NOT NULL,\n    created_at       TIMESTAMP DEFAULT CURRENT_TIMESTAMP\n);\n\n\n-- Insert data into the Posts table\nINSERT INTO posts (title, content)\nVALUES ('First Post', 'This is the content of the first post.'),\n       ('Second Post', 'This is the content of the second post.');\n\n-- Insert data into the Videos table\nINSERT INTO videos (title, url)\nVALUES ('First Video', 'https://example.com/video1'),\n       ('Second Video', 'https://example.com/video2');\n\n-- Insert data into the Comments table, associating some comments with posts and others with videos\n-- For posts:\nINSERT INTO comments (commentable_id, commentable_type, body)\nVALUES (1, 'post', 'This is a comment on the first post.'),\n       (2, 'post', 'This is a comment on the second post.');\n\n-- For videos:\nINSERT INTO comments (commentable_id, commentable_type, body)\nVALUES (1, 'video', 'This is a comment on the first video.'),\n       (2, 'video', 'This is a comment on the second video.');\n

The comments table has a polymorphic reference to the posts and videos tables. Depending on the value of the commentable_type column, the commentable_id column will reference either the posts.id or videos.id column.

The following example demonstrates how to make a subset for tables with polymorphic references.

Subset configuration example
dump:\n  virtual_references:\n    - schema: \"public\"\n      name: \"comments\"\n      references:\n        - schema: \"public\"\n          name: \"posts\"\n          polymorphic_exprs:\n            - \"public.comments.commentable_type = 'post'\"\n          columns:\n            - name: \"commentable_id\"\n        - schema: \"public\"\n          name: \"videos\"\n          polymorphic_exprs:\n            - \"public.comments.commentable_type = 'video'\"\n          columns:\n            - name: \"commentable_id\"\n\n  transformation:\n    - schema: \"public\"\n      name: \"posts\"\n      subset_conds:\n        - \"public.posts.id in (1)\"\n

This example selects only the first post from the posts table and its related comments from the comments table. The comments are associated with videos are included without filtering because the subset condition is applied only to the posts table and related comments.

The resulted records will be:

transformed=# select * from comments;\n id | commentable_id | commentable_type |                 body                  |         created_at         \n----+----------------+------------------+---------------------------------------+----------------------------\n  1 |              1 | post             | This is a comment on the first post.  | 2024-09-18 05:27:54.217405\n  2 |              2 | post             | This is a comment on the second post. | 2024-09-18 05:27:54.217405\n  3 |              1 | video            | This is a comment on the first video. | 2024-09-18 05:27:54.229794\n(3 rows)\n
"},{"location":"installation/","title":"Installation","text":""},{"location":"installation/#prerequisites","title":"Prerequisites","text":"

  • Ensure that you have PostgreSQL utilities preinstalled, matching the major version of your destination server.

  • If you are building Greenmask from source, make sure you have the make utility installed.

"},{"location":"installation/#via-docker","title":"Via docker","text":"

You can find the docker images in the:

  1. Docker-hub page

To run the greenmask container from DockerHub, use the following command: 

docker run -it greenmask/greenmask:latest\n

  1. GitHub container registry

To run the greenmask container from Github registry, use the following command: 

docker run -it ghcr.io/greenmaskio/greenmask:latest\n

Info

For pre-releases (rc, beta, etc.), use explicit tags like v0.2.0b2.

"},{"location":"installation/#via-brew","title":"Via brew","text":"

The greenmask build is available in brew, but only a production build is available. To install the greenmask via brew, use the following command:

brew install greenmask\n
"},{"location":"installation/#from-source","title":"From source","text":"

  1. Clone the Greenmask repository by using the following command:

    git clone git@github.com:GreenmaskIO/greenmask.git\n

  2. Once the repository is cloned, execute the following command to build Greenmask:

    make build\n

After completing the build process, you will find the binary named greenmask in the root directory of the repository. Execute the binary to start using Greenmask.

"},{"location":"installation/#playground","title":"Playground","text":"

Greenmask Playground is a sandbox environment for your experiments in Docker with sample databases included to help you try Greenmask without any additional actions. Read the Playground guide to learn more.

"},{"location":"playground/","title":"Greenmask Playground","text":"

Greenmask Playground is a sandbox environment in Docker with sample databases included to help you try Greenmask without any additional actions. It includes the following components:

  • Original database \u2014 the source database you'll be working with.
  • Empty database for restoration \u2014 an empty database where the restored data will be placed.
  • MinIO storage \u2014 used for storage purposes.
  • Greenmask Utility \u2014 Greenmask itself, ready for use.

Warning

To complete this guide, you must have Docker and docker-compose installed.

"},{"location":"playground/#setting-up-greenmask-playground","title":"Setting up Greenmask Playground","text":"

  1. Clone the greenmask repository and navigate to its directory by running the following commands:

    git clone git@github.com:GreenmaskIO/greenmask.git && cd greenmask\n

  2. Once you have cloned the repository, start the environment by running Docker Compose:

    docker-compose run greenmask\n

Tip

If you're experiencing problems with pulling images from Docker Hub, you can build the Greenmask image from source by running the following command:

docker-compose run greenmask-from-source\n

Now you have Greenmask Playground up and running with a shell prompt inside the container. All further operations will be carried out within this container's shell.

"},{"location":"playground/#commands","title":"Commands","text":"

Below you can see Greenmask commands:

  • dump \u2014 performs a logical data dump, transforms the data, and stores it in the designated storage.

  • list-dumps \u2014 retrieves a list of all stored dumps within the chosen storage.

  • delete \u2014 removes a dump with a specific ID from the storage.

  • list-transformers \u2014 displays a list of approved transformers and their documentation.

  • restore \u2014 restores a dump either by specifying its ID or using the latest available dump to the target database.

  • show-dump \u2014 presents metadata information about a specific dump (equivalent to pg_restore -l ./).

  • validate \u2014 executes a validation process and generates a data diff for the transformation.

  • completion \u2014 generates the autocompletion script for the specified shell.

To learn more about them, see Commands.

"},{"location":"playground/#transformers","title":"Transformers","text":"

A configuration file is mandatory for Greenmask functioning. The pre-defined configuration file is stored at the repository root directory (./playground/config.yml). It also serves to define transformers which you can update to your liking in order to use Greenmask Playground more effectively and to get better understanding of the tool itself. To learn how to customize a configuration file, see Configuration

The pre-defined configuration file uses the NoiseDate transformer as an example. To learn more about other transformers and how to use them, see Transformers.

"},{"location":"built_in_transformers/","title":"About transformers","text":"

Transformers in Greenmask are methods which are applied to anonymize sensitive data. All Greenmask transformers are split into the following groups:

  • Dynamic parameters \u2014 transformers that require an input of parameters and generate random data based on them.
  • Transformation engines \u2014 the type of generator used in transformers. Hash (deterministic) and random (randomization)
  • Parameters templating \u2014 generate static parameters values from templates.
  • Transformation conditions \u2014 conditions that can be applied to transformers. If the condition is not met, the transformer will not be applied.
  • Transformation Inheritance \u2014 transformation inheritance for partitioned tables and tables with foreign keys. Define once and apply to all.
  • Standard transformers \u2014 transformers that require only an input of parameters.
  • Advanced transformers \u2014 transformers that can be modified according to user's needs with the help of custom functions.
  • Custom transformers \u2014 coming soon...
"},{"location":"built_in_transformers/dynamic_parameters/","title":"Dynamic parameters","text":""},{"location":"built_in_transformers/dynamic_parameters/#description","title":"Description","text":"

Most transformers in Greenmask have dynamic parameters. This functionality is possible because Greenmask utilizes a database driver that can encode and decode raw values into their actual type representations.

This allows you to retrieve parameter values directly from the records. This capability is particularly beneficial when you need to resolve functional dependencies between fields or satisfy constraints. Greenmask processes transformations sequentially. Therefore, when you reference a field that was transformed in a previous step, you will access the transformed value.

"},{"location":"built_in_transformers/dynamic_parameters/#definition","title":"Definition","text":"
dynamic_params:\n  - column: \"column_name\" # (1)\n    cast_to: \"cast_function\" # (2)\n    template: \"template_function\" # (3)\n    default_value: any # (4)\n
  1. Name of the column from which the value is retrieved.
  2. Function used to cast the column value to the desired type.
  3. Default value used if the column's value is NULL.
  4. Template used for casting the column value to the desired type.
"},{"location":"built_in_transformers/dynamic_parameters/#dynamic-parameter-options","title":"Dynamic parameter options","text":"

  • column - Specifies the column name. The value from each record in this column will be passed to the transformer as a parameter.

  • cast_to - Indicates the function used to cast the column value to the desired type. Before being passed to the transformer, the value is cast to this type. For more details, see Cast functions.

  • template - Defines the template used for casting the column value to the desired type. You can create your own template and incorporate predefined functions and operators to implement the casting logic or other logic required for passing the value to the transformer. For more details, see Template functions.

  • default_value - Determines the default value used if the column's value is NULL. This value is represented in raw format appropriate to the type specified in the column parameter.

"},{"location":"built_in_transformers/dynamic_parameters/#cast-functions","title":"Cast functions","text":"name description input type output type UnixNanoToDate Cast int value as Unix Timestamp in Nano Seconds to date type int2, int4, int8, numeric, float4, float8 date UnixMicroToDate Cast int value as Unix Timestamp in Micro Seconds to date type int2, int4, int8, numeric, float4, float8 date UnixMilliToDate Cast int value as Unix Timestamp in Milli Seconds to date type int2, int4, int8, numeric, float4, float8 date UnixSecToDate Cast int value as Unix Timestamp in Seconds to date type int2, int4, int8, numeric, float4, float8 date UnixNanoToTimestamp Cast int value as Unix Timestamp in Nano Seconds to timestamp type int2, int4, int8, numeric, float4, float8 timestamp UnixMicroToTimestamp Cast int value as Unix Timestamp in Micro Seconds to timestamp type int2, int4, int8, numeric, float4, float8 timestamp UnixMilliToTimestamp Cast int value as Unix Timestamp in Milli Seconds to timestamp type int2, int4, int8, numeric, float4, float8 timestamp UnixSecToTimestamp Cast int value as Unix Timestamp in Seconds to timestamp type int2, int4, int8, numeric, float4, float8 timestamp UnixNanoToTimestampTz Cast int value as Unix Timestamp in Nano Seconds to timestamptz type int2, int4, int8, numeric, float4, float8 timestamptz UnixMicroToTimestampTz Cast int value as Unix Timestamp in Micro Seconds to timestamptz type int2, int4, int8, numeric, float4, float8 timestamptz UnixMilliToTimestampTz Cast int value as Unix Timestamp in Milli Seconds to timestamptz type int2, int4, int8, numeric, float4, float8 timestamptz UnixSecToTimestampTz Cast int value as Unix Timestamp in Seconds to timestamptz type int2, int4, int8, numeric, float4, float8 timestamptz DateToUnixNano Cast date value to int value as a Unix Timestamp in Nano Seconds date int2, int4, int8, numeric, float4, float8 DateToUnixMicro Cast date value to int value as a Unix Timestamp in Micro Seconds date int2, int4, int8, numeric, float4, float8 DateToUnixMilli Cast date value to int value as a Unix Timestamp in Milli Seconds date int2, int4, int8, numeric, float4, float8 DateToUnixSec Cast date value to int value as a Unix Timestamp in Seconds date int2, int4, int8, numeric, float4, float8 TimestampToUnixNano Cast timestamp value to int value as a Unix Timestamp in Nano Seconds timestamp int2, int4, int8, numeric, float4, float8 TimestampToUnixMicro Cast timestamp value to int value as a Unix Timestamp in Micro Seconds timestamp int2, int4, int8, numeric, float4, float8 TimestampToUnixMilli Cast timestamp value to int value as a Unix Timestamp in Milli Seconds timestamp int2, int4, int8, numeric, float4, float8 TimestampToUnixSec Cast timestamp value to int value as a Unix Timestamp in Seconds timestamp int2, int4, int8, numeric, float4, float8 TimestampTzToUnixNano Cast timestamptz value to int value as a Unix Timestamp in Nano Seconds timestamptz int2, int4, int8, numeric, float4, float8 TimestampTzToUnixMicro Cast timestamptz value to int value as a Unix Timestamp in Micro Seconds timestamptz int2, int4, int8, numeric, float4, float8 TimestampTzToUnixMilli Cast timestamptz value to int value as a Unix Timestamp in Milli Seconds timestamptz int2, int4, int8, numeric, float4, float8 TimestampTzToUnixSec Cast timestamptz value to int value as a Unix Timestamp in Seconds timestamptz int2, int4, int8, numeric, float4, float8 FloatToInt Cast float value to one of integer type. The fractional part will be discarded numeric, float4, float8 int2, int4, int8, numeric IntToFloat Cast int value to one of integer type int2, int4, int8, numeric numeric, float4, float8 IntToBool Cast int value to boolean. The value with 0 is false, 1 is true int2, int4, int8, numeric, float4, float8 bool BoolToInt Cast boolean value to int. The value false is 0, true is 1 bool int2, int4, int8, numeric, float4, float8"},{"location":"built_in_transformers/dynamic_parameters/#example-functional-dependency-resolution-between-columns","title":"Example: Functional dependency resolution between columns","text":"

There is simplified schema of the table humanresources.employee from the playground:

       Column      |            Type                      \n------------------+-----------------------------\n businessentityid | integer                      \n jobtitle         | character varying(50)        \n birthdate        | date                        \n hiredate         | date                         \nCheck constraints:\n    CHECK (birthdate >= '1930-01-01'::date AND birthdate <= (now() - '18 years'::interval))\n

As you can see, there is a functional dependency between the birthdate and hiredate columns. Logically, the hiredate should be later than the birthdate. Additionally, the birthdate should range from 1930-01-01 to 18 years prior to the current date.

Imagine that you need to generate random birthdate and hiredate columns. To ensure these dates satisfy the constraints, you can use dynamic parameters in the RandomDate transformer:

- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n\n    - name: \"RandomDate\" # (1)\n      params:\n        column: \"birthdate\"\n        min: '{{ now | tsModify \"-30 years\" | .EncodeValue }}' # (2)\n        max: '{{ now | tsModify \"-18 years\" | .EncodeValue }}' # (3)\n\n    - name: \"RandomDate\" # (4)\n      params:\n        column: \"hiredate\"\n        max: \"{{ now | .EncodeValue }}\" # (5)\n      dynamic_params:\n        min:\n          column: \"birthdate\" # (6)\n          template: '{{ .GetValue | tsModify \"18 years\" | .EncodeValue }}' # (7)\n
  1. Firstly we generate the RadnomDate for birthdate column. The result of the transformation will used as the minimum value for the next transformation for hiredate column.
  2. Apply the template for static parameter. It calculates the now date and subtracts 30 years from it. The result is 1994. The function tsModify return not a raw data, but time.Time object. For getting the raw value suitable for birthdate type we need to pass this value to .EncodeValue function. This value is used as the minimum value for the birthdate column.
  3. The same as the previous step, but we subtract 18 years from the now date. The result is 2002.
  4. Generate the RadnomDate for hiredate column based on the value from the birthdate.
  5. Set the maximum value for the hiredate column. The value is the current date.
  6. The min parameter is set to the value of the birthdate column from the previous step.
  7. The template gets the value of the randomly generated birthdate value and adds 18 years to it.

Below is the result of the transformation:

From the result, you can see that all functional dependencies and constraints are satisfied.

"},{"location":"built_in_transformers/parameters_templating/","title":"Parameters templating","text":""},{"location":"built_in_transformers/parameters_templating/#description","title":"Description","text":"

It is allowed to generate parameter values from templates. It is useful when you don't want to write values manually, but instead want to generate and initialize them dynamically.

Here you can find the list of template functions that can be used in the template Custom functions.

You can encode and decode objects using the driver function bellow.

"},{"location":"built_in_transformers/parameters_templating/#template-functions","title":"Template functions","text":"Function Description Signature .GetColumnType Returns a string with the column type. .GetColumnType(name string) (typeName string, err error) .EncodeValueByColumn Encodes a value of any type into its raw string representation using the specified column name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValueByColumn(name string, value any) (res any, err error) .DecodeValueByColumn Decodes a value from its raw string representation to a Golang type using the specified column name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByColumn(name string, value any) (res any, err error) .EncodeValueByType Encodes a value of any type into its string representation using the specified type name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValueByType(name string, value any) (res any, err error) .DecodeValueByType Decodes a value from its raw string representation to a Golang type using the specified type name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByType(name string, value any) (res any, err error) .DecodeValue Decodes a value from its raw string representation to a Golang type using the data type assigned to the table column specified in the column parameter. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByColumn(value any) (res any, err error) .EncodeValue Encodes a value of any type into its string representation using the type assigned to the table column specified in the column parameter. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValue(value any) (res any, err error)

Warning

If column parameter is not linked to column parameter, then functions .DecodeValue and .EncodeValue will return an error. You can use .DecodeValueByType and .EncodeValueByType or .DecodeValueByColumn and .EncodeValueByColumn instead.

"},{"location":"built_in_transformers/parameters_templating/#example","title":"Example","text":"

In the example below, the min and max values for the birth_date column are generated dynamically using the now template function. The value returns the current date and time. The tsModify function is then used to subtract 30 (and 18) years. But because the parameter type is mapped on column parameter type, the EncodeValue function is used to encode the value into the column type.

For example, if we have the now date as 2021-01-01, the dynamically calculated min value will be 1994-01-01 and the max value will be 2006-01-01.

CREATE TABLE account\n(\n    id         SERIAL PRIMARY KEY,\n    gender     VARCHAR(1) NOT NULL,\n    email      TEXT       NOT NULL NOT NULL UNIQUE,\n    first_name TEXT       NOT NULL,\n    last_name  TEXT       NOT NULL,\n    birth_date DATE,\n    created_at TIMESTAMP  NOT NULL DEFAULT NOW()\n);\n\nINSERT INTO account (first_name, gender, last_name, birth_date, email)\nVALUES ('John', 'M', 'Smith', '1980-01-01', 'john.smith@gmail.com');\n
- schema: \"public\"\n  name: \"account\"\n  transformers:\n    - name: \"RandomDate\"\n      params:\n        column: \"birth_date\"\n        min: '{{ now | tsModify \"-30 years\" | .EncodeValue }}' # 1994\n        max: '{{ now | tsModify \"-18 years\" | .EncodeValue }}' # 2006\n

Result

ColumnOriginalValueTransformedValue birth_date1980-01-011995-09-06"},{"location":"built_in_transformers/transformation_condition/","title":"Transformation Condition","text":""},{"location":"built_in_transformers/transformation_condition/#description","title":"Description","text":"

The transformation condition feature allows you to execute a defined transformation only if a specified condition is met. The condition must be defined as a boolean expression that evaluates to true or false. Greenmask uses expr-lang/expr under the hood. You can use all functions and syntax provided by the expr library.

You can use the same functions that are described in the built-in transformers

The transformers are executed one by one - this helps you create complex transformation pipelines. For instance depending on value chosen in the previous transformer, you can decide to execute the next transformer or not.

"},{"location":"built_in_transformers/transformation_condition/#record-descriptors","title":"Record descriptors","text":"

To improve the user experience, Greenmask offers special namespaces for accessing values in different formats: either the driver-encoded value in its real type or as a raw string.

  • record: This namespace provides the record value in its actual type.
  • raw_record: This namespace provides the record value as a string.

You can access a specific column\u2019s value using record.column_name for the real type or raw_record.column_name for the raw string value.

Warning

A record may always be modified by previous transformers before the condition is evaluated. This means Greenmask does not retain the original record value and instead provides the current modified value for condition evaluation.

"},{"location":"built_in_transformers/transformation_condition/#null-values-condition","title":"Null values condition","text":"

To check if the value is null, you can use null value for the comparisson. This operation works compatibly with SQL operator IS NULL or IS NOT NULL.

Is null cond example
record.accountnumber == null && record.date > now()\n
Is not null cond example
record.accountnumber != null && record.date <= now()\n
"},{"location":"built_in_transformers/transformation_condition/#expression-scope","title":"Expression scope","text":"

Expression scope can be on table or specific transformer. If you define the condition on the table scope, then the condition will be evaluated before any transformer is executed. If you define the condition on the transformer scope, then the condition will be evaluated before the specified transformer is executed.

Table scope
- schema: \"purchasing\"\n  name: \"vendor\"\n  when: 'record.accountnumber == null || record.accountnumber == \"ALLENSON0001\"'\n  transformers:\n    - name: \"RandomString\"\n      params:\n        column: \"accountnumber\"\n        min_length: 9\n        max_length: 12\n        symbols: \"1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ\"\n
Transformer scope
- schema: \"purchasing\"\n  name: \"vendor\"\n  transformers:\n    - name: \"RandomString\"\n      when: 'record.accountnumber != null || record.accountnumber == \"ALLENSON0001\"'\n      params:\n        column: \"accountnumber\"\n        min_length: 9\n        max_length: 12\n        symbols: \"1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ\"\n
"},{"location":"built_in_transformers/transformation_condition/#int-and-float-value-definition","title":"Int and float value definition","text":"

It is important to create the integer or float value in the correct format. If you want to define the integer value you must write a number without dot (1, 2, etc.). If you want to define the float value you must write a number with dot (1.0, 2.0, etc.).

Warning

You may see a wrong comparison result if you compare int and float, for example 1 == 1.0 will return false.

"},{"location":"built_in_transformers/transformation_condition/#architecture","title":"Architecture","text":"

Greenmask encodes the way only when evaluating the condition - this allows to optimize the performance of the transformation if you have a lot of conditions that uses or (||) or and (&&) operators.

"},{"location":"built_in_transformers/transformation_condition/#example-chose-random-value-and-execute-one-of","title":"Example: Chose random value and execute one of","text":"

In the following example, the RandomChoice transformer is used to choose a random value from the list of values. Depending on the chosen value, the Replace transformer is executed to set the activeflag column to true or false.

In this case the condition scope is on the transformer level.

- schema: \"purchasing\"\n  name: \"vendor\"\n  transformers:\n    - name: \"RandomChoice\"\n      params:\n        column: \"name\"\n        values:\n          - \"test1\"\n          - \"test2\"\n\n    - name: \"Replace\"\n      when: 'record.name == \"test1\"'\n      params:\n        column: \"activeflag\"\n        value: \"false\"\n\n    - name: \"Replace\"\n      when: 'record.name == \"test2\"'\n      params:\n        column: \"activeflag\"\n        value: \"true\"\n
"},{"location":"built_in_transformers/transformation_condition/#example-do-not-transform-specific-columns","title":"Example: Do not transform specific columns","text":"

In the following example, the RandomString transformer is executed only if the businessentityid column value is not equal to 1492 or 1.

  - schema: \"purchasing\"\n    name: \"vendor\"\n    when: '!(record.businessentityid | has([1492, 1]))'\n    transformers:\n      - name: \"RandomString\"\n        params:\n          column: \"accountnumber\"\n          min_length: 9\n          max_length: 12\n          symbols: \"1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ\"\n
"},{"location":"built_in_transformers/transformation_condition/#example-check-the-json-attribute-value","title":"Example: Check the json attribute value","text":"

In the following example, the RandomString transformer is executed only if the a attribute in the json_data column is equal to 1.

- schema: \"public\"\n  name: \"jsondata\"\n  when: 'raw_record.json_data | jsonGet(\"a\") == 1'\n  transformers:\n    - name: \"RandomString\"\n      params:\n        column: \"accountnumber\"\n        min_length: 9\n        max_length: 12\n        symbols: \"1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ\"\n
"},{"location":"built_in_transformers/transformation_engines/","title":"Transformation engine","text":"

The greenmask provides two engines random and hash. Most of the transformers has engine parameters that by default is set to random. Use hash engine when you need to generate deterministic data - the same input will always produce the same output.

Info

Greenmask employs the SHA-3 algorithm to hash input values. While this function is cryptographically secure, it does exhibit lower performance. We plan to introduce additional hash functions in the future to offer a balance between security and performance. For example, SipHash, which provides a good trade-off between security and performance, is currently in development and is expected to be included in the stable v0.2 release of Greenmask.

Warning

The hash engine does not guarantee the uniqueness of generated values. Although transformers such as Hash, RandomEmail, and RandomUuid typically have a low probability of producing duplicate values The feature to ensure uniqueness is currently under development at Greenmask and is expected to be released in future updates. For the latest status, please visit the Greenmask roadmap.

"},{"location":"built_in_transformers/transformation_engines/#details","title":"Details","text":""},{"location":"built_in_transformers/transformation_engines/#example-schema","title":"Example schema","text":"

The next examples will be run on the following schema and sample data:

CREATE TABLE account\n(\n    id         SERIAL PRIMARY KEY,\n    gender     VARCHAR(1) NOT NULL,\n    email      TEXT       NOT NULL NOT NULL UNIQUE,\n    first_name TEXT       NOT NULL,\n    last_name  TEXT       NOT NULL,\n    birth_date DATE,\n    created_at TIMESTAMP  NOT NULL DEFAULT NOW()\n);\n\nINSERT INTO account (first_name, gender, last_name, birth_date, email)\nVALUES ('John', 'M', 'Smith', '1980-01-01', 'john.smith@gmail.com');\n\nCREATE TABLE orders\n(\n    id          SERIAL PRIMARY KEY,\n    account_id  INTEGER REFERENCES account (id),\n    total_price NUMERIC(10, 2),\n    created_at  TIMESTAMP NOT NULL DEFAULT NOW(),\n    paid_at     TIMESTAMP\n);\n\nINSERT INTO orders (account_id, total_price, created_at, paid_at)\nVALUES (1, 100.50, '2024-05-01', '2024-05-02'),\n       (1, 200.75, '2024-05-03', NULL);\n
"},{"location":"built_in_transformers/transformation_engines/#random-engine","title":"Random engine","text":"

The random engine serves as the default engine for the greenmask. It operates using a pseudo-random number generator, which is initialized with a random seed sourced from a cryptographically secure random number generator. Employ the random engine when you need to generate random data and do not require reproducibility of the same transformation results with the same input.

The following example demonstrates how to configure the RandomDate transformer to generate random.

- schema: \"public\"\n  name: \"account\"\n  transformers:\n    - name: \"RandomDate\"\n      params:\n        column: \"birth_date\"\n        engine: \"random\" # (1)\n        min: '1970-01-01'\n        max: '2000-01-01'\n
  1. random engine is explicitly specified, although it is the default value.

Results:

ColumnOriginalValueTransformedValue birth_date1980-01-011970-02-23

Keep in mind that the random engine is always generates different values for the same input. For instance in we run the previous example multiple times we will get different results.

"},{"location":"built_in_transformers/transformation_engines/#hash-engine","title":"Hash engine","text":"

The hash engine is designed to generate deterministic data. It uses the SHA-3 algorithm to hash the input value. The hash engine is particularly useful when you need to generate the same output for the same input. For example, when you want to transform values that are used as primary or foreign keys in a database.

For secure reason it is suggested set global greenmask salt via GREENMASK_GLOBAL_SALT environment variable. The salt is added to the hash input to prevent the possibility of reverse engineering the original value from the hashed output. The value is hex encoded with variadic length. For example, GREENMASK_GLOBAL_SALT=a5eddc84e762e810. Generate a strong random salt and keep it secret.

The following example demonstrates how to configure the RandomInt transformer to generate deterministic data using the hash engine. The public.account.id and public.orders.account_id columns will have the same values.

- schema: \"public\"\n  name: \"account\"\n  transformers:\n\n    - name: \"RandomInt\"\n      params:\n        column: \"id\"\n        engine: hash\n        min: 1\n        max: 2147483647\n\n- schema: \"public\"\n  name: \"orders\"\n  transformers:\n\n    - name: \"RandomInt\"\n      params:\n        column: \"account_id\"\n        engine: hash\n        min: 1\n        max: 2147483647\n

Result:

  • public.account
ColumnOriginalValueTransformedValue id1130162079
  • public.orders
ColumnOriginalValueTransformedValue account_id1130162079"},{"location":"built_in_transformers/transformation_inheritance/","title":"Transformation Inheritance","text":""},{"location":"built_in_transformers/transformation_inheritance/#description","title":"Description","text":"

If you have partitioned tables or want to apply a transformation to a primary key and propagate it to all tables referencing that column, you can do so with Greenmask.

"},{"location":"built_in_transformers/transformation_inheritance/#apply-for-inherited","title":"Apply for inherited","text":"

Using apply_for_inherited, you can apply transformations to all partitions of a partitioned table, including any subpartitions.

"},{"location":"built_in_transformers/transformation_inheritance/#configuration-conflicts","title":"Configuration conflicts","text":"

When a partition has a transformation defined manually via config, and apply_for_inherited is set on the parent table, Greenmask will merge both the inherited and manually defined configurations. The manually defined transformation will execute last, giving it higher priority.

If this situation occurs, you will see the following information in the log:

{\n  \"level\": \"info\",\n  \"ParentTableSchema\": \"public\",\n  \"ParentTableName\": \"sales\",\n  \"ChildTableSchema\": \"public\",\n  \"ChildTableName\": \"sales_2022_feb\",\n  \"ChildTableConfig\": [\n    {\n      \"name\": \"RandomDate\",\n      \"params\": {\n        \"column\": \"sale_date\",\n        \"engine\": \"random\",\n        \"max\": \"2005-01-01\",\n        \"min\": \"2001-01-01\"\n      }\n    }\n  ],\n  \"time\": \"2024-11-03T22:14:01+02:00\",\n  \"message\": \"config will be merged: found manually defined transformers on the partitioned table\"\n}\n
"},{"location":"built_in_transformers/transformation_inheritance/#apply-for-references","title":"Apply for references","text":"

Using apply_for_references, you can apply transformations to columns involved in a primary key or in tables with a foreign key that references that column. This simplifies the transformation process by requiring you to define the transformation only on the primary key column, which will then be applied to all tables referencing that column.

The transformer must be deterministic or support hash engine and the hash engin must be set in the configuration file.

List of transformers that supports apply_for_references:

  • Hash
  • NoiseDate
  • NoiseFloat
  • NoiseInt
  • NoiseNumeric
  • RandomBool
  • RandomDate
  • RandomEmail
  • RandomFloat
  • RandomInt
  • RandomIp
  • RandomMac
  • RandomNumeric
  • RandomString
  • RandomUuid
  • RandomUnixTimestamp
"},{"location":"built_in_transformers/transformation_inheritance/#end-to-end-identifiers","title":"End-to-End Identifiers","text":"

End-to-end identifiers in databases are unique identifiers that are consistently used across multiple tables in a relational database schema, allowing for a seamless chain of references from one table to another. These identifiers typically serve as primary keys in one table and are propagated as foreign keys in other tables, creating a direct, traceable link from one end of a data relationship to the other.

Greenmask can detect end-to-end identifiers and apply transformations across the entire sequence of tables. These identifiers are detected when the following condition is met: the foreign key serves as both a primary key and a foreign key in the referenced table.

"},{"location":"built_in_transformers/transformation_inheritance/#configuration-conflicts_1","title":"Configuration conflicts","text":"

When on the referenced column a transformation is manually defined via config, and the apply_for_references is set on parent table, the transformation defined will be chosen and the inherited transformation will be ignored. You will receive a INFO message in the logs.

{\n  \"level\": \"info\",\n  \"TransformerName\": \"RandomInt\",\n  \"ParentTableSchema\": \"public\",\n  \"ParentTableName\": \"tablea\",\n  \"ChildTableSchema\": \"public\",\n  \"ChildTableName\": \"tablec\",\n  \"ChildColumnName\": \"id2\",\n  \"TransformerConfig\": {\n    \"name\": \"RandomInt\",\n    \"apply_for_references\": true\n  },\n  \"time\": \"2024-11-03T21:28:10+02:00\",\n  \"message\": \"skipping apply transformer for reference: found manually configured transformer\"\n}\n
"},{"location":"built_in_transformers/transformation_inheritance/#limitations","title":"Limitations","text":"
  • The transformation must be deterministic.
  • The transformation condition will not be applied to the referenced column.
  • Not all transformers support apply_for_references

Warning

We do not recommend using apply_for_references with transformation conditions, as these conditions are not inherited by transformers on the referenced columns. This may lead to inconsistencies in the data.

"},{"location":"built_in_transformers/transformation_inheritance/#example-1-partitioned-tables","title":"Example 1. Partitioned tables","text":"

In this example, we have a partitioned table sales that is partitioned by year and then by month. Each partition contains a subset of data based on the year and month of the sale. The sales table has a primary key sale_id and is partitioned by sale_date. The sale_date column is transformed using the RandomDate transformer.

CREATE TABLE sales\n(\n    sale_id   SERIAL         NOT NULL,\n    sale_date DATE           NOT NULL,\n    amount    NUMERIC(10, 2) NOT NULL\n) PARTITION BY RANGE (EXTRACT(YEAR FROM sale_date));\n\n-- Step 2: Create first-level partitions by year\nCREATE TABLE sales_2022 PARTITION OF sales\n    FOR VALUES FROM (2022) TO (2023)\n    PARTITION BY LIST (EXTRACT(MONTH FROM sale_date));\n\nCREATE TABLE sales_2023 PARTITION OF sales\n    FOR VALUES FROM (2023) TO (2024)\n    PARTITION BY LIST (EXTRACT(MONTH FROM sale_date));\n\n-- Step 3: Create second-level partitions by month for each year, adding PRIMARY KEY on each partition\n\n-- Monthly partitions for 2022\nCREATE TABLE sales_2022_jan PARTITION OF sales_2022 FOR VALUES IN (1)\n    WITH (fillfactor = 70);\nCREATE TABLE sales_2022_feb PARTITION OF sales_2022 FOR VALUES IN (2);\nCREATE TABLE sales_2022_mar PARTITION OF sales_2022 FOR VALUES IN (3);\n-- Continue adding monthly partitions for 2022...\n\n-- Monthly partitions for 2023\nCREATE TABLE sales_2023_jan PARTITION OF sales_2023 FOR VALUES IN (1);\nCREATE TABLE sales_2023_feb PARTITION OF sales_2023 FOR VALUES IN (2);\nCREATE TABLE sales_2023_mar PARTITION OF sales_2023 FOR VALUES IN (3);\n-- Continue adding monthly partitions for 2023...\n\n-- Step 4: Insert sample data\nINSERT INTO sales (sale_date, amount)\nVALUES ('2022-01-15', 100.00);\nINSERT INTO sales (sale_date, amount)\nVALUES ('2022-02-20', 150.00);\nINSERT INTO sales (sale_date, amount)\nVALUES ('2023-03-10', 200.00);\n

To transform the sale_date column in the sales table and all its partitions, you can use the following configuration:

- schema: public\n  name: sales\n  apply_for_inherited: true\n  transformers:\n    - name: RandomDate\n      params:\n        min: \"2022-01-01\"\n        max: \"2022-03-01\"\n        column: \"sale_date\"\n        engine: \"random\"\n
"},{"location":"built_in_transformers/transformation_inheritance/#example-2-simple-table-references","title":"Example 2. Simple table references","text":"

This is ordinary table references where the primary key of the users table is referenced in the orders table.

-- Enable the extension for UUID generation (if not enabled)\nCREATE EXTENSION IF NOT EXISTS \"uuid-ossp\";\n\nCREATE TABLE users\n(\n    user_id  UUID PRIMARY KEY DEFAULT uuid_generate_v4(),\n    username VARCHAR(50) NOT NULL\n);\n\nCREATE TABLE orders\n(\n    order_id   UUID PRIMARY KEY DEFAULT uuid_generate_v4(),\n    user_id    UUID REFERENCES users (user_id),\n    order_date DATE NOT NULL\n);\n\nINSERT INTO users (username)\nVALUES ('john_doe');\nINSERT INTO users (username)\nVALUES ('jane_smith');\n\nINSERT INTO orders (user_id, order_date)\nVALUES ((SELECT user_id FROM users WHERE username = 'john_doe'), '2024-10-31'),\n       ((SELECT user_id FROM users WHERE username = 'jane_smith'), '2024-10-30');\n

To transform the username column in the users table, you can use the following configuration:

- schema: public\n  name: users\n  apply_for_inherited: true\n  transformers:\n    - name: RandomUuid\n      apply_for_references: true\n      params:\n        column: \"user_id\"\n        engine: \"hash\"\n

This will apply the RandomUuid transformation to the user_id column in the orders table automatically.

"},{"location":"built_in_transformers/transformation_inheritance/#example-3-references-on-tables-with-end-to-end-identifiers","title":"Example 3. References on tables with end-to-end identifiers","text":"

In this example, we have three tables: tablea, tableb, and tablec. All tables have a composite primary key. In the tables tableb and tablec, the primary key is also a foreign key that references the primary key of tablea. This means that all PKs are end-to-end identifiers.

CREATE TABLE tablea\n(\n    id1  INT,\n    id2  INT,\n    data VARCHAR(50),\n    PRIMARY KEY (id1, id2)\n);\n\nCREATE TABLE tableb\n(\n    id1    INT,\n    id2    INT,\n    detail VARCHAR(50),\n    PRIMARY KEY (id1, id2),\n    FOREIGN KEY (id1, id2) REFERENCES tablea (id1, id2) ON DELETE CASCADE\n);\n\nCREATE TABLE tablec\n(\n    id1         INT,\n    id2         INT,\n    description VARCHAR(50),\n    PRIMARY KEY (id1, id2),\n    FOREIGN KEY (id1, id2) REFERENCES tableb (id1, id2) ON DELETE CASCADE\n);\n\nINSERT INTO tablea (id1, id2, data)\nVALUES (1, 1, 'Data A1'),\n       (2, 1, 'Data A2'),\n       (3, 1, 'Data A3');\n\nINSERT INTO tableb (id1, id2, detail)\nVALUES (1, 1, 'Detail B1'),\n       (2, 1, 'Detail B2'),\n       (3, 1, 'Detail B3');\n\nINSERT INTO tablec (id1, id2, description)\nVALUES (1, 1, 'Description C1'),\n       (2, 1, 'Description C2'),\n       (3, 1, 'Description C3');\n

To transform the data column in tablea, you can use the following configuration:

- schema: public\n  name: \"tablea\"\n  apply_for_inherited: true\n  transformers:\n    - name: RandomInt\n      apply_for_references: true\n      params:\n        min: 0\n        max: 100\n        column: \"id1\"\n        engine: \"hash\"\n    - name: RandomInt\n      apply_for_references: true\n      params:\n        min: 0\n        max: 100\n        column: \"id2\"\n        engine: \"hash\"\n

This will apply the RandomInt transformation to the id1 and id2 columns in tableb and tablec automatically.

"},{"location":"built_in_transformers/advanced_transformers/","title":"Advanced transformers","text":"

Advanced transformers are modifiable anonymization methods that users can adjust based on their needs by using custom functions.

Below you can find an index of all advanced transformers currently available in Greenmask.

  1. Json \u2014 changes a JSON content by using delete and set operations.
  2. Template \u2014 executes a Go template of your choice and applies the result to a specified column.
  3. TemplateRecord \u2014 modifies records by using a Go template of your choice and applies the changes via the PostgreSQL driver.
"},{"location":"built_in_transformers/advanced_transformers/json/","title":"Json","text":"

Change a JSON document using delete and set operations. NULL values are kept.

"},{"location":"built_in_transformers/advanced_transformers/json/#parameters","title":"Parameters","text":"Name Properties Description Default Required Supported DB types column The name of the column to be affected Yes json, jsonb operations A list of operations that contains editing delete and set Yes - \u221f operation Specifies the operation type: set or delete Yes - \u221f path The path to an object to be modified. See path syntax below. Yes - \u221f value A value to be assigned to the provided path No - \u221f value_template A Golang template to be assigned to the provided path. See the list of template functions below. No - \u221f error_not_exist Throws an error if the key does not exist by the provided path. Disabled by default. false No -"},{"location":"built_in_transformers/advanced_transformers/json/#description","title":"Description","text":"

The Json transformer applies a sequence of changing operations (set and/or delete) to a JSON document. The value can be static or dynamic. For the set operation type, a static value is provided in the value parameter, while a dynamic value is provided in the value_template parameter, taking the data received after template execution as a result. Both the value and value_template parameters are mandatory for the set operation.

"},{"location":"built_in_transformers/advanced_transformers/json/#path-syntax","title":"Path syntax","text":"

The Json transformer is based on tidwall/sjson and supports the same path syntax. See their documentation for syntax rules.

"},{"location":"built_in_transformers/advanced_transformers/json/#template-functions","title":"Template functions","text":"Function Description Signature .GetPath Returns the current path to which the operation is being applied .GetPath() (path string) .GetOriginalValue Returns the original value to which the current operation path is pointing. If the value at the specified path does not exist, it returns nil. .GetOriginalValue() (value any) .OriginalValueExists Returns a boolean value indicating whether the specified path exists or not. .OriginalValueExists() (exists bool) .GetColumnValue Returns an encoded into Golang type value for a specified column or throws an error. A value can be any of int, float, time, string, bool, or slice or map. .GetColumnValue(name string) (value any, err error) .GetRawColumnValue Returns a raw value for a specified column as a string or throws an error .GetRawColumnValue(name string) (value string, err error) .EncodeValueByColumn Encodes a value of any type into its raw string representation using the specified column name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValueByColumn(name string, value any) (res any, err error) .DecodeValueByColumn Decodes a value from its raw string representation to a Golang type using the specified column name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByColumn(name string, value any) (res any, err error) .EncodeValueByType Encodes a value of any type into its string representation using the specified type name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValueByType(name string, value any) (res any, err error) .DecodeValueByType Decodes a value from its raw string representation to a Golang type using the specified type name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByType(name string, value any) (res any, err error)"},{"location":"built_in_transformers/advanced_transformers/json/#example-changing-json-document","title":"Example: Changing JSON document","text":"Json transformer example
- schema: \"bookings\"\n  name: \"aircrafts_data\"\n  transformers:\n    - name: \"Json\"\n      params:\n        column: \"model\"\n        operations:\n          - operation: \"set\"\n            path: \"en\"\n            value: \"Boeing 777-300-2023\"\n          - operation: \"set\"\n            path: \"seats\"\n            error_not_exist: True\n            value_template: \"{{ randomInt 100 400 }}\"\n          - operation: \"set\"\n            path: \"details.preperties.1\"\n            value: {\"name\": \"somename\", \"description\": null}\n          - operation: \"delete\"\n            path: \"values.:2\"\n
"},{"location":"built_in_transformers/advanced_transformers/template/","title":"Template","text":"

Execute a Go template and automatically apply the result to a specified column.

"},{"location":"built_in_transformers/advanced_transformers/template/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes any template A Go template string Yes - validate Validates the template result using the PostgreSQL driver decoding procedure. Throws an error if a custom type does not have an encode-decoder implementation. false No -"},{"location":"built_in_transformers/advanced_transformers/template/#description","title":"Description","text":"

The Template transformer executes Go templates and automatically applies the template result to a specified column. Go template system is designed to be extensible, enabling developers to access data objects and incorporate custom functions programmatically. For more information, you can refer to the official Go Template documentation.

With the Template transformer, you can implement complicated transformation logic using basic or custom template functions. Below you can get familiar with the basic template functions for the Template transformer. For more information about available custom template functions, see Custom functions.

Warning

Pay attention to the whitespaces in templates. Use dash-wrapped - brackets {{- -}} for trimming the spaces. For example, the value \"2023-12-19\" is not the same as \" 2023-12-19 \" and it may throw an error when restoring.

"},{"location":"built_in_transformers/advanced_transformers/template/#template-functions","title":"Template functions","text":"Function Description Signature .GetColumnType Returns a string with the column type. .GetColumnType(name string) (typeName string, err error) .GetValue Returns the column value for column assigned in the column parameter, encoded by the PostgreSQL driver into any type along with any associated error. Supported types include int, float, time, string, bool, as well as slice or map of any type. .GetValue() (value any, err error) .GetRawValue Returns a raw value as a string for column assigned in the column parameter. .GetRawColumnValue(name string) (value string, err error) .GetColumnValue Returns an encoded value for a specified column or throws an error. A value can be any of int, float, time, string, bool, or slice or map. .GetColumnValue(name string) (value any, err error) .GetRawColumnValue Returns a raw value for a specified column as a string or throws an error .GetRawColumnValue(name string) (value string, err error) .EncodeValue Encodes a value of any type into its string representation using the type assigned to the table column specified in the column parameter. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValue(value any) (res any, err error) .DecodeValue Decodes a value from its raw string representation to a Golang type using the data type assigned to the table column specified in the column parameter. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByColumn(value any) (res any, err error) .EncodeValueByColumn Encodes a value of any type into its raw string representation using the specified column name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValueByColumn(name string, value any) (res any, err error) .DecodeValueByColumn Decodes a value from its raw string representation to a Golang type using the specified column name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByColumn(name string, value any) (res any, err error) .EncodeValueByType Encodes a value of any type into its string representation using the specified type name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValueByType(name string, value any) (res any, err error) .DecodeValueByType Decodes a value from its raw string representation to a Golang type using the specified type name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByType(name string, value any) (res any, err error)"},{"location":"built_in_transformers/advanced_transformers/template/#example-update-the-firstname-column","title":"Example: Update the firstname column","text":"

Below you can see the table structure:

"},{"location":"built_in_transformers/advanced_transformers/template/#change-rule","title":"Change rule","text":"

The goal is to modify the firstname column based on the following conditions:

  • If the current value of the firstname column is equal to Terri, replace it with Mary.
  • For all other cases, generate a random name and append Jr.
"},{"location":"built_in_transformers/advanced_transformers/template/#using-a-template-function","title":"Using a template function","text":"

To generate random names, you can use the fakerFirstName template function, which is designed to create synthetic names.

Template transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformation:\n    - name: \"Template\"\n      params:\n        column: \"firstname\"\n        template: >\n          {{- if eq .GetValue \"Terri\" -}}\n            Mary\n          {{- else -}}\n            {{- fakerFirstName -}} Jr\n          {{- end -}}\n\n        validate: true\n

Expected result:

Value = TerryValue != Terri column name original value transformed firstname Terri Mary column name original value transformed firstname Ken Jr Mike"},{"location":"built_in_transformers/advanced_transformers/template_record/","title":"TemplateRecord","text":"

Modify records using a Go template and apply changes by using the PostgreSQL driver functions. This transformer provides a way to implement custom transformation logic.

"},{"location":"built_in_transformers/advanced_transformers/template_record/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types columns A list of columns to be affected by the template. The list of columns will be checked for constraint violations. No any template A Go template string Yes - validate Validate the template result via PostgreSQL driver decoding procedure. Throws an error if a custom type does not have an encode-decoder implementation. false No -"},{"location":"built_in_transformers/advanced_transformers/template_record/#description","title":"Description","text":"

TemplateRecord uses Go templates to change data. However, while the Template transformer operates with a single column and automatically applies results, the TemplateRecord transformer can make changes to a set of columns in the string, and using driver functions .SetValue or .SetRawValue is mandatory to do that.

With the TemplateRecord transformer, you can implement complicated transformation logic using basic or custom template functions. Below you can get familiar with the basic template functions for the TemplateRecord transformer. For more information about available custom template functions, see Custom functions.

"},{"location":"built_in_transformers/advanced_transformers/template_record/#template-functions","title":"Template functions","text":"Function Description Signature .GetColumnType Returns a string with the column type. .GetColumnType(name string) (typeName string, err error) .GetColumnValue Returns an encoded value for a specified column or throws an error. A value can be any of int, float, time, string, bool, or slice or map. .GetColumnValue(name string) (value any, err error) .GetRawColumnValue Returns a raw value for a specified column as a string or throws an error .GetRawColumnValue(name string) (value string, err error) .SetColumnValue Sets a new value of a specific data type to the column. The value assigned must be compatible with the PostgreSQL data type of the column. For example, it is allowed to assign an int value to an INTEGER column, but you cannot assign a float value to a timestamptz column. SetColumnValue(name string, v any) (bool, error) .SetRawColumnValue Sets a new raw value for a column, inheriting the column's existing data type, without performing data type validation. This can lead to errors when restoring the dump if the assigned value is not compatible with the column type. To ensure compatibility, consider using the .DecodeValueByColumn function followed by .SetColumnValue, for example, {{ \"13\" \\| .DecodeValueByColumn \"items_amount\" \\| .SetColumnValue \"items_amount\" }}. .SetRawColumnValue(name string, value any) (err error) .EncodeValueByColumn Encodes a value of any type into its raw string representation using the specified column name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValueByColumn(name string, value any) (res any, err error) .DecodeValueByColumn Decodes a value from its raw string representation to a Golang type using the specified column name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByColumn(name string, value any) (res any, err error) .EncodeValueByType Encodes a value of any type into its string representation using the specified type name. Encoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .EncodeValueByType(name string, value any) (res any, err error) .DecodeValueByType Decodes a value from its raw string representation to a Golang type using the specified type name. Decoding is performed through the PostgreSQL driver. Throws an error if types are incompatible. .DecodeValueByType(name string, value any) (res any, err error)"},{"location":"built_in_transformers/advanced_transformers/template_record/#example-generate-a-random-created_at-and-updated_at-dates","title":"Example: Generate a random created_at and updated_at dates","text":"

Below you can see the table structure:

The goal is to modify the \"created_at\" and \"updated_at\" columns based on the following rules:

  • Do not change the value if the created_at is Null.
  • If the created_at is not Null, generate the current time and use it as the minimum threshold for randomly generating the updated_at value.
  • Assign all generated values using the .SetColumnValue function.
Template transformer example
- name: \"TemplateRecord\"\n  params:\n    columns:\n      - \"created_at\"\n      - \"updated_at\"\n    template: >\n      {{ $val := .GetColumnValue \"created_at\" }}\n      {{ if isNotNull $val }}\n          {{ $createdAtValue := now }}\n          {{ $maxUpdatedDate := date_modify \"24h\" $createdAtValue }}\n          {{ $updatedAtValue := randomDate $createdAtValue $maxUpdatedDate }}\n          {{ .SetColumnValue \"created_at\" $createdAtValue }}\n          {{ .SetColumnValue \"updated_at\" $updatedAtValue }}\n      {{ end }}\n    validate: true\n

Expected result:

column name original value transformed created_at 2021-01-20 07:01:00.513325+00 2023-12-17 19:37:29.910054Z updated_at 2021-08-09 21:27:00.513325+00 2023-12-18 10:05:25.828498Z"},{"location":"built_in_transformers/advanced_transformers/custom_functions/","title":"Template custom functions","text":"

Within Greenmask, custom functions play a crucial role, providing a wide array of options for implementing diverse logic. Under the hood, the custom functions are based on the sprig Go's template functions. Greenmask enhances this capability by introducing additional functions and transformation functions. These extensions mirror the logic found in the standard transformers but offer you the flexibility to implement intricate and comprehensive logic tailored to your specific needs.

Currently, you can use template custom functions for the advanced transformers:

  • Json
  • Template
  • TemplateRecord

and for the Transformation condition feature as well.

Custom functions are arbitrarily divided into 2 groups:

  • Core functions \u2014 custom functions that vary in purpose and include PostgreSQL driver, JSON output, testing, and transformation functions.
  • Faker functions \u2014 custom function of a faker type which generate synthetic data.
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/","title":"Core functions","text":"

Below you can find custom core functions which are divided into categories based on the transformation purpose.

"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#postgresql-driver-functions","title":"PostgreSQL driver functions","text":"Function Description null Returns the NULL value that can be used for the driver encoding-decoding operations isNull Returns true if the checked value is NULL isNotNull Returns true if the checked value is not NULL sqlCoalesce Works as a standard SQL coalesce function. It allows you to choose the first non-NULL argument from the list."},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#json-output-function","title":"JSON output function","text":"Function Description jsonExists Checks if the path value exists in JSON. Returns true if the path exists. mustJsonGet Gets the JSON attribute value by path and throws an error if the path does not exist mustJsonGetRaw Gets the JSON attribute raw value by path and throws an error if the path does not exist jsonGet Gets the JSON attribute value by path and returns nil if the path does not exist jsonGetRaw Gets the JSON attribute raw value by path and returns nil if the path does not exist jsonSet Sets the value for the JSON document by path jsonSetRaw Sets the raw value for the JSON document by path jsonDelete Deletes an attribute from the JSON document by path jsonValidate Validates the JSON document syntax and throws an error if there are any issues jsonIsValid Checks the JSON document for validity and returns true if it is valid toJsonRawValue Casts any type of value to the raw JSON value"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#testing-functions","title":"Testing functions","text":"Function Description isInt Checks if the value of an integer type isFloat Checks if the value of a float type isNil Checks if the value is nil isString Checks if the value of a string type isMap Checks if the value of a map type isSlice Checks if the value of a slice type isBool Checks if the value of a boolean type"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#transformation-and-generators","title":"Transformation and generators","text":""},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#masking","title":"masking","text":"

Replaces characters with asterisk * symbols depending on the provided masking rule. If the value is NULL, it is kept unchanged. This function is based on ggwhite/go-masker.

Masking rulesSignatureParametersReturn values Rule Description Example input Example output default Returns the sequence of * symbols of the same length test1234 ******** name Masks the second and the third letters ABCD A**D password Always returns a sequence of * address Keeps first 6 letters, masks the rest Larnaca, makarios st Larnac************* email Keeps a domain and the first 3 letters, masks the rest ggw.chang@gmail.com ggw****@gmail.com mobile Masks 3 digits starting from the 4th digit 0987654321 0987***321 telephone Removes (, ), , - symbols, masks last 4 digits of a telephone number, and formats it to (??)????-???? 0227993078 (02)2799-**** id Masks last 4 digits of an ID A123456789 A12345**** credit_card Masks 6 digits starting from the 7th digit 1234567890123456 123456******3456 url Masks the password part of the URL (if applicable) http://admin:mysecretpassword@localhost:1234/uri http://admin:xxxxx@localhost:1234/uri

masking(dataType string, value string) (res string, err error)

  • dataType \u2014 one of the masking rules (see previous tab)
  • value \u2014 the original string value
  • res \u2014 a masked string
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#truncatedate","title":"truncateDate","text":"

Truncates datetime up to the provided part.

SignatureParametersReturn values

truncateDate(part string, original time.Time) (res time.Time, err error)

  • part \u2014 the truncation part. Must be one of nano, second, minute, hour, day, month, or year
  • original \u2014 the original datetime value
  • res \u2014 a truncated datetime
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#noisedatepginterval","title":"noiseDatePgInterval","text":"

Adds or subtracts a random duration in the provided interval to or from the original date value.

SignatureParametersReturn values

noiseDate(interval string, original time.Time) (res time.Time, err error)

  • interval \u2014 the maximum value of ratio that is added to the original value. The format is the same as in the PostgreSQL interval format.
  • original \u2014 the original time value
  • res \u2014 a noised date
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#noisefloat","title":"noiseFloat","text":"

Adds or subtracts a random fraction to or from the original float value. Multiplies the original float value by a provided random value that is not higher than the ratio parameter and adds it to the original value with the option to specify the decimal via the decimal parameter.

SignatureParametersReturn values

noiseFloat(ratio float, decimal int, value float) (res float64, err error)

  • ratio \u2014 the maximum multiplier value in the interval (0:1). The value will be randomly generated up to ratio, multiplied by the original value, and the result will be added to the original value.
  • decimal \u2014 the decimal of the resulted value
  • value \u2014 the original value
  • res \u2014 a noised float value
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#noiseint","title":"noiseInt","text":"

Adds or subtracts a random fraction to or from the original integer value. Multiplies the original integer value by a provided random value that is not higher than the ratio parameter and adds it to the original value.

SignatureParametersReturn values

noiseInt(ratio float, value float) (res int, err error)

  • ratio \u2014 the max multiplier value in the interval (0:1). The value will be generated randomly up to ratio, multiplied by the original value, and the result will be added to the original value.
  • value \u2014 the original value
  • res \u2014 a noised integer value
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#randombool","title":"randomBool","text":"

Generates a random boolean value.

"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#randomdate","title":"randomDate","text":"

Generates a random date within the provided interval.

SignatureParametersReturn values

randomDate(min time.Time, max time.Time) (res time.Time, err error)

  • min \u2014 the minimum random value threshold
  • max \u2014 the maximum random value threshold
  • res \u2014 a randomly generated date value
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#randomfloat","title":"randomFloat","text":"

Generates a random float value within the provided interval.

SignatureParametersReturn values

randomFloat(min any, max any, decimal int) (res float, err error)

  • min \u2014 the minimum random value threshold
  • max \u2014 the maximum random value threshold
  • decimal \u2014 the decimal of the resulted value
  • res \u2014 a randomly generated float value
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#randomint","title":"randomInt","text":"

Generates a random integer value within the provided interval.

SignatureParametersReturn values

randomInt(min int, max int) (res int, err error)

  • min \u2014 the minimum random value threshold
  • max \u2014 the maximum random value threshold
  • res \u2014 a randomly generated int value
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#randomstring","title":"randomString","text":"

Generates a random string using the provided characters within the specified length range.

SignatureParametersReturn values

randomString(minLength int, maxLength int, symbols string) (res string, err error)

  • minLength \u2014 the minimum string length
  • maxLength \u2014 the maximum string length
  • symbols \u2014 a string with a set of symbols which can be used. The default value is abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890
  • res \u2014 a randomly generated string value
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#roundfloat","title":"roundFloat","text":"

Rounds a float value up to provided decimal.

SignatureParametersReturn values

roundFloat(decimal int, original float) (res float, err error)

  • decimal \u2014 the decimal of the value
  • original \u2014 the original float value
  • res \u2014 a rounded float value
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/core_functions/#tsmodify","title":"tsModify","text":"

Modify original time value by adding or subtracting the provided interval. The interval is a string in the format of the PostgreSQL interval.

SignatureParametersReturn values

tsModify(interval string, val time.Time) (time.Time, error)

  • interval \u2014 the maximum value of ratio that is added to the original value. The format is the same as in the PostgreSQL interval format.
  • original \u2014 the original time value
  • res \u2014 a modified date
  • err \u2014 an error if there is an issue
"},{"location":"built_in_transformers/advanced_transformers/custom_functions/faker_function/","title":"Faker functions","text":"

Greenmask uses go-faker/faker under the hood for generating of synthetic data.

"},{"location":"built_in_transformers/advanced_transformers/custom_functions/faker_function/#faker-functions-address","title":"Faker functions: Address","text":"Function Description Signature fakerRealAddress Generates a random real-world address that includes: city, state, postal code, latitude, and longitude fakerRealAddress() (res ReadAddress) fakerLatitude Generates random fake latitude fakerLatitude() (res float64) fakerLongitude Generates random fake longitude fakerLongitude() (res float64)"},{"location":"built_in_transformers/advanced_transformers/custom_functions/faker_function/#faker-functions-datetime","title":"Faker functions: Datetime","text":"Function Description Signature fakerUnixTime Generates random Unix time in seconds fakerLongitude() (res int64) fakerDate Generates random date with the pattern of YYYY-MM-DD fakerDate() (res string) fakerTimeString Generates random time fakerTimeString() (res string) fakerMonthName Generates a random month fakerMonthName() (res string) fakerYearString Generates a random year fakerYearString() (res string) fakerDayOfWeek Generates a random day of a week fakerDayOfWeek() (res string) fakerDayOfMonth Generates a random day of a month fakerDayOfMonth() (res string) fakerTimestamp Generates a random timestamp with the pattern of YYYY-MM-DD HH:MM:SS fakerTimestamp() (res string) fakerCentury Generates a random century fakerCentury() (res string) fakerTimezone Generates a random timezone name fakerTimezone() (res string) fakerTimeperiod Generates a random time period with the patter of either AM or PM fakerTimeperiod() (res string)"},{"location":"built_in_transformers/advanced_transformers/custom_functions/faker_function/#faker-functions-internet","title":"Faker functions: Internet","text":"Function Description Signature fakerEmail Generates a random email fakerEmail() (res string) fakerMacAddress Generates a random MAC address fakerMacAddress() (res string) fakerDomainName Generates a random domain name fakerDomainName() (res string) fakerURL Generates a random URL with the pattern of https://www.domainname.some/somepath fakerURL() (res string) fakerUsername Generates a random username fakerUsername() (res string) fakerIPv4 Generates a random IPv4 address fakerIPv4() (res string) fakerIPv6 Generates a random IPv6 address fakerIPv6() (res string) fakerPassword Generates a random password fakerPassword() (res string)"},{"location":"built_in_transformers/advanced_transformers/custom_functions/faker_function/#faker-functions-words-and-sentences","title":"Faker functions: words and sentences","text":"Function Description Signature fakerWord Generates a random word fakerWord() (res string) fakerSentence Generates a random sentence fakerSentence() (res string) fakerParagraph Generates a random sequence of sentences as a paragraph fakerParagraph() (res string)"},{"location":"built_in_transformers/advanced_transformers/custom_functions/faker_function/#faker-functions-payment","title":"Faker functions: Payment","text":"Function Description Signature fakerCCType Generates a random credit card type, e.g. VISA, MasterCard, etc. fakerCCType() (res string) fakerCCNumber Generates a random credit card number fakerCCNumber() (res string) fakerCurrency Generates a random currency name fakerCurrency() (res string) fakerAmountWithCurrency Generates random amount preceded with random currency fakerAmountWithCurrency() (res string)"},{"location":"built_in_transformers/advanced_transformers/custom_functions/faker_function/#faker-functions-person","title":"Faker functions: Person","text":"Function Description Signature fakerTitleMale Generates a random male title from the predefined list fakerTitleMale() (res string) fakerTitleFemale Generates a random female title from the predefined list fakerTitleFemale() (res string) fakerFirstName Generates a random first name fakerFirstName() (res string) fakerFirstNameMale Generates a random male first name fakerFirstNameMale() (res string) fakerFirstNameFemale Generates a random female first name fakerFirstNameFemale() (res string) fakerFirstLastName Generates a random last name fakerFirstLastName() (res string) fakerName Generates a random full name preceded with a title fakerName() (res string)"},{"location":"built_in_transformers/advanced_transformers/custom_functions/faker_function/#faker-functions-phone","title":"Faker functions: Phone","text":"Function Description Signature fakerPhoneNumber Generates a random phone number fakerPhoneNumber() (res string) fakerTollFreePhoneNumber Generates a random phone number with the pattern of (123) 456-7890 fakerTollFreePhoneNumber() (res string) fakerE164PhoneNumber Generates a random phone number with the pattern of +12345678900 fakerE164PhoneNumber() (res string)"},{"location":"built_in_transformers/advanced_transformers/custom_functions/faker_function/#faker-functions-uuid","title":"Faker functions: UUID","text":"Function Description Signature fakerUUIDHyphenated Generates a random unique user ID separated by hyphens fakerUUID() (res string) fakerUUIDDigit Generates a random unique user ID in the HEX format fakerUUIDDigit() (res string)"},{"location":"built_in_transformers/standard_transformers/","title":"Standard transformers","text":"

Standard transformers are ready-to-use methods that require no customization and perform with just as little as parameters input. Below you can find an index of all standard transformers currently available in Greenmask.

  1. Cmd \u2014 transforms data via external program using stdin and stdout interaction.
  2. Dict \u2014 replaces values matched by dictionary keys.
  3. Hash \u2014 generates a hash of the text value.
  4. Masking \u2014 masks a value using one of the masking behaviors depending on your domain.
  5. NoiseDate \u2014 randomly adds or subtracts a duration within the provided ratio interval to the original date value.
  6. NoiseFloat \u2014 adds or subtracts a random fraction to the original float value.terval to the original date value.
  7. NoiseNumeric \u2014 adds or subtracts a random fraction to the original numeric value.
  8. NoiseInt \u2014 adds or subtracts a random fraction to the original integer value.
  9. RandomBool \u2014 generates random boolean values.
  10. RandomChoice \u2014 replaces values randomly chosen from a provided list.
  11. RandomDate \u2014 generates a random date in a specified interval.
  12. RandomFloat \u2014 generates a random float within the provided interval.
  13. RandomInt \u2014 generates a random integer within the provided interval.
  14. RandomString \u2014 generates a random string using the provided characters within the specified length range.
  15. RandomUuid \u2014 generates a random unique user ID.
  16. RandomLatitude \u2014 generates a random latitude value.
  17. RandomLongitude \u2014 generates a random longitude value.
  18. RandomUnixTimestamp \u2014 generates a random Unix timestamp.
  19. RandomDayOfWeek \u2014 generates a random day of the week.
  20. RandomDayOfMonth \u2014 generates a random day of the month.
  21. RandomMonthName \u2014 generates the name of a random month.
  22. RandomYearString \u2014 generates a random year as a string.
  23. RandomCentury \u2014 generates a random century.
  24. RandomTimezone \u2014 generates a random timezone.
  25. RandomEmail \u2014 generates a random email address.
  26. RandomUsername \u2014 generates a random username.
  27. RandomPassword \u2014 generates a random password.
  28. RandomDomainName \u2014 generates a random domain name.
  29. RandomURL \u2014 generates a random URL.
  30. RandomMac \u2014 generates a random MAC addresses.
  31. RandomIP \u2014 generates a random IPv4 or IPv6 addresses.
  32. RandomWord \u2014 generates a random word.
  33. RandomSentence \u2014 generates a random sentence.
  34. RandomParagraph \u2014 generates a random paragraph.
  35. RandomCCType \u2014 generates a random credit card type.
  36. RandomCCNumber \u2014 generates a random credit card number.
  37. RandomCurrency \u2014 generates a random currency code.
  38. RandomAmountWithCurrency \u2014 generates a random monetary amount with currency.
  39. RandomPerson \u2014 generates a random person data (first name, last name, etc.)
  40. RandomPhoneNumber \u2014 generates a random phone number.
  41. RandomTollFreePhoneNumber \u2014 generates a random toll-free phone number.
  42. RandomE164PhoneNumber \u2014 generates a random phone number in E.164 format.
  43. RealAddress \u2014 generates a real address.
  44. RegexpReplace \u2014 replaces a string using a regular expression.
  45. Replace \u2014 replaces an original value by the provided one.
  46. SetNull \u2014 sets NULL value to the column.
"},{"location":"built_in_transformers/standard_transformers/cmd/","title":"Cmd","text":"

Transform data via external program using stdin and stdout interaction.

"},{"location":"built_in_transformers/standard_transformers/cmd/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types columns A list of column names to be affected. If empty, the entire tuple is used. Read about the structure further. Yes Any executable The path to the executable parameter file Yes - args A list of parameters for the executable No - driver The row driver with parameters that is used for interacting with cmd. See details below. {\"name\": \"csv\"} No - validate Performs a decoding operation using the PostgreSQL driver for data received from the command to ensure the data format is correct false No - timeout Timeout for sending and receiving data from the external command 2s No - expected_exit_code The expected exit code on SIGTERM signal. If the exit code is unexpected, the transformation exits with an error. 0 No - skip_on_behaviour Skips transformation call if one of the provided columns has a null value (any) or each of the provided columns has null values (all). This option works together with the skip_on_null_input parameter on columns. Possible values: all, any. all No -

Warning

The parameter validate_output=true may cause an error if the type does not have a PostgreSQL driver decoder implementation. Most of the types, such as int, float, text, varchar, date, timestamp, etc., have encoders and decoders, as well as inherited types like domain types based on them.

"},{"location":"built_in_transformers/standard_transformers/cmd/#description","title":"Description","text":"

The Cmd transformer allows you to send original data to an external program via stdin and receive transformed data from stdout. It supports various interaction formats such as json, csv, or plain text for one-column transformations. The interaction is performed line by line, so at the end of each sent data, a new line symbol \\n must be included.

"},{"location":"built_in_transformers/standard_transformers/cmd/#types-of-interaction-modes","title":"Types of interaction modes","text":""},{"location":"built_in_transformers/standard_transformers/cmd/#text","title":"text","text":"

Textual driver that is used only for one column transformation, thus you cannot provide here more than one column. The value encodes into string laterally. For example, 2023-01-03 01:00:00.0+03.

"},{"location":"built_in_transformers/standard_transformers/cmd/#json","title":"json","text":"

JSON line driver. It has two formats that can be passed through driver.json_data_format: [text|bytes]. Use the bytes format for binary datatypes. Use the text format for non-binary datatypes and for those that can be represented as string literals. The default json_data_format is text.

Text format with indexesBytes format with indexes 
{\n  \"column1\": {\n    \"d\": \"some_value1\",\n    \"n\": false,\n  },\n  \"column2\": {\n    \"d\": \"some_value2\",\n    \"n\": false,\n  }\n}\n
{\n  \"column1\": {\n    \"d\": \"aGVsbG8gd29ybHNeODcxMjE5MCUlJSUlJQ==\",\n    \"n\": false,\n  },\n  \"column2\": {\n    \"d\": \"aGVsbG8gd29ybHNeODcxMjE5MCUlJSUlJQ==\",\n    \"n\": false,\n  }\n}\n

where:

  • Each line is a JSON line with a map of attribute numbers to their values
  • d \u2014 the raw data represented as base64 encoding for the bytes format or Unicode text for the text format. The base64 encoding is needed because data can be binary.
  • n \u2014 indicates if NULL is present
"},{"location":"built_in_transformers/standard_transformers/cmd/#csv","title":"csv","text":"

CSV driver (comma-separated). The number of attributes is the same as the number of table columns, but the columns that were not mentioned in the columns list are empty. The NULL value is represented as \\N. Each attribute is escaped by a quote (\"). For example, if the transformed table has attributes id, title, and created_at, and only id and created_at require transformation, then the CSV line will look as follows:

csv line example
\"123\",\"\",\"2023-01-03 01:00:00.0+03\"\n
"},{"location":"built_in_transformers/standard_transformers/cmd/#column-object-attributes","title":"Column object attributes","text":"
  • name \u2014 the name of the column. This value is required. Depending on the attributes that follows further, this column may be used just as a value and is not affected in any way.
  • not_affected \u2014 indicates whether the column is affected in the transformation. This attribute is required for the validation procedure when Greenmask is called with greenmask dump --validate. Setting not_affected=true can be helpful when the command transformer transforms data depending on the value of another column. For example, if you want to generate an updated_at column value depending on the created_at column value, you can set created_at to not_affected=true. The default value is false.
  • skip_original_data \u2014 indicates whether the original data is required for the transformer. This attribute can be helpful for decreasing the interaction time. One use case is when the command works as a generator and returns the value without relying on the original data. The default value is false.
  • skip_on_null_input \u2014 specifies whether to skip transformation when the original value is null. This attribute works in conjunction with the skip_on_behaviour parameter. For example, if you have two affected columns with skip_on_null_input=true and one column is null, then, if skip_on_behaviour=any, the transformation will be skipped, or, if skip_on_behaviour=and, the transformation will be performed. The default is false.
"},{"location":"built_in_transformers/standard_transformers/cmd/#example-apply-transformation-performed-by-external-command-in-text-format","title":"Example: Apply transformation performed by external command in TEXT format","text":"

In the following example, jobtitle columns is transformed via external command transformer.

External transformer in python example
#!/usr/bin/env python3\nimport signal\nimport sys\n\nsignal.signal(signal.SIGTERM, lambda sig, frame: exit(0))\n\n\n# If we want to implement a simple generator, we need read the line from stdin and write any result to stdout\nfor _ in sys.stdin:\n    # Writing the result to stdout with new line and flushing the buffer\n    sys.stdout.write(\"New Job Title\")\n    sys.stdout.write(\"\\n\")\n    sys.stdout.flush()\n
Cmd transformer config example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"Cmd\"\n      params:\n        driver:\n          name: \"text\"\n        expected_exit_code: -1\n        skip_on_null_input: true\n        validate: true\n        skip_on_behaviour: \"any\"\n        timeout: 60s\n        executable: \"/var/lib/playground/test.py\"\n        columns:\n          - name: \"jobtitle\"\n            skip_original_data: true\n            skip_on_null_input: true \n
"},{"location":"built_in_transformers/standard_transformers/cmd/#example-apply-transformation-performed-by-external-command-in-json-format","title":"Example: Apply transformation performed by external command in JSON format","text":"

In the following example, jobtitle and loginid columns are transformed via external command transformer.

External transformer in python example
#!/usr/bin/env python3\nimport json\nimport signal\nimport sys\n\nsignal.signal(signal.SIGTERM, lambda sig, frame: exit(0))\n\nfor line in sys.stdin:\n    res = json.loads(line)\n    # Setting dummy values\n    res[\"jobtitle\"] = {\"d\": \"New Job Title\", \"n\": False}\n    res[\"loginid\"][\"d\"] = \"123\"\n\n    # Writing the result to stdout with new line and flushing the buffer\n    sys.stdout.write(json.dumps(res))\n    sys.stdout.write(\"\\n\")\n    sys.stdout.flush()\n
Cmd transformer config example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"Cmd\"\n      params:\n        driver:\n          name: \"json\" # (1)\n          json_data_format: \"text\" # (4)\n        expected_exit_code: -1\n        skip_on_null_input: true\n        validate: true\n        skip_on_behaviour: \"any\" # (2)\n        timeout: 60s\n        executable: \"/var/lib/playground/test.py\"\n        columns:\n          - name: \"jobtitle\"\n            skip_original_data: true\n            skip_on_null_input: true # (3)\n          - name: \"loginid\"\n            skip_original_data: false # (5)\n            skip_on_null_input: true # (3)\n

{ .annotate }

  1. Validate the received data via decode procedure using the PostgreSQL driver. Note that this may cause an error if the type is not supported in the PostgreSQL driver.
  2. Skip transformation (keep the values) if one of the affected columns (not_affected=false) has a null value.
  3. If a column has a null value, then skip it. This works in conjunction with skip_on_behaviour. Since it has the value any, if one of the columns (jobtitle or loginid) has a null value, then skip the transformation call.
  4. The format of JSON can be either text or bytes. The default value is text.
  5. The skip_original_data attribute is set to true the date will not be transfered to the command. This column will contain the empty original data
"},{"location":"built_in_transformers/standard_transformers/dict/","title":"Dict","text":"

Replace values matched by dictionary keys.

"},{"location":"built_in_transformers/standard_transformers/dict/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes any values Value replace mapping as in: {\"string\": \"string\"}. The string with value \"\\N\" is considered NULL. No - default Shown if no value has been matched with dict. The string with value \"\\N\" is considered NULL. By default is empty. No - fail_not_matched When no value is matched with the dict, fails the replacement process if set to true, or keeps the current value, if set to false. true No - validate Performs the encode-decode procedure using column type to ensure that values have correct type true No -"},{"location":"built_in_transformers/standard_transformers/dict/#description","title":"Description","text":"

The Dict transformer uses a user-provided key-value dictionary to replace values based on matches specified in the values parameter mapping. These provided values must align with the PostgreSQL type format. To validate the values format before application, you can utilize the validate parameter, triggering a decoding procedure via the PostgreSQL driver.

If there are no matches by key, an error will be raised according to a default fail_not_matched: true parameter. You can change this behaviour by providing the default parameter, value from which will be shown in case of a missing match.

In certain cases where the driver type does not support the validation operation, an error may occur. For setting or matching a NULL value, use a string with the \\N sequence.

"},{"location":"built_in_transformers/standard_transformers/dict/#example-replace-marital-status","title":"Example: Replace marital status","text":"

The following example replaces marital status from S to M or from M to S and raises an error if there is no match:

Dict transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"Dict\"\n      params:\n        column: \"maritalstatus\"\n        values:\n          \"S\": \"M\"\n          \"M\": \"S\"\n        validate: true\n        fail_not_matched: true\n

Result

ColumnOriginalValueTransformedValue maritalstatusSM"},{"location":"built_in_transformers/standard_transformers/hash/","title":"Hash","text":"

Generate a hash of the text value using the Scrypt hash function under the hood. NULL values are kept.

"},{"location":"built_in_transformers/standard_transformers/hash/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar salt Hex encoded salt string. This value may be provided via environment variable GREENMASK_GLOBAL_SALT Yes text, varchar function Hash algorithm to anonymize data. Can be any of md5, sha1, sha256, sha512, sha3-224, sha3-254, sha3-384, sha3-512. sha1 No - max_length Indicates whether to truncate the hash tail and specifies at what length. Can be any integer number, where 0 means \"no truncation\". 0 No -"},{"location":"built_in_transformers/standard_transformers/hash/#example-generate-hash-from-job-title","title":"Example: Generate hash from job title","text":"

The following example generates a hash from the jobtitle into sha1 and truncates the results after the 10th character.

We can set the salt via the environment variable GREENMASK_GLOBAL_SALT:

export GREENMASK_GLOBAL_SALT=\"12343567baaa\"\n
Hash transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"Hash\"\n      params:\n        column: \"jobtitle\"\n        function: \"sha1\"\n        max_length: 10\n
Expected result
| column name | original value                   | transformed |\n|-------------|----------------------------------|-------------|\n| jobtitle    | Research and Development Manager | 3a456da5c5  |\n
"},{"location":"built_in_transformers/standard_transformers/masking/","title":"Masking","text":"

Mask a value using one of the masking rules depending on your domain. NULL values are kept.

"},{"location":"built_in_transformers/standard_transformers/masking/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar type Data type of attribute (default, password, name, addr, email, mobile, tel, id, credit, url) default No -"},{"location":"built_in_transformers/standard_transformers/masking/#description","title":"Description","text":"

The Masking transformer replaces characters with asterisk * symbols depending on the provided data type. If the value is NULL, it is kept unchanged. It is based on ggwhite/go-masker and supports the following masking rules:

Type Description default Returns * symbols with the same length, e.g. input: test1234 output: ******** name Masks the second letter the third letter in a word, e. g. input: ABCD output: A**D password Always returns ************ address Keeps first 6 letters, masks the rest, e. g. input: Larnaca, makarios st output: Larnac************* email Keeps a domain and the first 3 letters, masks the rest, e. g. input: ggw.chang@gmail.com output: ggw****@gmail.com mobile Masks 3 digits starting from the 4th digit, e. g. input: 0987654321 output: 0987***321 telephone Removes (, ), , - chart, and masks last 4 digits of telephone number, then formats it to (??)????-????, e. g. input: 0227993078 output: (02)2799-**** id Masks last 4 digits of ID number, e. g. input: A123456789 output: A12345**** credit_cart Masks 6 digits starting from the 7th digit, e. g. input 1234567890123456 output 123456******3456 url Masks the password part of the URL, if applicable, e. g. http://admin:mysecretpassword@localhost:1234/uri output: http://admin:xxxxx@localhost:1234/uri"},{"location":"built_in_transformers/standard_transformers/masking/#example-masking-employee-national-id-number","title":"Example: Masking employee national ID number","text":"

In the following example, the national ID number of an employee is masked.

Masking transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"Masking\"\n      params:\n        column: \"nationalidnumber\"\n        type: \"id\"\n
Expected result
| column name      | original value | transformed |\n|------------------|----------------|-------------|\n| nationalidnumber | 295847284      | 295847****  |\n
"},{"location":"built_in_transformers/standard_transformers/noise_date/","title":"NoiseDate","text":"

Randomly add or subtract a duration within the provided ratio interval to the original date value.

"},{"location":"built_in_transformers/standard_transformers/noise_date/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes date, timestamp, timestamptz min_ratio The minimum random value for noise. The value must be in PostgreSQL interval format, e. g. 1 year 2 mons 3 day 04:05:06.07 5% from max_ration parameter No - max_ratio The maximum random value for noise. The value must be in PostgreSQL interval format, e. g. 1 year 2 mons 3 day 04:05:06.07 Yes - min Min threshold date (and/or time) of value. The value has the same format as column parameter No - max Max threshold date (and/or time) of value. The value has the same format as column parameter No - truncate Truncate the date to the specified part (nanosecond, microsecond, millisecond, second, minute, hour, day, month, year). The truncate operation is not applied by default. No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/noise_date/#dynamic-parameters","title":"Dynamic parameters","text":"Parameter Supported types min date, timestamp, timestamptz max date, timestamp, timestamptz"},{"location":"built_in_transformers/standard_transformers/noise_date/#description","title":"Description","text":"

The NoiseDate transformer randomly generates duration between min_ratio and max_ratio parameter and adds it to or subtracts it from the original date value. The min_ratio or max_ratio parameters must be written in the PostgreSQL interval format. You can also truncate the resulted date up to a specified part by setting the truncate parameter.

In case you have constraints on the date range, you can set the min and max parameters to specify the threshold values. The values for min and max must have the same format as the column parameter. Parameters min and max support dynamic mode.

Info

If the noised value exceeds the max threshold, the transformer will set the value to max. If the noised value is lower than the min threshold, the transformer will set the value to min.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/noise_date/#example-adding-noise-to-the-modified-date","title":"Example: Adding noise to the modified date","text":"

In the following example, the original timestamp value of modifieddate will be noised up to 1 year 2 months 3 days 4 hours 5 minutes 6 seconds and 7 milliseconds with truncation up to the month part.

NoiseDate transformer example
- schema: \"humanresources\"\n  name: \"jobcandidate\"\n  transformers:\n    - name: \"NoiseDate\"\n      params:\n        column: \"hiredate\"\n        max_ratio: \"1 year 2 mons 3 day 04:05:06.07\"\n        truncate: \"month\"\n        max: \"2020-01-01 00:00:00\"\n
"},{"location":"built_in_transformers/standard_transformers/noise_date/#example-adding-noise-to-the-modified-date-with-dynamic-min-parameter-with-hash-engine","title":"Example: Adding noise to the modified date with dynamic min parameter with hash engine","text":"

In the following example, the original timestamp value of hiredate will be noised up to 1 year 2 months 3 days 4 hours 5 minutes 6 seconds and 7 milliseconds with truncation up to the month part. The max threshold is set to 2020-01-01 00:00:00, and the min threshold is set to the birthdate column. If the birthdate column is NULL, the default value 1990-01-01 will be used. The hash engine is used for deterministic generation - the same input will always produce the same output.

NoiseDate transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"NoiseDate\"\n      params:\n        column: \"hiredate\"\n        max_ratio: \"1 year 2 mons 3 day 04:05:06.07\"\n        truncate: \"month\"\n        max: \"2020-01-01 00:00:00\"\n        engine: \"hash\"\n      dynamic_params:\n        min:\n          column: \"birthdate\"\n          default: \"1990-01-01\"\n

Result

ColumnOriginalValueTransformedValue hiredate2009-01-142010-08-01"},{"location":"built_in_transformers/standard_transformers/noise_float/","title":"NoiseFloat","text":"

Add or subtract a random fraction to the original float value.

"},{"location":"built_in_transformers/standard_transformers/noise_float/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes float4, float8 decimal The decimal of the noised float value (number of digits after the decimal point) 4 No - min_ratio The minimum random percentage for noise, from 0 to 1, e. g. 0.1 means \"add noise up to 10%\" 0.05 No - max_ratio The maximum random percentage for noise, from 0 to 1, e. g. 0.1 means \"add noise up to 10%\" Yes - min Min threshold of noised value No - max Max threshold of noised value No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/noise_float/#dynamic-parameters","title":"Dynamic parameters","text":"Parameter Supported types min float4, float8, int2, int4, int8 max float4, float8, int2, int4, int8"},{"location":"built_in_transformers/standard_transformers/noise_float/#description","title":"Description","text":"

The NoiseFloat transformer multiplies the original float value by randomly generated value that is not higher than the max_ratio parameter and not less that max_ratio parameter and adds it to or subtracts it from the original value. Additionally, you can specify the number of decimal digits by using the decimal parameter.

In case you have constraints on the float range, you can set the min and max parameters to specify the threshold values. The values for min and max must have the same format as the column parameter. Parameters min and max support dynamic mode. Engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines

Info

If the noised value exceeds the max threshold, the transformer will set the value to max. If the noised value is lower than the min threshold, the transformer will set the value to min.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/noise_float/#example-adding-noise-to-the-purchase-price","title":"Example: Adding noise to the purchase price","text":"

In this example, the original value of standardprice will be noised up to 50% and rounded up to 2 decimals.

NoiseFloat transformer example
- schema: \"purchasing\"\n  name: \"productvendor\"\n  columns_type_override: # (1)\n    lastreceiptcost: \"float8\"\n    standardprice: \"float8\"\n  transformers:\n    - name: \"NoiseFloat\"\n      params:\n        column: \"lastreceiptcost\"\n        max_ratio: 0.15\n        decimal: 2\n      dynamic_params:\n        min:\n          column: \"standardprice\"\n
  1. The type overrides applied for example because the playground database does not contain any tables with float columns.

Result

ColumnOriginalValueTransformedValue lastreceiptcost50.263547.87"},{"location":"built_in_transformers/standard_transformers/noise_int/","title":"NoiseInt","text":"

Add or subtract a random fraction to the original integer value.

"},{"location":"built_in_transformers/standard_transformers/noise_int/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes int2, int4, int8 min_ratio The minimum random percentage for noise, from 0 to 1, e. g. 0.1 means \"add noise up to 10%\" 0.05 No - max_ratio The maximum random percentage for noise, from 0 to 1, e. g. 0.1 means \"add noise up to 10%\" Yes - min Min threshold of noised value No - max Min threshold of noised value No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/noise_int/#dynamic-parameters","title":"Dynamic parameters","text":"Parameter Supported types min int2, int4, int8 max int2, int4, int8"},{"location":"built_in_transformers/standard_transformers/noise_int/#description","title":"Description","text":"

The NoiseInt transformer multiplies the original integer value by randomly generated value that is not higher than the max_ratio parameter and not less that max_ratio parameter and adds it to or subtracts it from the original value.

In case you have constraints on the integer range, you can set the min and max parameters to specify the threshold values. The values for min and max must have the same format as the column parameter. Parameters min and max support dynamic mode.

Info

If the noised value exceeds the max threshold, the transformer will set the value to max. If the noised value is lower than the min threshold, the transformer will set the value to min.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/noise_int/#example-noise-vacation-hours-of-an-employee","title":"Example: Noise vacation hours of an employee","text":"

In the following example, the original value of vacationhours will be noised up to 40%. The transformer will set the value to 10 if the noised value is lower than 10 and to 1000 if the noised value exceeds 1000.

NoiseInt transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"NoiseInt\"\n      params:\n        column: \"vacationhours\"\n        max_ratio: 0.4\n        min: 10\n        max: 1000\n

Result

ColumnOriginalValueTransformedValue vacationhours9969"},{"location":"built_in_transformers/standard_transformers/noise_numeric/","title":"NoiseNumeric","text":"

Add or subtract a random fraction to the original numeric value.

"},{"location":"built_in_transformers/standard_transformers/noise_numeric/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes numeric, decimal decimal The decimal of the noised float value (number of digits after the decimal point) 4 No - min_ratio The minimum random percentage for noise, from 0 to 1, e. g. 0.1 means \"add noise up to 10%\" 0.05 No - max_ratio The maximum random percentage for noise, from 0 to 1, e. g. 0.1 means \"add noise up to 10%\" Yes - min Min threshold of noised value No - max Max threshold of noised value No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/noise_numeric/#dynamic-parameters","title":"Dynamic parameters","text":"Parameter Supported types min numeric, decimal, float4, float8, int2, int4, int8 max numeric, decimal, float4, float8, int2, int4, int8"},{"location":"built_in_transformers/standard_transformers/noise_numeric/#description","title":"Description","text":"

The NoiseNumeric transformer multiplies the original numeric (or decimal) value by randomly generated value that is not higher than the max_ratio parameter and not less that max_ratio parameter and adds it to or subtracts it from the original value. Additionally, you can specify the number of decimal digits by using the decimal parameter.

In case you have constraints on the numeric range, you can set the min and max parameters to specify the threshold values. The values for min and max must have the same format as the column parameter. Parameters min and max support dynamic mode. Engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines

Info

If the noised value exceeds the max threshold, the transformer will set the value to max. If the noised value is lower than the min threshold, the transformer will set the value to min.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

Warning

Greenmask cannot parse the numeric type sitteng. For instance NUMERIC(10, 2). You should set min and max treshholds manually as well as allowed decimal. This behaviour will be changed in the later versions. Grenmask will be able to determine the decimal and scale of the column and set the min and max treshholds automatically if were not set.

"},{"location":"built_in_transformers/standard_transformers/noise_numeric/#example-adding-noise-to-the-purchase-price","title":"Example: Adding noise to the purchase price","text":"

In this example, the original value of standardprice will be noised up to 50% and rounded up to 2 decimals.

NoiseNumeric transformer example
- schema: \"purchasing\"\n  name: \"productvendor\"\n  transformers:\n    - name: \"NoiseNumeric\"\n      params:\n        column: \"lastreceiptcost\"\n        max_ratio: 0.15\n        decimal: 2\n        max: 10000\n      dynamic_params:\n        min:\n          column: \"standardprice\"\n

Result

ColumnOriginalValueTransformedValue lastreceiptcost50.263557.33"},{"location":"built_in_transformers/standard_transformers/random_amount_with_currency/","title":"RandomAmountWithCurrency","text":"

The RandomAmountWithCurrency transformer is specifically designed to populate specified database columns with random financial amounts accompanied by currency codes. Ideal for applications requiring the simulation of financial transactions, this utility enhances the realism of financial datasets by introducing variability in amounts and currencies.

"},{"location":"built_in_transformers/standard_transformers/random_amount_with_currency/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_amount_with_currency/#description","title":"Description","text":"

This transformer automatically generates random financial amounts along with corresponding global currency codes (e. g., 250.00 USD, 300.00 EUR), injecting them into the designated database column. It provides a straightforward solution for populating financial records with varied and realistic data, suitable for testing payment systems, data anonymization, and simulation of economic models.

"},{"location":"built_in_transformers/standard_transformers/random_amount_with_currency/#example-populate-the-payments-table-with-random-amounts-and-currencies","title":"Example: Populate the payments table with random amounts and currencies","text":"

This example shows how to configure the RandomAmountWithCurrency transformer to populate the payment_details column in the payments table with random amounts and currencies. It is an effective approach to simulating a diverse range of payment transactions.

RandomAmountWithCurrency transformer example
- schema: \"public\"\n  name: \"payments\"\n  transformers:\n    - name: \"RandomAmountWithCurrency\"\n      params:\n        column: \"payment_details\"\n        keep_null: false\n

In this setup, the payment_details column will be updated with random financial amounts and currency codes for each entry, replacing any existing non-NULL values. The keep_null parameter, when set to true, ensures that existing NULL values in the column remain unchanged, preserving the integrity of records without specified payment details.

"},{"location":"built_in_transformers/standard_transformers/random_bool/","title":"RandomBool","text":"

Generate random boolean values.

"},{"location":"built_in_transformers/standard_transformers/random_bool/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes bool keep_null Indicates whether NULL values should be replaced with transformed values or not true No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_bool/#description","title":"Description","text":"

The RandomBool transformer generates a random boolean value. The behaviour for NULL values can be configured using the keep_null parameter. The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_bool/#example-generate-a-random-boolean-for-a-column","title":"Example: Generate a random boolean for a column","text":"

In the following example, the RandomBool transformer generates a random boolean value for the salariedflag column.

RandomBool transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"RandomBool\"\n      params:\n        column: \"salariedflag\"\n

Result

ColumnOriginalValueTransformedValue salariedflagtf"},{"location":"built_in_transformers/standard_transformers/random_cc_number/","title":"RandomCCNumber","text":"

The RandomCCNumber transformer is specifically designed to populate specified database columns with random credit card numbers. This utility is crucial for applications that involve simulating financial data, testing payment systems, or anonymizing real credit card numbers in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_cc_number/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_cc_number/#description","title":"Description","text":"

By leveraging algorithms capable of generating plausible credit card numbers that adhere to standard credit card validation rules (such as the Luhn algorithm), the RandomCCNumber transformer injects random credit card numbers into the designated database column. This approach ensures the generation of credit card numbers that are realistic for testing and development purposes, without compromising real-world applicability and security.

"},{"location":"built_in_transformers/standard_transformers/random_cc_number/#example-populate-random-credit-card-numbers-for-the-payment_information-table","title":"Example: Populate random credit card numbers for the payment_information table","text":"

This example demonstrates configuring the RandomCCNumber transformer to populate the cc_number column in the payment_information table with random credit card numbers. It is an effective strategy for creating a realistic set of payment data for application testing or data anonymization.

RandomCCNumber transformer example
- schema: \"public\"\n  name: \"payment_information\"\n  transformers:\n    - name: \"RandomCCNumber\"\n      params:\n        column: \"cc_number\"\n        keep_null: false\n

With this setup, the cc_number column will be updated with random credit card numbers for each entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, it will ensure that existing NULL values in the column are preserved, maintaining the integrity of records where credit card information is not applicable or available.

"},{"location":"built_in_transformers/standard_transformers/random_cc_type/","title":"RandomCCType","text":"

The RandomCCType transformer is designed to populate specified database columns with random credit card types. This tool is essential for applications that require the simulation of financial transaction data, testing payment processing systems, or anonymizing credit card type information in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_cc_type/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_cc_type/#description","title":"Description","text":"

Utilizing a predefined list of credit card types (e.g., VISA, MasterCard, American Express, Discover), the RandomCCType transformer injects random credit card type names into the designated database column. This feature allows for the creation of realistic and varied financial transaction datasets by simulating a range of credit card types without using real card data.

"},{"location":"built_in_transformers/standard_transformers/random_cc_type/#example-populate-random-credit-card-types-for-the-transactions-table","title":"Example: Populate random credit card types for the transactions table","text":"

This example shows how to configure the RandomCCType transformer to populate the card_type column in the transactions table with random credit card types. It is a straightforward method for simulating diverse payment methods across transactions.

RandomCCType transformer example
- schema: \"public\"\n  name: \"transactions\"\n  transformers:\n    - name: \"RandomCCType\"\n      params:\n        column: \"card_type\"\n        keep_null: false\n

In this configuration, the card_type column will be updated with random credit card types for each entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, maintaining the integrity of records where card type information is not applicable.

"},{"location":"built_in_transformers/standard_transformers/random_century/","title":"RandomCentury","text":"

The RandomCentury transformer is crafted to populate specified database columns with random century values. It is ideal for applications that require historical data simulation, such as generating random years within specific centuries for historical databases, testing datasets with temporal dimensions, or anonymizing dates in historical research data.

"},{"location":"built_in_transformers/standard_transformers/random_century/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_century/#description","title":"Description","text":"

The RandomCentury transformer utilizes an algorithm or a library function (hypothetical in this context) to generate random century values. Each value represents a century (e.g., 19th, 20th, 21st), providing a broad temporal range that can be used to enhance datasets requiring a distribution across different historical periods without the need for precise date information.

"},{"location":"built_in_transformers/standard_transformers/random_century/#example-populate-random-centuries-for-the-historical_artifacts-table","title":"Example: Populate random centuries for the historical_artifacts table","text":"

This example shows how to configure the RandomCentury transformer to populate the century column in a historical_artifacts table with random century values, adding an element of variability and historical context to the dataset.

RandomCentury transformer example
- schema: \"public\"\n  name: \"historical_artifacts\"\n  transformers:\n    - name: \"RandomCentury\"\n      params:\n        column: \"century\"\n        keep_null: false\n

In this setup, the century column will be filled with random century values, replacing any existing non-NULL values. If the keep_null parameter is set to true, then existing NULL values in the column will remain untouched, preserving the original dataset's integrity where no temporal data is available.

"},{"location":"built_in_transformers/standard_transformers/random_choice/","title":"RandomChoice","text":"

Replace values randomly chosen from a provided list.

"},{"location":"built_in_transformers/standard_transformers/random_choice/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes any values A list of values in any format. The string with value \\N is considered NULL. Yes - validate Performs a decoding procedure via the PostgreSQL driver using the column type to ensure that values have correct type true No keep_null Indicates whether NULL values should be replaced with transformed values or not true No engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_choice/#description","title":"Description","text":"

The RandomChoice transformer replaces one randomly chosen value from the list provided in the values parameter. You can use the validate parameter to ensure that values are correct before applying the transformation. The behaviour for NULL values can be configured using the keep_null parameter.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_choice/#example-choosing-randomly-from-provided-dates","title":"Example: Choosing randomly from provided dates","text":"

In this example, the provided values undergo validation through PostgreSQL driver decoding, and one value is randomly chosen from the list.

RandomChoice transformer example
- schema: \"humanresources\"\n  name: \"jobcandidate\"\n  transformers:\n    - name: \"RandomChoice\"\n      params:\n        column: \"modifieddate\"\n        validate: true\n        engine: hash\n        values:\n          - \"2023-12-21 07:41:06.891\"\n          - \"2023-12-21 07:41:06.896\"\n

Result

ColumnOriginalValueTransformedValue modifieddate2007-06-23 00:00:002023-12-21 07:41:06.891"},{"location":"built_in_transformers/standard_transformers/random_currency/","title":"RandomCurrency","text":"

The RandomCurrency transformer is tailored to populate specified database columns with random currency codes. This tool is highly beneficial for applications involving the simulation of international financial data, testing currency conversion features, or anonymizing currency information in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_currency/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_currency/#description","title":"Description","text":"

Utilizing a comprehensive list of global currency codes (e.g., USD, EUR, JPY), the RandomCurrency transformer injects random currency codes into the designated database column. This feature allows for the creation of diverse and realistic financial transaction datasets by simulating a variety of currencies without relying on actual financial data.

"},{"location":"built_in_transformers/standard_transformers/random_currency/#example-populate-random-currency-codes-for-the-transactions-table","title":"Example: Populate random currency codes for the transactions table","text":"

This example outlines configuring the RandomCurrency transformer to populate the currency_code column in a transactions table with random currency codes. It is an effective way to simulate international transactions across multiple currencies.

RandomCurrency transformer example
- schema: \"public\"\n  name: \"transactions\"\n  transformers:\n    - name: \"RandomCurrency\"\n      params:\n        column: \"currency_code\"\n        keep_null: false\n

In this configuration, the currency_code column will be updated with random currency codes for each entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, ensuring the integrity of records where currency data may not be applicable.

"},{"location":"built_in_transformers/standard_transformers/random_date/","title":"RandomDate","text":"

Generate a random date in a specified interval.

"},{"location":"built_in_transformers/standard_transformers/random_date/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column Name of the column to be affected Yes date, timestamp, timestamptz min The minimum threshold date for the random value. The format depends on the column type. Yes - max The maximum threshold date for the random value. The format depends on the column type. Yes - truncate Truncate the date to the specified part (nanosecond, microsecond, millisecond, second, minute, hour, day, month, year). The truncate operation is not applied by default. No - keep_null Indicates whether NULL values should be replaced with transformed values or not true No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_date/#dynamic-parameters","title":"Dynamic parameters","text":"Parameter Supported types min date, timestamp, timestamptz max date, timestamp, timestamptz"},{"location":"built_in_transformers/standard_transformers/random_date/#description","title":"Description","text":"

The RandomDate transformer generates a random date within the provided interval, starting from min to max. It can also perform date truncation up to the specified part of the date. The format of dates in the min and max parameters must adhere to PostgreSQL types, including DATE, TIMESTAMP WITHOUT TIMEZONE, or TIMESTAMP WITH TIMEZONE.

Note

The value of min and max parameters depends on the column type. For example, for the date column, the value should be in the format YYYY-MM-DD, while for the timestamp column, the value should be in the format YYYY-MM-DD HH:MM:SS or YYYY-MM-DD HH:MM:SS.SSSSSS. The timestamptz column requires the value to be in the format YYYY-MM-DD HH:MM:SS.SSSSSS+HH:MM. Read more about date/time formats in the PostgreSQL documentation.

The behaviour for NULL values can be configured using the keep_null parameter. The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_date/#example-generate-modifieddate","title":"Example: Generate modifieddate","text":"

In the following example, a random timestamp without timezone is generated for the modifieddate column within the range from 2011-05-31 00:00:00 to 2013-05-31 00:00:00, and the part of the random value after day is truncated.

RandomDate transformer example
- schema: \"sales\"\n  name: \"salesorderdetail\"\n  transformers:\n    - name: \"RandomDate\"\n      params:\n        column: \"modifieddate\"\n        keep_null: false\n        min: \"2011-05-31 00:00:00\"\n        max: \"2013-05-31 00:00:00\"\n        truncate: \"day\"\n

Result

ColumnOriginalValueTransformedValue modifieddate2014-06-30 00:00:002012-07-27 00:00:00"},{"location":"built_in_transformers/standard_transformers/random_date/#example-generate-hiredate-based-on-birthdate-using-two-transformations","title":"Example: Generate hiredate based on birthdate using two transformations","text":"

In this example, the RandomDate transformer generates a random date for the birthdate column within the range now - 50 years to now - 18 years. The hire date is generated based on the birthdate, ensuring that the employee is at least 18 years old when hired.

- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"RandomDate\"\n      params:\n        column: \"birthdate\"\n        min: '{{ now | tsModify \"-50 years\" | .EncodeValue }}' # 1994\n        max: '{{ now | tsModify \"-18 years\" | .EncodeValue }}' # 2006\n\n    - name: \"RandomDate\"\n      params:\n        column: \"hiredate\"\n        truncate: \"month\"\n        max: \"{{ now | .EncodeValue }}\"\n      dynamic_params:\n        min:\n          column: \"birthdate\"\n          template: '{{ .GetValue | tsModify \"18 years\" | .EncodeValue }}' # min age 18 years\n

Result:

ColumnOriginalValueTransformedValue birthdate1969-01-291985-10-29 hiredate2009-01-142023-01-01"},{"location":"built_in_transformers/standard_transformers/random_day_of_month/","title":"RandomDayOfMonth","text":"

The RandomDayOfMonth transformer is designed to populate specified database columns with random day-of-the-month values. It is particularly useful for scenarios requiring the simulation of dates, such as generating random event dates, user sign-up dates, or any situation where the specific day of the month is needed without reference to the actual month or year.

"},{"location":"built_in_transformers/standard_transformers/random_day_of_month/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar, int2, int4, int8, numeric keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_day_of_month/#description","title":"Description","text":"

Utilizing the faker library, the RandomDayOfMonth transformer generates random numerical values representing days of the month, ranging from 1 to 31. This allows for the easy insertion of random but plausible day-of-the-month data into a database, enhancing realism or anonymizing actual dates.

"},{"location":"built_in_transformers/standard_transformers/random_day_of_month/#example-populate-random-days-of-the-month-for-the-events-table","title":"Example: Populate random days of the month for the events table","text":"

This example illustrates how to configure the RandomDayOfMonth transformer to fill the event_day column in the events table with random day-of-the-month values, facilitating the simulation of varied event scheduling.

RandomDayOfMonth transformer example
- schema: \"public\"\n  name: \"events\"\n  transformers:\n    - name: \"RandomDayOfMonth\"\n      params:\n        column: \"event_day\"\n        keep_null: false\n

With this setup, the event_day column will be updated with random day-of-the-month values, replacing any existing non-NULL values. Setting keep_null to true ensures that NULL values in the column are left unchanged, maintaining any existing gaps in the data.

"},{"location":"built_in_transformers/standard_transformers/random_day_of_week/","title":"RandomDayOfWeek","text":"

The RandomDayOfWeek transformer is specifically designed to fill specified database columns with random day-of-the-week names. It is particularly useful for applications that require simulated weekly schedules, random event planning, or any scenario where the day of the week is relevant but the specific date is not.

"},{"location":"built_in_transformers/standard_transformers/random_day_of_week/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_day_of_week/#description","title":"Description","text":"

Utilizing the faker library, the RandomDayOfWeek transformer generates names of days (e. g., Monday, Tuesday) at random. This transformer can be applied to any text or varchar column in a database, introducing variability and realism into data sets that need to represent days of the week in a non-specific manner.

"},{"location":"built_in_transformers/standard_transformers/random_day_of_week/#example-populate-random-days-of-the-week-for-the-work_schedule-table","title":"Example: Populate random days of the week for the work_schedule table","text":"

This example demonstrates configuring the RandomDayOfWeek transformer to populate the work_day column in the work_schedule table with random days of the week. This setup can help simulate a diverse range of work schedules without tying them to specific dates.

RandomDayOfWeek transformer example
- schema: \"public\"\n  name: \"work_schedule\"\n  transformers:\n    - name: \"RandomDayOfWeek\"\n      params:\n        column: \"work_day\"\n        keep_null: false\n

In this configuration, every entry in the work_day column will be updated with a random day of the week, replacing any existing non-NULL values. If the keep_null parameter is set to true, then existing NULL values within the column will remain unchanged.

"},{"location":"built_in_transformers/standard_transformers/random_domain_name/","title":"RandomDomainName","text":"

The RandomDomainName transformer is designed to populate specified database columns with random domain names. This tool is invaluable for simulating web data, testing applications that interact with domain names, or anonymizing real domain information in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_domain_name/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_domain_name/#description","title":"Description","text":"

By leveraging an algorithm or library capable of generating believable domain names, the RandomDomainName transformer introduces random domain names into the specified database column. Each generated domain name includes a second-level domain (SLD) and a top-level domain (TLD), such as \"example.com\" or \"website.org,\" providing a wide range of plausible web addresses for database enrichment.

"},{"location":"built_in_transformers/standard_transformers/random_domain_name/#example-populate-random-domain-names-for-the-websites-table","title":"Example: Populate random domain names for the websites table","text":"

This example demonstrates configuring the RandomDomainName transformer to populate the domain column in the websites table with random domain names. This approach facilitates the creation of a diverse and realistic set of web addresses for testing, simulation, or data anonymization purposes.

RandomDomainName transformer example
- schema: \"public\"\n  name: \"websites\"\n  transformers:\n    - name: \"RandomDomainName\"\n      params:\n        column: \"domain\"\n        keep_null: false\n

In this setup, the domain column will be updated with random domain names for each entry, replacing any existing non-NULL values. If keep_null is set to true, the transformer will preserve existing NULL values in the column, maintaining the integrity of data where domain information is not applicable.

"},{"location":"built_in_transformers/standard_transformers/random_e164_phone_number/","title":"RandomE164PhoneNumber","text":"

The RandomE164PhoneNumber transformer is developed to populate specified database columns with random E.164 phone numbers. This tool is essential for applications requiring the simulation of contact information, testing phone number validation systems, or anonymizing phone number data in datasets while focusing on E.164 numbers.

"},{"location":"built_in_transformers/standard_transformers/random_e164_phone_number/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_e164_phone_number/#description","title":"Description","text":"

The RandomE164PhoneNumber transformer utilizes algorithms capable of generating random E.164 phone numbers with the standard international format and injects them into the designated database column. This feature allows for the creation of diverse and realistic contact information in datasets for development, testing, or data anonymization purposes.

"},{"location":"built_in_transformers/standard_transformers/random_e164_phone_number/#example-populate-random-e164-phone-numbers-for-the-contact_information-table","title":"Example: Populate random E.164 phone numbers for the contact_information table","text":"

This example demonstrates configuring the RandomE164PhoneNumber transformer to populate the phone_number column in the contact_information table with random E.164 phone numbers. It is an effective method for simulating a variety of contact information entries with E.164 numbers.

RandomE164PhoneNumber transformer example
- schema: \"public\"\n  name: \"contact_information\"\n  transformers:\n    - name: \"RandomE164PhoneNumber\"\n      params:\n        column: \"phone_number\"\n        keep_null: false\n

In this configuration, the phone_number column will be updated with random E.164 phone numbers for each contact information entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, ensuring the integrity of records where E.164 phone number information is not applicable or provided.

"},{"location":"built_in_transformers/standard_transformers/random_email/","title":"RandomEmail","text":"

Generate email addresses for a specified column.

"},{"location":"built_in_transformers/standard_transformers/random_email/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_original_domain Keep original of the original address false No - local_part_template The template for local part of email No - domain_part_template The template for domain part of email No - domains List of domains for new email [\"gmail.com\", \"yahoo.com\", \"outlook.com\", \"hotmail.com\", \"aol.com\", \"icloud.com\", \"mail.com\", \"zoho.com\", \"yandex.com\", \"protonmail.com\", \"gmx.com\", \"fastmail.com\"] No - validate Validate generated email if using template false No - max_random_length Max length of randomly generated part of the email 32 No - keep_null Indicates whether NULL values should be preserved false No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_email/#description","title":"Description","text":"

The RandomEmail transformer generates random email addresses for the specified database column. By default, the transformer generates random email addresses with a maximum length of 32 characters. The keep_original_domain parameter allows you to preserve the original domain part of the email address. The local_part_template and domain_part_template parameters enable you to specify templates for the local and domain parts of the email address, respectively. If the validate parameter is set to true, the transformer will validate the generated email addresses against the specified templates. The keep_null parameter allows you to preserve existing NULL values in the column.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_email/#templates-parameters","title":"Templates parameters","text":"

In each template you have access to the columns of the table by using the {{ .column_name }} syntax. Note that all values are strings. For example, you can use for assembling the email address by accessing to first_name and last_name columns {{ .first_name | lower }}.{{ .last_name | lower }}.

The transformer always generates random sequences for the email, and you can use it by accessing the {{ .random_string }} variable. For example, we can add random string in the end of local part {{ .first_name | lower }}.{{ .last_name | lower }}.{{ .random_string }}.

Read more about template function Template functions.

"},{"location":"built_in_transformers/standard_transformers/random_email/#random-email-generation-using-first-name-and-last-name","title":"Random email generation using first name and last name","text":"

In this example, the RandomEmail transformer generates random email addresses for the email column in the account table. The transformer generates email addresses using the first_name and last_name columns as the local part of the email address and adds a random string to the end of the local part with length 10 characters. The original domain part of the email address is preserved.

CREATE TABLE account\n(\n    id         SERIAL PRIMARY KEY,\n    gender     VARCHAR(1) NOT NULL,\n    email      TEXT       NOT NULL NOT NULL UNIQUE,\n    first_name TEXT       NOT NULL,\n    last_name  TEXT       NOT NULL,\n    birth_date DATE,\n    created_at TIMESTAMP  NOT NULL DEFAULT NOW()\n);\n\nINSERT INTO account (first_name, gender, last_name, birth_date, email)\nVALUES ('John', 'M', 'Smith', '1980-01-01', 'john.smith@gmail.com');\n
RandomEmail transformer example
- schema: \"public\"\n  name: \"account\"\n  transformers:\n    - name: \"RandomEmail\"\n      params:\n        column: \"email\"\n        engine: \"hash\"\n        keep_original_domain: true\n        local_part_template: \"{{ first_name | lower }}.{{ last_name | lower }}.{{ .random_string | trunc 10 }}\"\n

Result:

ColumnOriginalValueTransformedValue emailjohn.smith@gmail.comjohn.smith.a075d99e2d@gmail.com"},{"location":"built_in_transformers/standard_transformers/random_email/#simple-random-email-generation","title":"Simple random email generation","text":"

In this example, the RandomEmail transformer generates random email addresses for the email column in the account table. The transformer generates random email addresses with a maximum length of 10 characters.

RandomEmail transformer example
- schema: \"public\"\n  name: \"account\"\n  transformers:\n    - name: \"RandomEmail\"\n      params:\n        column: \"email\"\n        max_random_length: 10\n

Result:

ColumnOriginalValueTransformedValue emailjohn.smith@gmail.comjohn.smith.a075d99e2d@gmail.com"},{"location":"built_in_transformers/standard_transformers/random_float/","title":"RandomFloat","text":"

Generate a random float within the provided interval.

"},{"location":"built_in_transformers/standard_transformers/random_float/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes float4, float8 min The minimum threshold for the random value. The value range depends on the column type. Yes - max The maximum threshold for the random value. The value range depends on the column type. Yes - decimal The decimal of the random float value (number of digits after the decimal point) 4 No - keep_null Indicates whether NULL values should be replaced with transformed values or not true No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_float/#dynamic-parameters","title":"Dynamic parameters","text":"Parameter Supported types min float4, float8 max float4, float8"},{"location":"built_in_transformers/standard_transformers/random_float/#description","title":"Description","text":"

The RandomFloat transformer generates a random float value within the provided interval, starting from min to max, with the option to specify the number of decimal digits by using the decimal parameter. The behaviour for NULL values can be configured using the keep_null parameter.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_float/#example-generate-random-price","title":"Example: Generate random price","text":"

In this example, the RandomFloat transformer generates random prices in the range from 0.1 to 7000 while maintaining a decimal of up to 2 digits.

RandomFloat transformer example
- schema: \"sales\"\n  name: \"salesorderdetail\"\n  columns_type_override:  # (1)\n    \"unitprice\": \"float8\"\n  transformers:\n    - name: \"RandomFloat\"\n      params:\n        column: \"unitprice\"\n        min: 0.1\n        max: 7000\n        decimal: 2\n
  1. The type overrides applied for example because the playground database does not contain any tables with float columns.

Result:

ColumnOriginalValueTransformedValue unitprice2024.9944449.7"},{"location":"built_in_transformers/standard_transformers/random_int/","title":"RandomInt","text":"

Generate a random integer within the provided interval.

"},{"location":"built_in_transformers/standard_transformers/random_int/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes int2, int4, int8 min The minimum threshold for the random value Yes - max The maximum threshold for the random value Yes - keep_null Indicates whether NULL values should be replaced with transformed values or not true No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_int/#dynamic-parameters","title":"Dynamic parameters","text":"Parameter Supported types min int2, int4, int8 max int2, int4, int8"},{"location":"built_in_transformers/standard_transformers/random_int/#description","title":"Description","text":"

The RandomInt transformer generates a random integer within the specified min and max thresholds. The behaviour for NULL values can be configured using the keep_null parameter.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_int/#example-generate-random-item-quantity","title":"Example: Generate random item quantity","text":"

In the following example, the RandomInt transformer generates a random value in the range from 1 to 30 and assigns it to the orderqty column.

generate random orderqty in the range from 1 to 30
- schema: \"sales\"\n  name: \"salesorderdetail\"\n  transformers:\n    - name: \"RandomInt\"\n      params:\n        column: \"orderqty\"\n        min: 1\n        max: 30\n

Result

ColumnOriginalValueTransformedValue orderqty129"},{"location":"built_in_transformers/standard_transformers/random_int/#example-generate-random-sick-leave-hours-based-on-vacation-hours","title":"Example: Generate random sick leave hours based on vacation hours","text":"

In the following example, the RandomInt transformer generates a random value in the range from 1 to the value of the vacationhours column and assigns it to the sickleavehours column. This configuration allows for the simulation of sick leave hours based on the number of vacation hours.

RandomInt transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"RandomInt\"\n      params:\n        column: \"sickleavehours\"\n        max: 100\n      dynamic_params:\n        min:\n          column: \"vacationhours\"\n

Result

ColumnOriginalValueTransformedValue sickleavehours6999"},{"location":"built_in_transformers/standard_transformers/random_ip/","title":"RandomIP","text":"

The RandomIp transformer is designed to populate specified database columns with random IP v4 or V6 addresses. This utility is essential for applications requiring the simulation of network data, testing systems that utilize IP addresses, or anonymizing real IP addresses in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_ip/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar, inet subnet Subnet for generating random ip in V4 or V6 format Yes - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_ip/#dynamic-parameters","title":"Dynamic parameters","text":"Name Supported types subnet cidr, text, varchar"},{"location":"built_in_transformers/standard_transformers/random_ip/#description","title":"Description","text":"

Utilizing a robust algorithm or library for generating IP addresses, the RandomIp transformer injects random IPv4 or IPv6 addresses into the designated database column, depending on the provided subnet. The transformer automatically detects whether to generate an IPv4 or IPv6 address based on the subnet version specified.

"},{"location":"built_in_transformers/standard_transformers/random_ip/#example-generate-a-random-ipv4-address-for-a-1921681024-subnet","title":"Example: Generate a Random IPv4 Address for a 192.168.1.0/24 Subnet","text":"

This example demonstrates how to configure the RandomIp transformer to inject a random IPv4 address into the ip_address column for entries in the 192.168.1.0/24 subnet:

Create table ip_networks and insert data
CREATE TABLE ip_networks\n(\n    id         SERIAL PRIMARY KEY,\n    ip_address INET,\n    network    CIDR\n);\n\nINSERT INTO ip_networks (ip_address, network)\nVALUES ('192.168.1.10', '192.168.1.0/24'),\n       ('10.0.0.5', '10.0.0.0/16'),\n       ('172.16.254.3', '172.16.0.0/12'),\n       ('192.168.100.14', '192.168.100.0/24'),\n       ('2001:0db8:85a3:0000:0000:8a2e:0370:7334', '2001:0db8:85a3::/64'); -- An IPv6 address and network\n
RandomPerson transformer example
- schema: public\n  name: ip_networks\n  transformers:\n    - name: \"RandomIp\"\n      params:\n        subnet: \"192.168.1.0/24\"\n        column: \"ip_address\"\n        engine: \"random\"\n

Result:

ColumnOriginalValueTransformedValue ip_address192.168.1.10192.168.1.28"},{"location":"built_in_transformers/standard_transformers/random_ip/#example-generate-a-random-ip-based-on-the-dynamic-subnet-parameter","title":"Example: Generate a Random IP Based on the Dynamic Subnet Parameter","text":"

This configuration illustrates how to use the RandomIp transformer dynamically, where it reads the subnet information from the network column of the database and generates a corresponding random IP address:

RandomPerson transformer example with dynamic mode
- schema: public\n  name: ip_networks\n  transformers:\n    - name: \"RandomIp\"\n      params:\n        column: \"ip_address\"\n        engine: \"random\"\n      dynamic_params:\n        subnet:\n          column: \"network\"\n

Result:

ColumnOriginalValueTransformedValue ip_address192.168.1.10192.168.1.111"},{"location":"built_in_transformers/standard_transformers/random_latitude/","title":"RandomLatitude","text":"

The RandomLatitude transformer generates random latitude values for specified database columns. It is designed to support geographical data enhancements, particularly useful for applications requiring randomized but plausible geographical coordinates.

"},{"location":"built_in_transformers/standard_transformers/random_latitude/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes float4, float8, numeric keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_latitude/#description","title":"Description","text":"

The RandomLatitude transformer utilizes the faker library to produce random latitude values within the range of -90 to +90 degrees. This transformer can be applied to columns designated to store geographical latitude information, enhancing data sets with randomized latitude coordinates.

"},{"location":"built_in_transformers/standard_transformers/random_latitude/#example-populate-random-latitude-for-the-locations-table","title":"Example: Populate random latitude for the locations table","text":"

This example demonstrates configuring the RandomLatitude transformer to populate the latitude column in the locations table with random latitude values.

RandomLatitude transformer example
- schema: \"public\"\n  name: \"locations\"\n  transformers:\n    - name: \"RandomLatitude\"\n      params:\n        column: \"latitude\"\n        keep_null: false\n

With this configuration, the latitude column will be filled with random latitude values, replacing any existing non-NULL values. If keep_null is set to true, existing NULL values will be preserved.

"},{"location":"built_in_transformers/standard_transformers/random_longitude/","title":"RandomLongitude","text":"

The RandomLongitude transformer is designed to generate random longitude values for specified database columns, enhancing datasets with realistic geographic coordinates suitable for a wide range of applications, from testing location-based services to anonymizing real geographic data.

"},{"location":"built_in_transformers/standard_transformers/random_longitude/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes float4, float8, numeric keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_longitude/#description","title":"Description","text":"

The RandomLongitude transformer leverages the faker library to produce random longitude values within the globally accepted range of -180 to +180 degrees. This flexibility allows the transformer to be applied to any column intended for storing longitude data, providing a simple yet powerful tool for introducing randomized longitude coordinates into a database.

"},{"location":"built_in_transformers/standard_transformers/random_longitude/#example-populate-random-longitude-for-the-locations-table","title":"Example: Populate random longitude for the locations table","text":"

This example shows how to use the RandomLongitude transformer to fill the longitude column in the locations table with random longitude values.

RandomLongitude transformer example
- schema: \"public\"\n  name: \"locations\"\n  transformers:\n    - name: \"RandomLongitude\"\n      params:\n        column: \"longitude\"\n        keep_null: false\n

This setup ensures that all entries in the longitude column receive a random longitude value, replacing any existing non-NULL values. If keep_null is set to true, then existing NULL values in the column will remain unchanged.

"},{"location":"built_in_transformers/standard_transformers/random_mac/","title":"RandomMac","text":"

The RandomMac transformer is designed to populate specified database columns with random MAC addresses.

"},{"location":"built_in_transformers/standard_transformers/random_mac/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar, macaddr keep_original_vendor Should the Individual/Group (I/G) and Universal/Local (U/L) bits be preserved from the original MAC address. false No - cast_type Param which allow to set Individual/Group (I/G) bit in MAC Address. Allowed values [any, individual, group]. If this value is individual, the address is meant for a single device (unicast). If it is group, the address is for a group of devices, which can include multicast and broadcast addresses. any No management_type Param which allow to set Universal/Local (U/L) bit in MAC Address. Allowed values [any, universal, local]. If this bit is universal, the address is universally administered (globally unique). If it is local, the address is locally administered (such as when set manually or programmatically on a network device). any No engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_mac/#description","title":"Description","text":"

The RandomMac transformer generates a random MAC address and injects it into the specified database column. The transformer can be configured to preserve the Individual/Group (I/G) and Universal/Local (U/L) bits from the original MAC address. You can also keep the original vendor bits in the generated MAC address by setting the keep_original_vendor parameter to true.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_mac/#example-generate-a-random-mac-address","title":"Example: Generate a Random MAC Address","text":"

This example demonstrates how to configure the RandomMac transformer to inject a random MAC address into the mac_address column:

Create table mac_addresses and insert data
CREATE TABLE mac_addresses\n(\n    id          SERIAL PRIMARY KEY,\n    device_name VARCHAR(50),\n    mac_address MACADDR,\n    description TEXT\n);\n\nINSERT INTO mac_addresses (device_name, mac_address, description)\nVALUES ('Device A', '00:1A:2B:3C:4D:5E', 'Description for Device A'),\n       ('Device B', '01:2B:3C:4D:5E:6F', 'Description for Device B'),\n       ('Device C', '02:3C:4D:5E:6F:70', 'Description for Device C'),\n       ('Device D', '03:4D:5E:6F:70:71', 'Description for Device D'),\n       ('Device E', '04:5E:6F:70:71:72', 'Description for Device E');\n
RandomPerson transformer example
- schema: public\n  name: mac_addresses\n  transformers:\n    - name: \"RandomMac\"\n      params:\n        column: \"mac_address\"\n        engine: \"random\"\n        cast_type: \"any\"\n        management_type: \"any\"\n

Result:

ColumnOriginalValueTransformedValue mac_address00:1a:2b:3c:4d:5eac:7f:a8:11:4e:0d"},{"location":"built_in_transformers/standard_transformers/random_month_name/","title":"RandomMonthName","text":"

The RandomMonthName transformer is crafted to populate specified database columns with random month names. This transformer is especially useful for scenarios requiring the simulation of time-related data, such as user birth months or event months, without relying on specific date values.

"},{"location":"built_in_transformers/standard_transformers/random_month_name/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_month_name/#description","title":"Description","text":"

The RandomMonthName transformer utilizes the faker library to generate the names of months at random. It can be applied to any textual column in a database to introduce variety and realism into data sets that require representations of months without the need for specific calendar dates.

"},{"location":"built_in_transformers/standard_transformers/random_month_name/#example-populate-random-month-names-for-the-user_profiles-table","title":"Example: Populate random month names for the user_profiles table","text":"

This example demonstrates how to configure the RandomMonthName transformer to fill the birth_month column in the user_profiles table with random month names, adding a layer of diversity to user data without using actual birthdates.

RandomMonthName transformer example
- schema: \"public\"\n  name: \"user_profiles\"\n  transformers:\n    - name: \"RandomMonthName\"\n      params:\n        column: \"birth_month\"\n        keep_null: false\n

With this setup, the birth_month column will be updated with random month names, replacing any existing non-NULL values. If the keep_null parameter is set to true, then existing NULL values within the column will remain untouched.

"},{"location":"built_in_transformers/standard_transformers/random_numeric/","title":"RandomNumeric","text":"

Generate a random numeric within the provided interval.

"},{"location":"built_in_transformers/standard_transformers/random_numeric/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes numeric, decimal min The minimum threshold for the random value. The value range depends on the column type. Yes - max The maximum threshold for the random value. The value range depends on the column type. Yes - decimal The decimal of the random numeric value (number of digits after the decimal point) 4 No - keep_null Indicates whether NULL values should be replaced with transformed values or not true No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_numeric/#dynamic-parameters","title":"Dynamic parameters","text":"Parameter Supported types min int2, int4, int8, float4, float8, numeric, decimal max int2, int4, int8, float4, float8, numeric, decimal"},{"location":"built_in_transformers/standard_transformers/random_numeric/#description","title":"Description","text":"

The RandomNumeric transformer generates a random numeric value within the provided interval, starting from min to max, with the option to specify the number of decimal digits by using the decimal parameter. The behaviour for NULL values can be configured using the keep_null parameter.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_numeric/#example-generate-random-price","title":"Example: Generate random price","text":"

In this example, the RandomNumeric transformer generates random prices in the range from 0.1 to 7000 while maintaining a decimal of up to 2 digits.

RandomNumeric transformer example
- schema: \"sales\"\n  name: \"salesorderdetail\"\n  transformers:\n    - name: \"RandomNumeric\"\n      params:\n        column: \"unitprice\"\n        min: 0.1\n        max: 7000\n        decimal: 2\n
  1. The type overrides applied for example because the playground database does not contain any tables with numeric columns.

Result:

ColumnOriginalValueTransformedValue unitprice2024.9944449.7"},{"location":"built_in_transformers/standard_transformers/random_paragraph/","title":"RandomParagraph","text":"

The RandomParagraph transformer is crafted to populate specified database columns with random paragraphs. This utility is indispensable for applications that require the generation of extensive textual content, such as simulating articles, enhancing textual datasets for NLP systems, or anonymizing textual content in databases.

"},{"location":"built_in_transformers/standard_transformers/random_paragraph/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_paragraph/#description","title":"Description","text":"

Employing sophisticated text generation algorithms or libraries, the RandomParagraph transformer generates random paragraphs, injecting them into the designated database column. This transformer is designed to create varied and plausible paragraphs that simulate real-world textual content, providing a valuable tool for database enrichment, testing, and anonymization.

"},{"location":"built_in_transformers/standard_transformers/random_paragraph/#example-populate-random-paragraphs-for-the-articles-table","title":"Example: Populate random paragraphs for the articles table","text":"

This example illustrates configuring the RandomParagraph transformer to populate the body column in an articles table with random paragraphs. It is an effective way to simulate diverse article content for development, testing, or demonstration purposes.

RandomParagraph transformer example
- schema: \"public\"\n  name: \"articles\"\n  transformers:\n    - name: \"RandomParagraph\"\n      params:\n        column: \"body\"\n        keep_null: false\n

With this setup, the body column will receive random paragraphs for each entry, replacing any existing non-NULL values. Setting the keep_null parameter to true allows for the preservation of existing NULL values within the column, maintaining the integrity of records where article content is not applicable or provided.

"},{"location":"built_in_transformers/standard_transformers/random_password/","title":"RandomPassword","text":"

The RandomPassword transformer is designed to populate specified database columns with random passwords. This utility is vital for applications that require the simulation of secure user data, testing systems with authentication mechanisms, or anonymizing real passwords in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_password/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_password/#description","title":"Description","text":"

Employing sophisticated password generation algorithms or libraries, the RandomPassword transformer injects random passwords into the designated database column. This feature is particularly useful for creating realistic and secure user password datasets for development, testing, or demonstration purposes.

"},{"location":"built_in_transformers/standard_transformers/random_password/#example-populate-random-passwords-for-the-user_accounts-table","title":"Example: Populate random passwords for the user_accounts table","text":"

This example demonstrates how to configure the RandomPassword transformer to populate the password column in the user_accounts table with random passwords.

RandomPassword transformer example
- schema: \"public\"\n  name: \"user_accounts\"\n  transformers:\n    - name: \"RandomPassword\"\n      params:\n        column: \"password\"\n        keep_null: false\n

In this configuration, every entry in the password column will be updated with a random password. Setting the keep_null parameter to true will preserve existing NULL values in the column, accommodating scenarios where password data may not be applicable.

"},{"location":"built_in_transformers/standard_transformers/random_person/","title":"RandomPerson","text":"

The RandomPerson transformer is designed to populate specified database columns with personal attributes such as first name, last name, title and gender.

"},{"location":"built_in_transformers/standard_transformers/random_person/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types columns The name of the column to be affected Yes text, varchar gender set specific gender (possible values: Male, Female, Any) Any No - gender_mapping Specify gender name to possible values when using dynamic mode in \"gender\" parameter Any No - fallback_gender Specify fallback gender if not mapped when using dynamic mode in \"gender\" parameter Any No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_person/#description","title":"Description","text":"

The RandomPerson transformer utilizes a comprehensive list of first names to inject random first names into the designated database column. This feature allows for the creation of diverse and realistic user profiles by simulating a variety of first names without using real user data.

"},{"location":"built_in_transformers/standard_transformers/random_person/#column-object-attributes","title":"column object attributes","text":"
  • name \u2014 the name of the column where the personal attributes will be stored. This value is required.

  • template - the template for the column value. You can use the next attributes: .FirstName, .LastName or .Title. For example, if you want to generate a full name, you can use the next template: \"{{ .FirstName }} {{ .LastName }}\"

  • hashing - the bool value. Indicates whether the column value must be passed through the hashing function. The default value is false. If all column has hashing set to false (by default), then all columns will be hashed.

  • keep_null - the bool value. Indicates whether NULL values should be preserved. The default value is true
"},{"location":"built_in_transformers/standard_transformers/random_person/#gender_mapping-object-attributes","title":"gender_mapping object attributes","text":"

gender_mapping - a dictionary that maps the gender value when gender parameters works in dynamic mode. The default value is:

{\n  \"Male\": [\n    \"male\",\n    \"M\",\n    \"m\",\n    \"man\",\n    \"Man\"\n  ],\n  \"Female\": [\n    \"female\",\n    \"F\",\n    \"f\",\n    \"w\",\n    \"woman\",\n    \"Woman\"\n  ]\n}\n
"},{"location":"built_in_transformers/standard_transformers/random_person/#fallback_gender","title":"fallback_gender","text":"

Gender that will be used if gender_mapping was not found. This parameter is optional and required only for gender parameter in dynamic mode. The default value is Any.

"},{"location":"built_in_transformers/standard_transformers/random_person/#example-populate-random-first-name-and-last-name-for-table-user_profiles-in-static-mode","title":"Example: Populate random first name and last name for table user_profiles in static mode","text":"

This example demonstrates how to use the RandomPerson transformer to populate the name and surname columns in the user_profiles table with random first names, last name, respectively.

Create table user_profiles and insert data
CREATE TABLE personal_data\n(\n    id      SERIAL PRIMARY KEY,\n    name    VARCHAR(100),\n    surname VARCHAR(100),\n    sex     CHAR(1) CHECK (sex IN ('M', 'F'))\n);\n\n-- Insert sample data into the table\nINSERT INTO personal_data (name, surname, sex)\nVALUES ('John', 'Doe', 'M'),\n       ('Jane', 'Smith', 'F'),\n       ('Alice', 'Johnson', 'F'),\n       ('Bob', 'Lee', 'M');\n
RandomPerson transformer example
- schema: public\n  name: personal_data\n  transformers:\n    - name: \"RandomPerson\"\n      params:\n        gender: \"Any\"\n        columns:\n          - name: \"name\"\n            template: \"{{ .FirstName }}\"\n          - name: \"surname\"\n            template: \"{{ .LastName }}\"\n        engine: \"hash\"\n

Result

ColumnOriginalValueTransformedValue nameJohnZane surnameDoeMcCullough"},{"location":"built_in_transformers/standard_transformers/random_person/#example-populate-random-first-name-and-last-name-for-table-user_profiles-in-dynamic-mode","title":"Example: Populate random first name and last name for table user_profiles in dynamic mode","text":"

This example demonstrates how to use the RandomPerson transformer to populate the name, surname using dynamic gender

RandomPerson transformer example with dynamic mode
- schema: public\n  name: personal_data\n  transformers:\n    - name: \"RandomPerson\"\n      params:\n        columns:\n          - name: \"name\"\n            template: \"{{ .FirstName }}\"\n          - name: \"surname\"\n            template: \"{{ .LastName }}\"\n        engine: \"random\"\n      dynamic_params:\n        gender:\n          column: sex\n

Result:

ColumnOriginalValueTransformedValue nameJohnMartin surnameDoeMueller"},{"location":"built_in_transformers/standard_transformers/random_phone_number/","title":"RandomPhoneNumber","text":"

The RandomPhoneNumber transformer is developed to populate specified database columns with random phone numbers. This tool is essential for applications requiring the simulation of contact information, testing phone number validation systems, or anonymizing phone number data in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_phone_number/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_phone_number/#description","title":"Description","text":"

The RandomPhoneNumber transformer utilizes algorithms capable of generating random phone numbers with various formats and injects them into the designated database column. This feature allows for the creation of diverse and realistic contact information in datasets for development, testing, or data anonymization purposes.

"},{"location":"built_in_transformers/standard_transformers/random_phone_number/#example-populate-random-phone-numbers-for-the-contact_information-table","title":"Example: Populate random phone numbers for the contact_information table","text":"

This example demonstrates configuring the RandomPhoneNumber transformer to populate the phone_number column in the contact_information table with random phone numbers. It is an effective method for simulating a variety of contact information entries.

RandomPhoneNumber transformer example
- schema: \"public\"\n  name: \"contact_information\"\n  transformers:\n    - name: \"RandomPhoneNumber\"\n      params:\n        column: \"phone_number\"\n        keep_null: false\n

In this configuration, the phone_number column will be updated with random phone numbers for each contact information entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, ensuring the integrity of records where phone number information is not applicable or provided.

"},{"location":"built_in_transformers/standard_transformers/random_sentence/","title":"RandomSentence","text":"

The RandomSentence transformer is designed to populate specified database columns with random sentences. Ideal for simulating natural language text for user comments, testing NLP systems, or anonymizing textual data in databases.

"},{"location":"built_in_transformers/standard_transformers/random_sentence/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_sentence/#description","title":"Description","text":"

The RandomSentence transformer employs complex text generation algorithms or libraries to generate random sentences, injecting them into a designated database column without the need for specifying sentence length. This flexibility ensures the creation of varied and plausible text for a wide range of applications.

"},{"location":"built_in_transformers/standard_transformers/random_sentence/#example-populate-random-sentences-for-the-comments-table","title":"Example: Populate random sentences for the comments table","text":"

This example shows how to configure the RandomSentence transformer to populate the comment column in the comments table with random sentences. It is a straightforward method for simulating diverse user-generated content.

RandomSentence transformer example
- schema: \"public\"\n  name: \"comments\"\n  transformers:\n    - name: \"RandomSentence\"\n      params:\n        column: \"comment\"\n        keep_null: false\n

In this configuration, the comment column will be updated with random sentences for each entry, replacing any existing non-NULL values. If keep_null is set to true, existing NULL values in the column will be preserved, maintaining the integrity of records where comments are not applicable.

"},{"location":"built_in_transformers/standard_transformers/random_string/","title":"RandomString","text":"

Generate a random string using the provided characters within the specified length range.

"},{"location":"built_in_transformers/standard_transformers/random_string/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar min_length The minimum length of the generated string Yes - max_length The maximum length of the generated string Yes - symbols The range of characters that can be used in the random string abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ No - keep_null Indicates whether NULL values should be replaced with transformed values or not true No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_string/#description","title":"Description","text":"

The RandomString transformer generates a random string with a length between min_length and max_length using the characters specified in the symbols string as the possible set of characters. The behaviour for NULL values can be configured using the keep_null parameter.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_string/#example-generate-a-random-string-for-accountnumber","title":"Example: Generate a random string for accountnumber","text":"

In the following example, a random string is generated for the accountnumber column with a length range from 9 to 12. The character set used for generation includes 1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ.

RandomString transformer example
- schema: \"purchasing\"\n  name: \"vendor\"\n  transformers:\n    - name: \"RandomString\"\n      params:\n        column: \"accountnumber\"\n        min_length: 9\n        max_length: 12\n        symbols: \"1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZ\"\n

Result

ColumnOriginalValueTransformedValue accountnumberAUSTRALI00014VUI6P2OZ"},{"location":"built_in_transformers/standard_transformers/random_timezone/","title":"RandomTimezone","text":"

The RandomTimezone transformer is designed to populate specified database columns with random timezone strings. This transformer is particularly useful for applications that require the simulation of global user data, testing of timezone-related functionalities, or anonymizing real user timezone information in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_timezone/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_timezone/#description","title":"Description","text":"

Utilizing a comprehensive library or algorithm for generating timezone data, the RandomTimezone transformer provides random timezone strings (e. g., \"America/New_York\", \"Europe/London\") for database columns. This feature enables the creation of diverse and realistic datasets by simulating timezone information for user profiles, event timings, or any other data requiring timezone context.

"},{"location":"built_in_transformers/standard_transformers/random_timezone/#example-populate-random-timezone-strings-for-the-user_accounts-table","title":"Example: Populate random timezone strings for the user_accounts table","text":"

This example demonstrates how to configure the RandomTimezone transformer to populate the timezone column in the user_accounts table with random timezone strings, enhancing the dataset with varied global user representations.

RandomTimezone transformer example
- schema: \"public\"\n  name: \"user_accounts\"\n  transformers:\n    - name: \"RandomTimezone\"\n      params:\n        column: \"timezone\"\n        keep_null: false\n

With this configuration, every entry in the timezone column will be updated with a random timezone string, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values within the column will remain unchanged, preserving the integrity of rows without specified timezone data.

"},{"location":"built_in_transformers/standard_transformers/random_toll_free_phone_number/","title":"RandomTollFreePhoneNumber","text":"

The RandomTollFreePhoneNumber transformer is designed to populate specified database columns with random toll-free phone numbers. This tool is essential for applications requiring the simulation of contact information, testing phone number validation systems, or anonymizing phone number data in datasets while focusing on toll-free numbers.

"},{"location":"built_in_transformers/standard_transformers/random_toll_free_phone_number/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_toll_free_phone_number/#description","title":"Description","text":"

The RandomTollFreePhoneNumber transformer utilizes algorithms capable of generating random toll-free phone numbers with various formats and injects them into the designated database column. This feature allows for the creation of diverse and realistic toll-free contact information in datasets for development, testing, or data anonymization purposes.

"},{"location":"built_in_transformers/standard_transformers/random_toll_free_phone_number/#example-populate-random-toll-free-phone-numbers-for-the-contact_information-table","title":"Example: Populate random toll-free phone numbers for the contact_information table","text":"

This example demonstrates configuring the RandomTollFreePhoneNumber transformer to populate the phone_number column in the contact_information table with random toll-free phone numbers. It is an effective method for simulating a variety of contact information entries with toll-free numbers.

RandomTollFreePhoneNumber transformer example
- schema: \"public\"\n  name: \"contact_information\"\n  transformers:\n    - name: \"RandomTollFreePhoneNumber\"\n      params:\n        column: \"phone_number\"\n        keep_null: false\n

In this configuration, the phone_number column will be updated with random toll-free phone numbers for each contact information entry, replacing any existing non-NULL values. If the keep_null parameter is set to true, existing NULL values in the column will be preserved, ensuring the integrity of records where toll-free phone number information is not applicable or provided.

"},{"location":"built_in_transformers/standard_transformers/random_unix_timestamp/","title":"RandomUnixTimestamp","text":"

The RandomUnixTimestamp transformer generates random Unix time values (timestamps) for specified database columns. It is particularly useful for populating columns with timestamp data, simulating time-related data, or anonymizing actual timestamps in a dataset.

"},{"location":"built_in_transformers/standard_transformers/random_unix_timestamp/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes int2, int4, int8 min The minimum threshold date for the random value in unix timestamp format (integer) with sec unit by default Yes - max The maximum threshold date for the random value in unix timestamp format (integer) with sec unit by default Yes - unit Generated unix timestamp value unit. Possible values [second, millisecond, microsecond, nanosecond] second Yes - min_unit Min unix timestamp threshold date unit. Possible values [second, millisecond, microsecond, nanosecond] second Yes - max_unit Min unix timestamp threshold date unit. Possible values [second, millisecond, microsecond, nanosecond] second Yes - keep_null Indicates whether NULL values should be preserved false No - truncate Truncate the date to the specified part (nanosecond, microsecond, millisecond, second, minute, hour, day, month, year). The truncate operation is not applied by default. No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_unix_timestamp/#description","title":"Description","text":"

The RandomUnixTimestamp transformer generates random Unix timestamps within the provided interval, starting from min to max. The min and max parameters are expected to be in Unix timestamp format. The min_unit and max_unit parameters specify the unit of the Unix timestamp threshold date. The truncate parameter allows you to truncate the date to the specified part of the date. The keep_null parameter allows you to specify whether NULL values should be preserved or replaced with transformed values.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_unix_timestamp/#example-generate-random-unix-timestamps-with-dynamic-parameters","title":"Example: Generate random Unix timestamps with dynamic parameters","text":"

In this example, the RandomUnixTimestamp transformer generates random Unix timestamps using dynamic parameters. The min parameter is set to the created_at column, which is converted to Unix seconds using the TimestampToUnixSec. The max parameter is set to a fixed value. The paid_at column is populated with random Unix timestamps in the range from created_at to 1715934239 (Unix timestamp for 2024-05-17 12:03:59). The unit parameter is set to millisecond because the paid_at column stores timestamps in milliseconds.

CREATE TABLE transactions\n(\n    id         SERIAL PRIMARY KEY,\n    kind       VARCHAR(255),\n    total      DECIMAL(10, 2),\n    created_at TIMESTAMP,\n    paid_at    BIGINT -- stores milliseconds since the epoch\n);\n\n-- Inserting data with milliseconds timestamp\nINSERT INTO transactions (kind, total, created_at, paid_at)\nVALUES ('Sale', 199.99, '2023-05-17 12:00:00', (EXTRACT(EPOCH FROM TIMESTAMP '2023-05-17 12:05:00') * 1000)),\n       ('Refund', 50.00, '2023-05-18 15:00:00', (EXTRACT(EPOCH FROM TIMESTAMP '2023-05-18 15:10:00') * 1000)),\n       ('Sale', 129.99, '2023-05-19 10:30:00', (EXTRACT(EPOCH FROM TIMESTAMP '2023-05-19 10:35:00') * 1000));\n
RandomUnixTimestamp transformer example
- schema: \"public\"\n  name: \"transactions\"\n  transformers:\n    - name: \"RandomUnixTimestamp\"\n      params:\n        column: \"paid_at\"\n        max: 1715934239\n        unit: \"millisecond\"\n        min_unit: \"second\"\n        max_unit: \"second\"\n      dynamic_params:\n        min:\n          column: \"created_at\"\n          cast_to: \"TimestampToUnixSec\"\n

Result:

ColumnOriginalValueTransformedValue paid_at16843251000001708919030732"},{"location":"built_in_transformers/standard_transformers/random_unix_timestamp/#example-generate-simple-random-unix-timestamps","title":"Example: Generate simple random Unix timestamps","text":"

In this example, the RandomUnixTimestamp transformer generates random Unix timestamps for the paid_at column in the range from 1615934239 (Unix timestamp for 2021-03-16 12:03:59) to 1715934239 (Unix timestamp for 2024-05-17 12:03:59). The unit parameter is set to millisecond because the paid_at column stores timestamps in milliseconds.

- schema: \"public\"\n  name: \"transactions\"\n  transformers:\n    - name: \"RandomUnixTimestamp\"\n      params:\n        column: \"paid_at\"\n        min: 1615934239\n        max: 1715934239\n        unit: \"millisecond\"\n

Result:

ColumnOriginalValueTransformedValue paid_at16843251000001655768292548"},{"location":"built_in_transformers/standard_transformers/random_url/","title":"RandomURL","text":"

The RandomURL transformer is designed to populate specified database columns with random URL (Uniform Resource Locator) addresses. This tool is highly beneficial for simulating web content, testing applications that require URL input, or anonymizing real web addresses in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_url/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_url/#description","title":"Description","text":"

Utilizing advanced algorithms or libraries for generating URL strings, the RandomURL transformer injects random, plausible URLs into the designated database column. Each generated URL is structured to include the protocol (e. g., \"http://\", \"https://\"), domain name, and path, offering a realistic range of web addresses for various applications.

"},{"location":"built_in_transformers/standard_transformers/random_url/#example-populate-random-urls-for-the-webpages-table","title":"Example: Populate random URLs for the webpages table","text":"

This example illustrates how to configure the RandomURL transformer to populate the page_url column in a webpages table with random URLs, providing a broad spectrum of web addresses for testing or data simulation purposes.

RandomURL transformer example
- schema: \"public\"\n  name: \"webpages\"\n  transformers:\n    - name: \"RandomURL\"\n      params:\n        column: \"page_url\"\n        keep_null: false\n

With this configuration, the page_url column will be filled with random URLs for each entry, replacing any existing non-NULL values. Setting the keep_null parameter to true allows for the preservation of existing NULL values within the column, accommodating scenarios where URL data may be intentionally omitted.

"},{"location":"built_in_transformers/standard_transformers/random_username/","title":"RandomUsername","text":"

The RandomUsername transformer is crafted to populate specified database columns with random usernames. This utility is crucial for applications that require the simulation of user data, testing systems with user login functionality, or anonymizing real usernames in datasets.

"},{"location":"built_in_transformers/standard_transformers/random_username/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_username/#description","title":"Description","text":"

By employing sophisticated algorithms or libraries capable of generating believable usernames, the RandomUsername transformer introduces random usernames into the specified database column. Each generated username is designed to be unique and plausible, incorporating a mix of letters, numbers, and possibly special characters, depending on the generation logic used.

"},{"location":"built_in_transformers/standard_transformers/random_username/#example-populate-random-usernames-for-the-user_accounts-table","title":"Example: Populate random usernames for the user_accounts table","text":"

This example demonstrates configuring the RandomUsername transformer to populate the username column in a user_accounts table with random usernames. This setup is ideal for creating a diverse and realistic user base for development, testing, or demonstration purposes.

RandomUsername transformer example
- schema: \"public\"\n  name: \"user_accounts\"\n  transformers:\n    - name: \"RandomUsername\"\n      params:\n        column: \"username\"\n        keep_null: false\n

In this configuration, every entry in the username column will be updated with a random username, replacing any existing non-NULL values. If the keep_null parameter is set to true, then the transformer will preserve existing NULL values within the column, maintaining data integrity where usernames are not applicable or available.

"},{"location":"built_in_transformers/standard_transformers/random_uuid/","title":"RandomUuid","text":"

Generate random unique user ID using version 4.

"},{"location":"built_in_transformers/standard_transformers/random_uuid/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar, uuid keep_null Indicates whether NULL values should be replaced with transformed values or not true No - engine The engine used for generating the values [random, hash]. Use hash for deterministic generation random No -"},{"location":"built_in_transformers/standard_transformers/random_uuid/#description","title":"Description","text":"

The RandomUuid transformer generates a random UUID. The behaviour for NULL values can be configured using the keep_null parameter.

The engine parameter allows you to choose between random and hash engines for generating values. Read more about the engines in the Transformation engines section.

"},{"location":"built_in_transformers/standard_transformers/random_uuid/#example-updating-the-rowguid-column","title":"Example: Updating the rowguid column","text":"

The following example replaces original UUID values of the rowguid column to randomly generated ones.

RandomUuid transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n  - name: \"RandomUuid\"\n    params:\n      column: \"rowguid\"\n      keep_null: false\n

Result

ColumnOriginalValueTransformedValue rowguidf01251e5-96a3-448d-981e-0f99d789110d8ed8c4b2-7e7a-1e8d-f0f0-768e0e8ed0d0"},{"location":"built_in_transformers/standard_transformers/random_word/","title":"RandomWord","text":"

The RandomWord transformer populates specified database columns with random words. Ideal for simulating textual content, enhancing linguistic datasets, or anonymizing text in databases.

"},{"location":"built_in_transformers/standard_transformers/random_word/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_word/#description","title":"Description","text":"

The RandomWord transformer employs a mechanism to inject random words into a designated database column, supporting the generation of linguistically plausible and contextually diverse text. This transformer is particularly beneficial for creating rich text datasets for development, testing, or educational purposes without specifying the language, focusing on versatility and ease of use.

"},{"location":"built_in_transformers/standard_transformers/random_word/#example-populate-random-words-for-the-content-table","title":"Example: Populate random words for the content table","text":"

This example demonstrates configuring the RandomWord transformer to populate the tag column in the content table with random words. It is a straightforward approach to adding varied textual data for tagging or content categorization.

RandomWord transformer example
- schema: \"public\"\n  name: \"content\"\n  transformers:\n    - name: \"RandomWord\"\n      params:\n        column: \"tag\"\n        keep_null: false\n

In this setup, the tag column will be updated with random words for each entry, replacing any existing non-NULL values. If keep_null is set to true, existing NULL values in the column will remain unchanged, maintaining data integrity for records where textual data is not applicable.

"},{"location":"built_in_transformers/standard_transformers/random_year_string/","title":"RandomYearString","text":"

The RandomYearString transformer is designed to populate specified database columns with random year strings. It is ideal for scenarios that require the representation of years without specific dates, such as manufacturing years of products, birth years of users, or any other context where only the year is relevant.

"},{"location":"built_in_transformers/standard_transformers/random_year_string/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar, int2, int4, int8, numeric keep_null Indicates whether NULL values should be preserved false No -"},{"location":"built_in_transformers/standard_transformers/random_year_string/#description","title":"Description","text":"

The RandomYearString transformer leverages the faker library to generate strings representing random years. This allows for the easy generation of year data in a string format, adding versatility and realism to datasets that need to simulate or anonymize year-related information.

"},{"location":"built_in_transformers/standard_transformers/random_year_string/#example-populate-random-year-strings-for-the-products-table","title":"Example: Populate random year strings for the products table","text":"

This example shows how to use the RandomYearString transformer to fill the manufacturing_year column in the products table with random year strings, simulating the diversity of manufacturing dates.

RandomYearString transformer example
- schema: \"public\"\n  name: \"products\"\n  transformers:\n    - name: \"RandomYearString\"\n      params:\n        column: \"manufacturing_year\"\n        keep_null: false\n

In this configuration, the manufacturing_year column will be populated with random year strings, replacing any existing non-NULL values. If keep_null is set to true, then existing NULL values in the column will be preserved.

"},{"location":"built_in_transformers/standard_transformers/real_address/","title":"RealAddress","text":"

Generates real addresses for specified database columns using the faker library. It supports customization of the generated address format through Go templates.

"},{"location":"built_in_transformers/standard_transformers/real_address/#parameters","title":"Parameters","text":"Name Properties Description Default Required Supported DB types columns Specifies the affected column names along with additional properties for each column Yes Various \u221f name The name of the column to be affected Yes string \u221f template A Go template string for formatting real address attributes Yes string \u221f keep_null Indicates whether NULL values should be preserved No bool"},{"location":"built_in_transformers/standard_transformers/real_address/#template-value-descriptions","title":"Template value descriptions","text":"

The template parameter allows for the injection of real address attributes into a customizable template. The following values can be included in your template:

  • {{.Address}} \u2014 street address or equivalent
  • {{.City}} \u2014 city name
  • {{.State}} \u2014 state, province, or equivalent region name
  • {{.PostalCode}} \u2014 postal or ZIP code
  • {{.Latitude}} \u2014 geographic latitude
  • {{.Longitude}} \u2014 geographic longitude

These placeholders can be combined and formatted as desired within the template string to generate custom address formats.

"},{"location":"built_in_transformers/standard_transformers/real_address/#description","title":"Description","text":"

The RealAddress transformer uses the faker library to generate realistic addresses, which can then be formatted according to a specified template and applied to selected columns in a database. It allows for the generated addresses to replace existing values or to preserve NULL values, based on the transformer's configuration.

"},{"location":"built_in_transformers/standard_transformers/real_address/#example-generate-real-addresses-for-the-employee-table","title":"Example: Generate Real addresses for the employee table","text":"

This example shows how to configure the RealAddress transformer to generate real addresses for the address column in the employee table, using a custom format.

RealAddress transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n    - name: \"RealAddress\"\n      params:\n        columns:\n          - name: \"address\"\n            template: \"{{.Address}}, {{.City}}, {{.State}} {{.PostalCode}}\"\n            keep_null: false\n

This configuration will generate real addresses with the format \"Street address, city, state postal code\" and apply them to the address column, replacing any existing non-NULL values.

"},{"location":"built_in_transformers/standard_transformers/regexp_replace/","title":"RegexpReplace","text":"

Replace a string using a regular expression.

"},{"location":"built_in_transformers/standard_transformers/regexp_replace/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes text, varchar regexp The regular expression pattern to search for in the column's value Yes - replace The replacement value. This value may be replaced with a captured group from the regexp parameter. Yes -"},{"location":"built_in_transformers/standard_transformers/regexp_replace/#description","title":"Description","text":"

The RegexpReplace transformer replaces a string according to the applied regular expression. The valid regular expressions syntax is the same as the general syntax used by Perl, Python, and other languages. To be precise, it is the syntax accepted by RE2 and described in the Golang documentation, except for \\C.

"},{"location":"built_in_transformers/standard_transformers/regexp_replace/#example-removing-leading-prefix-from-loginid-column-value","title":"Example: Removing leading prefix from loginid column value","text":"

In the following example, the original values from loginid matching the adventure-works\\{{ id_name }} format are replaced with {{ id_name }}.

RegexpReplace transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n  - name: \"RegexpReplace\"\n    params:\n      column: \"loginid\"\n      regexp: \"adventure-works\\\\\\\\(.*)\"\n      replace: \"$1\"\n
Expected result
| column name | original value       | transformed |\n|-------------|----------------------|-------------|\n| loginid     | adventure-works\\ken0 | ken0        |\n

Note

YAML has control symbols, and using them without escaping may result in an error. In the example above, the prefix of id is separated by the \\ symbol. Since this symbol is a control symbol, we must escape it using \\\\. However, the '\\' symbol is also a control symbol for regular expressions, which is why we need to double-escape it as \\\\\\\\.

"},{"location":"built_in_transformers/standard_transformers/replace/","title":"Replace","text":"

Replace an original value by the provided one.

"},{"location":"built_in_transformers/standard_transformers/replace/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes any replace The value to replace Yes - keep_null Indicates whether NULL values should be replaced with transformed values or not true No - validate Performs a decoding procedure via the PostgreSQL driver using the column type to ensure that values have correct type true No -"},{"location":"built_in_transformers/standard_transformers/replace/#description","title":"Description","text":"

The Replace transformer replace an original value from the specified column with the provided one. It can optionally run a validation check with the validate parameter to ensure that the values are of a correct type before starting transformation. The behaviour for NULL values can be configured using the keep_null parameter.

"},{"location":"built_in_transformers/standard_transformers/replace/#example-updating-the-jobtitle-column","title":"Example: Updating the jobtitle column","text":"

In the following example, the provided value: \"programmer\" is first validated through driver decoding. If the current value of the jobtitle column is not NULL, it will be replaced with programmer. If the current value is NULL, it will remain NULL.

Replace transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformers:\n  - name: \"Replace\"\n    params:\n      column: \"jobtitle\"\n      value: \"programmer\"\n      keep_null: false\n      validate: true\n
Expected result
| column name | original value          | transformed |\n|-------------|-------------------------|-------------|\n| jobtitle    | Chief Executive Officer | programmer  |\n
"},{"location":"built_in_transformers/standard_transformers/set_null/","title":"SetNull","text":"

Set NULL value to a column.

"},{"location":"built_in_transformers/standard_transformers/set_null/#parameters","title":"Parameters","text":"Name Description Default Required Supported DB types column The name of the column to be affected Yes any"},{"location":"built_in_transformers/standard_transformers/set_null/#description","title":"Description","text":"

The SetNull transformer assigns NULL value to a column. This transformer generates warning if the affected column has NOT NULL constraint.

NULL constraint violation warning
{\n  \"hash\": \"5a229ee964a4ba674a41a4d63dab5a8c\",\n  \"meta\": {\n    \"ColumnName\": \"jobtitle\",\n    \"ConstraintType\": \"NotNull\",\n    \"ParameterName\": \"column\",\n    \"SchemaName\": \"humanresources\",\n    \"TableName\": \"employee\",\n    \"TransformerName\": \"SetNull\"\n  },\n  \"msg\": \"transformer may produce NULL values but column has NOT NULL constraint\",\n  \"severity\": \"warning\"\n}\n
"},{"location":"built_in_transformers/standard_transformers/set_null/#example-set-null-value-to-updated_at-column","title":"Example: Set NULL value to updated_at column","text":"SetNull transformer example
- schema: \"humanresources\"\n  name: \"employee\"\n  transformation:\n    - name: \"SetNull\"\n      params:\n        column: \"jobtitle\"\n
Expected result
| column name | original value          | transformed |\n|-------------|-------------------------|-------------|\n| jobtitle    | Chief Executive Officer | NULL        |\n
"},{"location":"commands/","title":"Commands","text":""},{"location":"commands/#introduction","title":"Introduction","text":"Greenmask available commands
greenmask \\\n--log-format=[json|text] \\\n--log-level=[debug|info|error] \\\n--config=config.yml \\\n[dump|list-dumps|delete|list-transformers|show-transformer|restore|show-dump]`\n

You can use the following commands within Greenmask:

  • list-transformers \u2014 displays a list of available transformers along with their documentation
  • show-transformer \u2014 displays information about the specified transformer
  • validate - performs a validation procedure by testing config, comparing transformed data, identifying potential issues, and checking for schema changes.
  • dump \u2014 initiates the data dumping process
  • restore \u2014 restores data to the target database either by specifying a dumpId or using the latest available dump
  • list-dumps \u2014 lists all available dumps stored in the system
  • show-dump \u2014 provides metadata information about a particular dump, offering insights into its structure and attributes
  • delete \u2014 deletes a specific dump from the storage

For any of the commands mentioned above, you can include the following common flags:

  • --log-format \u2014 specifies the desired format for log output, which can be either json or text. This parameter is optional, with the default format set to text.
  • --log-level \u2014 sets the desired level for log output, which can be one of debug, info, or error. This parameter is optional, with the default log level being info.
  • --config \u2014 requires the specification of a configuration file in YAML format. This configuration file is mandatory for Greenmask to operate correctly.
  • --help \u2014 displays comprehensive help information for Greenmask, providing guidance on its usage and available commands.
"},{"location":"commands/delete/","title":"delete command","text":"

Delete dump from the storage with a specific ID

Supported flags
Usage:\n  greenmask delete [flags] [dumpId]\n\nFlags:\n      --before-date string   delete dumps older than the specified date in RFC3339Nano format: 2021-01-01T00:00.0:00Z\n      --dry-run              do not delete anything, just show what would be deleted\n      --prune-failed         prune failed dumps\n      --prune-unsafe         prune dumps with \"unknown-or-failed\" statuses. Works only with --prune-failed\n      --retain-for string    retain dumps for the specified duration in format: 1w2d3h4m5s6ms7us8ns\n      --retain-recent int    retain the most recent N completed dumps (default -1)\n
delete dump by id
greenmask --config config.yml delete 1723643249862\n
delete dumps older than the specified date
greenmask --config config.yml delete --before-date 2021-01-01T00:00.0:00Z --dry-run \n
prune failed dumps
greenmask --config config.yml delete --prune-failed --dry-run \n
prune dumps with 'unknown-or-failed' statuses
greenmask --config config.yml delete --prune-failed --prune-unsafe --dry-run\n
retain dumps for the specified duration
greenmask --config config.yml delete --retain-for 1w5d --dry-run\n
retain the most recent N completed dumps
greenmask --config config.yml delete --retain-recent 5 --dry-run\n
"},{"location":"commands/dump/","title":"dump","text":""},{"location":"commands/dump/#dump-command","title":"dump command","text":"

The dump command operates in the following way:

  1. Dumps the data from the source database.
  2. Validates the data for potential issues.
  3. Applies the defined transformations.
  4. Stores the transformed data in the specified storage location.

Note that the dump command shares the same parameters and environment variables as pg_dump, allowing you to configure the restoration process as needed.

Mostly it supports the same flags as the pg_dump utility, with some extra flags for Greenmask-specific features.

Supported flags
  -b, --blobs                           include large objects in dump\n  -c, --clean                           clean (drop) database objects before recreating\n  -Z, --compress int                    compression level for compressed formats (default -1)\n  -C, --create                          include commands to create database in dump\n  -a, --data-only                       dump only the data, not the schema\n  -d, --dbname string                   database to dump (default \"postgres\")\n      --disable-dollar-quoting          disable dollar quoting, use SQL standard quoting\n      --disable-triggers                disable triggers during data-only restore\n      --enable-row-security             enable row security (dump only content user has access to)\n  -E, --encoding string                 dump the data in encoding ENCODING\n  -N, --exclude-schema strings          dump the specified schema(s) only\n  -T, --exclude-table strings           do NOT dump the specified table(s)\n      --exclude-table-data strings      do NOT dump data for the specified table(s)\n  -e, --extension strings               dump the specified extension(s) only\n      --extra-float-digits string       override default setting for extra_float_digits\n  -f, --file string                     output file or directory name\n  -h, --host string                     database server host or socket directory (default \"/var/run/postgres\")\n      --if-exists                       use IF EXISTS when dropping objects\n      --include-foreign-data strings    use IF EXISTS when dropping objects\n  -j, --jobs int                        use this many parallel jobs to dump (default 1)\n      --load-via-partition-root         load partitions via the root table\n      --lock-wait-timeout int           fail after waiting TIMEOUT for a table lock (default -1)\n  -B, --no-blobs                        exclude large objects in dump\n      --no-comments                     do not dump comments\n  -O, --no-owner string                 skip restoration of object ownership in plain-text format\n  -X, --no-privileges                   do not dump privileges (grant/revoke)\n      --no-publications                 do not dump publications\n      --no-security-labels              do not dump security label assignments\n      --no-subscriptions                do not dump subscriptions\n      --no-sync                         do not wait for changes to be written safely to dis\n      --no-synchronized-snapshots       do not use synchronized snapshots in parallel jobs\n      --no-tablespaces                  do not dump tablespace assignments\n      --no-toast-compression            do not dump TOAST compression methods\n      --no-unlogged-table-data          do not dump unlogged table data\n      --pgzip                           use pgzip compression instead of gzip\n  -p, --port int                        database server port number (default 5432)\n      --quote-all-identifiers           quote all identifiers, even if not key words\n  -n, --schema strings                  dump the specified schema(s) only\n  -s, --schema-only string              dump only the schema, no data\n      --section string                  dump named section (pre-data, data, or post-data)\n      --serializable-deferrable         wait until the dump can run without anomalies\n      --snapshot string                 use given snapshot for the dump\n      --strict-names                    require table and/or schema include patterns to match at least one entity each\n  -S, --superuser string                superuser user name to use in plain-text format\n  -t, --table strings                   dump the specified table(s) only\n      --test string                     connect as specified database user (default \"postgres\")\n      --use-set-session-authorization   use SET SESSION AUTHORIZATION commands instead of ALTER OWNER commands to set ownership\n  -U, --username string                 connect as specified database user (default \"postgres\")\n  -v, --verbose string                  verbose mode\n
"},{"location":"commands/dump/#pgzip-compression","title":"Pgzip compression","text":"

By default, Greenmask uses gzip compression to restore data. In mist cases it is quite slow and does not utilize all available resources and is a bootleneck for IO operations. To speed up the restoration process, you can use the --pgzip flag to use pgzip compression instead of gzip. This method splits the data into blocks, which are compressed in parallel, making it ideal for handling large volumes of data. The output remains a standard gzip file.

"},{"location":"commands/list-dumps/","title":"list-dumps","text":""},{"location":"commands/list-dumps/#list-dumps-command","title":"list-dumps command","text":"

The list-dumps command provides a list of all dumps stored in the storage. The list includes the following attributes:

  • ID \u2014 the unique identifier of the dump, used for operations like restore, delete, and show-dump
  • DATE \u2014 the date when the snapshot was created
  • DATABASE \u2014 the name of the database associated with the dump
  • SIZE \u2014 the original size of the dump
  • COMPRESSED SIZE \u2014 the size of the dump after compression
  • DURATION \u2014 the duration of the dump procedure
  • TRANSFORMED \u2014 indicates whether the dump has been transformed
  • STATUS \u2014 the status of the dump, which can be one of the following:
    • done \u2014 the dump was completed successfully
    • in progress \u2014 the dump is currently being created
    • failed \u2014 the dump creation process failed
    • unknown or failed \u2014 the deprecated status of the dump that is used for failed dumps or dumps in progress for version v0.1.14 and earlier

Example of list-dumps output:

Info

Greenmask uses a heartbeat mechanism to determine the status of a dump. A dump is considered failed if it lacks a \"done\" heartbeat or if the last heartbeat timestamp exceeds 30 minutes. Heartbeats are recorded every 15 minutes by the dump command while it is in progress. If greenmask fails unexpectedly, the heartbeat stops being updated, and after 30 minutes (twice the interval), the dump is classified as failed. The in progress status indicates that a dump is still ongoing.

"},{"location":"commands/list-transformers/","title":"list-transformers","text":""},{"location":"commands/list-transformers/#list-transformers-command","title":"list-transformers command","text":"

The list-transformers command provides a list of all the allowed transformers, including both standard and advanced transformers. This list can be helpful for searching for an appropriate transformer for your data transformation needs.

To show a list of available transformers, use the following command:

greenmask --config=config.yml list-transformers\n

Supported flags:

  • --format \u2014 allows to select the output format. There are two options available: text or json. The default setting is text.

Example of list-transformers output:

When using the list-transformers command, you receive a list of available transformers with essential information about each of them. Below are the key parameters for each transformer:

  • NAME \u2014 the name of the transformer
  • DESCRIPTION \u2014 a brief description of what the transformer does
  • COLUMN PARAMETER NAME \u2014 name of a column or columns affected by transformation
  • SUPPORTED TYPES \u2014 list the supported value types

The JSON call greenmask --config=config.yml list-transformers --format=json has the same attributes:

JSON format output
[\n  {\n    \"name\": \"Cmd\",\n    \"description\": \"Transform data via external program using stdin and stdout interaction\",\n    \"parameters\": [\n      {\n        \"name\": \"columns\",\n        \"supported_types\": [\n          \"any\"\n        ]\n      }\n    ]\n  },\n  {\n    \"name\": \"Dict\",\n    \"description\": \"Replace values matched by dictionary keys\",\n    \"parameters\": [\n      {\n        \"name\": \"column\",\n        \"supported_types\": [\n          \"any\"\n        ]\n      }\n    ]\n  }\n]\n
"},{"location":"commands/restore/","title":"restore","text":""},{"location":"commands/restore/#restore-command","title":"restore command","text":"

The restore command is used to restore a database from a previously created dump. You can specify the dump to restore by providing the dump ID or use the latest keyword to restore the latest completed dump.

greenmask --config=config.yml restore DUMP_ID\n

Alternatively, to restore the latest completed dump, use the following command:

greenmask --config=config.yml restore latest\n

Note that the restore command shares the same parameters and environment variables as pg_restore, allowing you to configure the restoration process as needed.

Mostly it supports the same flags as the pg_restore utility, with some extra flags for Greenmask-specific features.

Supported flags
      --batch-size int                  the number of rows to insert in a single batch during the COPY command (0 - all rows will be inserted in a single batch)\n  -c, --clean                           clean (drop) database objects before recreating\n  -C, --create                          create the target database\n  -a, --data-only                       restore only the data, no schema\n  -d, --dbname string                   connect to database name (default \"postgres\")\n      --disable-triggers                disable triggers during data-only restore\n      --enable-row-security             enable row security\n  -N, --exclude-schema strings          do not restore objects in this schema\n  -e, --exit-on-error                   exit on error, default is to continue\n  -f, --file string                     output file name (- for stdout)\n  -P, --function strings                restore named function\n  -h, --host string                     database server host or socket directory (default \"/var/run/postgres\")\n      --if-exists                       use IF EXISTS when dropping objects\n  -i, --index strings                   restore named index\n      --inserts                         restore data as INSERT commands, rather than COPY\n  -j, --jobs int                        use this many parallel jobs to restore (default 1)\n      --list-format string              use table of contents in format of text, json or yaml (default \"text\")\n      --no-comments                     do not restore comments\n      --no-data-for-failed-tables       do not restore data of tables that could not be created\n  -O, --no-owner string                 skip restoration of object ownership\n  -X, --no-privileges                   skip restoration of access privileges (grant/revoke)\n      --no-publications                 do not restore publications\n      --no-security-labels              do not restore security labels\n      --no-subscriptions                ddo not restore subscriptions\n      --no-table-access-method          do not restore table access methods\n      --no-tablespaces                  do not restore tablespace assignments\n      --on-conflict-do-nothing          add ON CONFLICT DO NOTHING to INSERT commands\n      --overriding-system-value         use OVERRIDING SYSTEM VALUE clause for INSERTs\n      --pgzip                           use pgzip decompression instead of gzip\n  -p, --port int                        database server port number (default 5432)\n      --restore-in-order                restore tables in topological order, ensuring that dependent tables are not restored until the tables they depend on have been restored\n  -n, --schema strings                  restore only objects in this schema\n  -s, --schema-only                     restore only the schema, no data\n      --section string                  restore named section (pre-data, data, or post-data)\n  -1, --single-transaction              restore as a single transaction\n      --strict-names                    restore named section (pre-data, data, or post-data) match at least one entity each\n  -S, --superuser string                superuser user name to use for disabling triggers\n  -t, --table strings                   restore named relation (table, view, etc.)\n  -T, --trigger strings                 restore named trigger\n  -L, --use-list string                 use table of contents from this file for selecting/ordering output\n      --use-set-session-authorization   use SET SESSION AUTHORIZATION commands instead of ALTER OWNER commands to set ownership\n  -U, --username string                 connect as specified database user (default \"postgres\")\n  -v, --verbose string                  verbose mode\n
"},{"location":"commands/restore/#extra-features","title":"Extra features","text":""},{"location":"commands/restore/#inserts-and-error-handling","title":"Inserts and error handling","text":"

Warning

Insert commands are a lot slower than COPY commands. Use this feature only when necessary.

By default, Greenmask restores data using the COPY command. If you prefer to restore data using INSERT commands, you can use the --inserts flag. This flag allows you to manage errors that occur during the execution of INSERT commands. By configuring an error and constraint exclusion list in the config, you can skip certain errors and continue inserting subsequent rows from the dump.

This can be useful when adding new records to an existing dump, but you don't want the process to stop if some records already exist in the database or violate certain constraints.

By adding the --on-conflict-do-nothing flag, it generates INSERT statements with the ON CONFLICT DO NOTHING clause, similar to the original pg_dump option. However, this approach only works for unique or exclusion constraints. If a foreign key is missing in the referenced table or any other constraint is violated, the insertion will still fail. To handle these issues, you can define anexclusion list in the config.

example with inserts and error handling
```shell title=\"example with inserts and on conflict do nothing\"\ngreenmask --config=config.yml restore DUMP_ID --inserts --on-conflict-do-nothing\n

By adding the --overriding-system-value flag, it generates INSERT statements with the OVERRIDING SYSTEM VALUE clause, which allows you to insert data into identity columns.

example of GENERATED ALWAYS AS IDENTITY column
CREATE TABLE people (\n    id integer GENERATED ALWAYS AS IDENTITY PRIMARY KEY,\n    generated text GENERATED ALWAYS AS (id || first_name) STORED,\n    first_name text\n);\n
example with inserts
greenmask --config=config.yml restore DUMP_ID --inserts --overriding-system-value\n
"},{"location":"commands/restore/#restoration-in-topological-order","title":"Restoration in topological order","text":"

By default, Greenmask restores tables in the order they are listed in the dump file. To restore tables in topological order, use the --restore-in-order flag. This flag ensures that dependent tables are not restored until the tables they depend on have been restored.

This is useful when you have the schema already created with foreign keys and other constraints, and you want to insert data into the tables in the correct order or catch-up the target database with the new data.

Warning

Greenmask cannot guarantee restoration in topological order when the schema contains cycles. The only way to restore tables with cyclic dependencies is to temporarily remove the foreign key constraint (to break the cycle), restore the data, and then re-add the foreign key constraint once the data restoration is complete.

If your database has cyclic dependencies you will be notified about it but the restoration will continue.

2024-08-16T21:39:50+03:00 WRN cycle between tables is detected: cannot guarantee the order of restoration within cycle cycle=[\"public.employees\",\"public.departments\",\"public.projects\",\"public.employees\"]\n
"},{"location":"commands/restore/#pgzip-decompression","title":"Pgzip decompression","text":"

By default, Greenmask uses gzip decompression to restore data. In mist cases it is quite slow and does not utilize all available resources and is a bootleneck for IO operations. To speed up the restoration process, you can use the --pgzip flag to use pgzip decompression instead of gzip. This method splits the data into blocks, which are decompressed in parallel, making it ideal for handling large volumes of data.

example with pgzip decompression
greenmask --config=config.yml restore latest --pgzip\n
"},{"location":"commands/restore/#restore-data-batching","title":"Restore data batching","text":"

The COPY command returns the error only on transaction commit. This means that if you have a large dump and an error occurs, you will have to wait until the end of the transaction to see the error message. To avoid this, you can use the --batch-size flag to specify the number of rows to insert in a single batch during the COPY command. If an error occurs during the batch insertion, the error message will be displayed immediately. The data will be committed only if all batches are inserted successfully.

This is useful when you want to be notified of errors as immediately as possible without waiting for the entire table to be restored.

Warning

The batch size should be chosen carefully. If the batch size is too small, the restoration process will be slow. If the batch size is too large, you may not be able to identify the error row.

In the example below, the batch size is set to 1000 rows. This means that 1000 rows will be inserted in a single batch, so you will be notified of any errors immediately after each batch is inserted.

example with batch size
greenmask --config=config.yml restore latest --batch-size 1000\n
"},{"location":"commands/show-dump/","title":"show-dump","text":""},{"location":"commands/show-dump/#show-dump-command","title":"show-dump command","text":"

This command provides details about all objects and data that can be restored, similar to the pg_restore -l command in PostgreSQL. It helps you inspect the contents of the dump before performing the actual restoration.

Parameters:

  • --format \u2014 format of printing. Can be text or json.

To display metadata information about a dump, use the following command:

greenmask --config=config.yml show-dump dumpID\n
Text output example 
;\n; Archive created at 2023-10-30 12:52:38 UTC\n; dbname: demo\n; TOC Entries: 17\n; Compression: -1\n; Dump Version: 15.4\n; Format: DIRECTORY\n; Integer: 4 bytes\n; Offset: 8 bytes\n; Dumped from database version: 15.4\n; Dumped by pg_dump version: 15.4\n;\n;\n; Selected TOC Entries:\n;\n3444; 0 0 ENCODING - ENCODING\n3445; 0 0 STDSTRINGS - STDSTRINGS\n3446; 0 0 SEARCHPATH - SEARCHPATH\n3447; 1262 24970 DATABASE - demo postgres\n3448; 0 0 DATABASE PROPERTIES - demo postgres\n222; 1259 24999 TABLE bookings flights postgres\n223; 1259 25005 SEQUENCE bookings flights_flight_id_seq postgres\n3460; 0 0 SEQUENCE OWNED BY bookings flights_flight_id_seq postgres\n3281; 2604 25030 DEFAULT bookings flights flight_id postgres\n3462; 0 24999 TABLE DATA bookings flights postgres\n3289; 2606 25044 CONSTRAINT bookings flights flights_flight_no_scheduled_departure_key postgres\n3291; 2606 25046 CONSTRAINT bookings flights flights_pkey postgres\n3287; 1259 42848 INDEX bookings flights_aircraft_code_status_idx postgres\n3292; 1259 42847 INDEX bookings flights_status_aircraft_code_idx postgres\n3293; 2606 25058 FK CONSTRAINT bookings flights flights_aircraft_code_fkey postgres\n3294; 2606 25063 FK CONSTRAINT bookings flights flights_arrival_airport_fkey postgres\n3295; 2606 25068 FK CONSTRAINT bookings flights flights_departure_airport_fkey postgres\n
JSON output example 

{\n  \"startedAt\": \"2023-10-29T20:50:19.948017+02:00\", // (1)\n  \"completedAt\": \"2023-10-29T20:50:22.19333+02:00\", // (2)\n  \"originalSize\": 4053842, // (3)\n  \"compressedSize\": 686557, // (4)\n  \"transformers\": [ // (5)\n    {\n      \"Schema\": \"bookings\", // (6)\n      \"Name\": \"flights\", // (7)\n      \"Query\": \"\", // (8)\n      \"Transformers\": [ // (9)\n        {\n          \"Name\": \"RandomDate\", // (10)\n          \"Params\": { // (11)\n            \"column\": \"c2NoZWR1bGVkX2RlcGFydHVyZQ==\",\n            \"max\": \"MjAyMy0wMS0wMiAwMDowMDowMC4wKzAz\",\n            \"min\": \"MjAyMy0wMS0wMSAwMDowMDowMC4wKzAz\"\n          }\n        }\n      ],\n      \"ColumnsTypeOverride\": null // (12)\n    }\n  ],\n  \"header\": { // (13)\n    \"creationDate\": \"2023-10-29T20:50:20+02:00\",\n    \"dbName\": \"demo\",\n    \"tocEntriesCount\": 15,\n    \"dumpVersion\": \"16.0 (Homebrew)\",\n    \"format\": \"TAR\",\n    \"integer\": 4,\n    \"offset\": 8,\n    \"dumpedFrom\": \"16.0 (Debian 16.0-1.pgdg120+1)\",\n    \"dumpedBy\": \"16.0 (Homebrew)\",\n    \"tocFileSize\": 8090,\n    \"compression\": 0\n  },\n  \"entries\": [ // (14)\n    {\n      \"dumpId\": 3416,\n      \"databaseOid\": 0,\n      \"objectOid\": 0,\n      \"objectType\": \"ENCODING\",\n      \"schema\": \"\",\n      \"name\": \"ENCODING\",\n      \"owner\": \"\",\n      \"section\": \"PreData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": null\n    },\n    {\n      \"dumpId\": 3417,\n      \"databaseOid\": 0,\n      \"objectOid\": 0,\n      \"objectType\": \"STDSTRINGS\",\n      \"schema\": \"\",\n      \"name\": \"STDSTRINGS\",\n      \"owner\": \"\",\n      \"section\": \"PreData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": null\n    },\n    {\n      \"dumpId\": 3418,\n      \"databaseOid\": 0,\n      \"objectOid\": 0,\n      \"objectType\": \"SEARCHPATH\",\n      \"schema\": \"\",\n      \"name\": \"SEARCHPATH\",\n      \"owner\": \"\",\n      \"section\": \"PreData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": null\n    },\n    {\n      \"dumpId\": 3419,\n      \"databaseOid\": 16384,\n      \"objectOid\": 1262,\n      \"objectType\": \"DATABASE\",\n      \"schema\": \"\",\n      \"name\": \"demo\",\n      \"owner\": \"postgres\",\n      \"section\": \"PreData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": null\n    },\n    {\n      \"dumpId\": 3420,\n      \"databaseOid\": 0,\n      \"objectOid\": 0,\n      \"objectType\": \"DATABASE PROPERTIES\",\n      \"schema\": \"\",\n      \"name\": \"demo\",\n      \"owner\": \"postgres\",\n      \"section\": \"PreData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": null\n    },\n    {\n      \"dumpId\": 222,\n      \"databaseOid\": 16414,\n      \"objectOid\": 1259,\n      \"objectType\": \"TABLE\",\n      \"schema\": \"bookings\",\n      \"name\": \"flights\",\n      \"owner\": \"postgres\",\n      \"section\": \"PreData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": null\n    },\n    {\n      \"dumpId\": 223,\n      \"databaseOid\": 16420,\n      \"objectOid\": 1259,\n      \"objectType\": \"SEQUENCE\",\n      \"schema\": \"bookings\",\n      \"name\": \"flights_flight_id_seq\",\n      \"owner\": \"postgres\",\n      \"section\": \"PreData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": [\n        222\n      ]\n    },\n    {\n      \"dumpId\": 3432,\n      \"databaseOid\": 0,\n      \"objectOid\": 0,\n      \"objectType\": \"SEQUENCE OWNED BY\",\n      \"schema\": \"bookings\",\n      \"name\": \"flights_flight_id_seq\",\n      \"owner\": \"postgres\",\n      \"section\": \"PreData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": [\n        223\n      ]\n    },\n    {\n      \"dumpId\": 3254,\n      \"databaseOid\": 16445,\n      \"objectOid\": 2604,\n      \"objectType\": \"DEFAULT\",\n      \"schema\": \"bookings\",\n      \"name\": \"flights flight_id\",\n      \"owner\": \"postgres\",\n      \"section\": \"PreData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": [\n        223,\n        222\n      ]\n    },\n    {\n      \"dumpId\": 3434,\n      \"databaseOid\": 16414,\n      \"objectOid\": 0,\n      \"objectType\": \"TABLE DATA\",\n      \"schema\": \"\\\"bookings\\\"\",\n      \"name\": \"\\\"flights\\\"\",\n      \"owner\": \"\\\"postgres\\\"\",\n      \"section\": \"Data\",\n      \"originalSize\": 4045752,\n      \"compressedSize\": 678467,\n      \"fileName\": \"3434.dat.gz\",\n      \"dependencies\": []\n    },\n    {\n      \"dumpId\": 3261,\n      \"databaseOid\": 16461,\n      \"objectOid\": 2606,\n      \"objectType\": \"CONSTRAINT\",\n      \"schema\": \"bookings\",\n      \"name\": \"flights flights_flight_no_scheduled_departure_key\",\n      \"owner\": \"postgres\",\n      \"section\": \"PostData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": [\n        222,\n        222\n      ]\n    },\n    {\n      \"dumpId\": 3263,\n      \"databaseOid\": 16463,\n      \"objectOid\": 2606,\n      \"objectType\": \"CONSTRAINT\",\n      \"schema\": \"bookings\",\n      \"name\": \"flights flights_pkey\",\n      \"owner\": \"postgres\",\n      \"section\": \"PostData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": [\n        222\n      ]\n    },\n    {\n      \"dumpId\": 3264,\n      \"databaseOid\": 16477,\n      \"objectOid\": 2606,\n      \"objectType\": \"FK CONSTRAINT\",\n      \"schema\": \"bookings\",\n      \"name\": \"flights flights_aircraft_code_fkey\",\n      \"owner\": \"postgres\",\n      \"section\": \"PostData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": [\n        222\n      ]\n    },\n    {\n      \"dumpId\": 3265,\n      \"databaseOid\": 16482,\n      \"objectOid\": 2606,\n      \"objectType\": \"FK CONSTRAINT\",\n      \"schema\": \"bookings\",\n      \"name\": \"flights flights_arrival_airport_fkey\",\n      \"owner\": \"postgres\",\n      \"section\": \"PostData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": [\n        222\n      ]\n    },\n    {\n      \"dumpId\": 3266,\n      \"databaseOid\": 16487,\n      \"objectOid\": 2606,\n      \"objectType\": \"FK CONSTRAINT\",\n      \"schema\": \"bookings\",\n      \"name\": \"flights flights_departure_airport_fkey\",\n      \"owner\": \"postgres\",\n      \"section\": \"PostData\",\n      \"originalSize\": 0,\n      \"compressedSize\": 0,\n      \"fileName\": \"\",\n      \"dependencies\": [\n        222\n      ]\n    }\n  ]\n}\n

  1. The date when the backup has been initiated, also indicating the snapshot date.
  2. The date when the backup process was successfully completed.
  3. The original size of the backup in bytes.
  4. The size of the backup after compression in bytes.
  5. A list of tables that underwent transformation during the backup.
  6. The schema name of the table.
  7. The name of the table.
  8. Custom query override, if applicable.
  9. A list of transformers that were applied during the backup.
  10. The name of the transformer.
  11. The parameters provided for the transformer.
  12. A mapping of overridden column types.
  13. The header information in the table of contents file. This provides the same details as the --format=text output in the previous snippet.
  14. The list of restoration entries. This offers the same information as the --format=text output in the previous snippet.

Note

The json format provides more detailed information compared to the text format. The text format is primarily used for backward compatibility and for generating a restoration list that can be used with pg_restore -L listfile. On the other hand, the json format provides comprehensive metadata about the dump, including information about the applied transformers and their parameters. The json format is especially useful for detailed dump introspection.

"},{"location":"commands/show-transformer/","title":"show-transformer","text":""},{"location":"commands/show-transformer/#show-transformer-command","title":"show-transformer command","text":"

This command prints out detailed information about a transformer by a provided name, including specific attributes to help you understand and configure the transformer effectively.

To show detailed information about a transformer, use the following command:

greenmask --config=config.yml show-transformer TRANSFORMER_NAME\n

Supported flags:

  • --format \u2014 allows to select the output format. There are two options available: text or json. The default setting is text.

Example of show-transformer output:

When using the show-transformer command, you receive detailed information about the transformer and its parameters and their possible attributes. Below are the key parameters for each transformer:

  • Name \u2014 the name of the transformer
  • Description \u2014 a brief description of what the transformer does

  • Parameters \u2014 a list of transformer parameters, each with its own set of attributes. Possible attributes include:

    • description \u2014 a brief description of the parameter's purpose
    • required \u2014 a flag indicating whether the parameter is required when configuring the transformer
    • link_parameter \u2014 specifies whether the value of the parameter will be encoded using a specific parameter type encoder. For example, if a parameter named column is linked to another parameter start, the start parameter's value will be encoded according to the column type when the transformer is initialized.
    • cast_db_type \u2014 indicates that the value should be encoded according to the database type. For example, when dealing with the INTERVAL data type, you must provide the interval value in PostgreSQL format.
    • default_value \u2014 the default value assigned to the parameter if it's not provided during configuration.
    • column_properties \u2014 if a parameter represents the name of a column, it may contain additional properties, including:
      • nullable \u2014 indicates whether the transformer may produce NULL values, potentially violating the NOT NULL constraint
      • unique \u2014 specifies whether the transformer guarantees unique values for each call. If set to true, it means that the transformer cannot produce duplicate values, ensuring compliance with the UNIQUE constraint.
      • affected \u2014 indicates whether the column is affected during the transformation process. If not affected, the column's value might still be required for transforming another column.
      • allowed_types \u2014 a list of data types that are compatible with this parameter
      • skip_original_data \u2014 specifies whether the original value of the column, before transformation, is relevant for the transformation process
      • skip_on_null \u2014 indicates whether the transformer should skip the transformation when the input column value is NULL. If the column value is NULL, interaction with the transformer is unnecessary.

Warning

The default value in JSON format is base64 encoded. This might be changed in later version of Greenmask.

JSON output example
[\n  {\n    \"properties\": {\n      \"name\": \"NoiseFloat\",\n      \"description\": \"Make noise float for int\",\n      \"is_custom\": false\n    },\n    \"parameters\": [\n      {\n        \"name\": \"column\",\n        \"description\": \"column name\",\n        \"required\": true,\n        \"is_column\": true,\n        \"is_column_container\": false,\n        \"column_properties\": {\n          \"max_length\": -1,\n          \"affected\": true,\n          \"allowed_types\": [\n            \"float4\",\n            \"float8\",\n            \"numeric\"\n          ],\n          \"skip_on_null\": true\n        }\n      },\n      {\n        \"name\": \"ratio\",\n        \"description\": \"max random percentage for noise\",\n        \"required\": false,\n        \"is_column\": false,\n        \"is_column_container\": false,\n        \"default_value\": \"MC4x\"\n      },\n      {\n        \"name\": \"decimal\",\n        \"description\": \"decimal of noised float value (number of digits after coma)\",\n        \"required\": false,\n        \"is_column\": false,\n        \"is_column_container\": false,\n        \"default_value\": \"NA==\"\n      }\n    ]\n  }\n]\n
"},{"location":"commands/validate/","title":"validate command","text":"

The validate command allows you to perform a validation procedure and compare transformed data.

Below is a list of all supported flags for the validate command:

Supported flags
Usage:\n  greenmask validate [flags]\n\nFlags:\n      --data                  Perform test dump for --rows-limit rows and print it pretty\n      --diff                  Find difference between original and transformed data\n      --format string         Format of output. possible values [text|json] (default \"text\")\n      --rows-limit uint       Check tables dump only for specific tables (default 10)\n      --schema                Make a schema diff between previous dump and the current state\n      --table strings         Check tables dump only for specific tables\n      --table-format string   Format of table output (only for --format=text). Possible values [vertical|horizontal] (default \"vertical\")\n      --transformed-only      Print only transformed column and primary key\n      --warnings              Print warnings\n

Validate command can exit with non-zero code when:

  • Any error occurred
  • Validate was called with --warnings flag and there are warnings
  • Validate was called with --schema flag and there are schema differences

All of those cases may be used for CI/CD pipelines to stop the process when something went wrong. This is especially useful when --schema flag is used - this allows to avoid data leakage when schema changed.

You can use the --table flag multiple times to specify the tables you want to check. Tables can be written with or without schema names (e. g., public.table_name or table_name). If you specify multiple tables from different schemas, an error will be thrown.

To start validation, use the following command:

greenmask --config=config.yml validate \\\n  --warnings \\\n  --data \\\n  --diff \\\n  --schema \\\n  --format=text \\\n  --table-format=vertical \\\n  --transformed-only \\\n  --rows-limit=1\n
Validation output example
2024-03-15T19:46:12+02:00 WRN ValidationWarning={\"hash\":\"aa808fb574a1359c6606e464833feceb\",\"meta\":{\"ColumnName\":\"birthdate\",\"ConstraintDef\":\"CHECK (birthdate \\u003e= '1930-01-01'::date AND birthdate \\u003c= (now() - '18 years'::interval))\",\"ConstraintName\":\"humanresources\",\"ConstraintSchema\":\"humanresources\",\"ConstraintType\":\"Check\",\"ParameterName\":\"column\",\"SchemaName\":\"humanresources\",\"TableName\":\"employee\",\"TransformerName\":\"NoiseDate\"},\"msg\":\"possible constraint violation: column has Check constraint\",\"severity\":\"warning\"}\n

The validation output will provide detailed information about potential constraint violations and schema issues. Each line contains nested JSON data under the ValidationWarning key, offering insights into the affected part of the configuration and potential constraint violations.

Pretty formatted validation warning

{ \n  \"hash\": \"aa808fb574a1359c6606e464833feceb\", // (13)\n  \"meta\": { // (1)\n    \"ColumnName\": \"birthdate\", // (2)\n    \"ConstraintDef\": \"CHECK (birthdate >= '1930-01-01'::date AND birthdate <= (now() - '18 years'::interval))\", // (3)\n    \"ConstraintName\": \"humanresources\", // (4)\n    \"ConstraintSchema\": \"humanresources\", // (5)\n    \"ConstraintType\": \"Check\", // (6)\n    \"ParameterName\": \"column\", // (7)\n    \"SchemaName\": \"humanresources\", // (8)\n    \"TableName\": \"employee\", // (9)\n    \"TransformerName\": \"NoiseDate\" // (10)\n  },\n  \"msg\": \"possible constraint violation: column has Check constraint\", // (11)\n  \"severity\": \"warning\" // (12)\n}\n

  1. Detailed metadata. The validation output provides comprehensive metadata to pinpoint the source of problems.
  2. Column name indicates the name of the affected column.
  3. Constraint definition specifies the definition of the constraint that may be violated.
  4. Constraint name identifies the name of the constraint that is potentially violated.
  5. Constraint schema name indicates the schema in which the constraint is defined.
  6. Type of constraint represents the type of constraint and can be one of the following: 
    * ForeignKey\n* Check\n* NotNull\n* PrimaryKey\n* PrimaryKeyReferences\n* Unique\n* Length\n* Exclusion\n* TriggerConstraint\n
  7. Table schema name specifies the schema name of the affected table.
  8. Table name identifies the name of the table where the problem occurs.
  9. Transformer name indicates the name of the transformer responsible for the transformation.
  10. Name of affected parameter typically, this is the name of the column parameter that is relevant to the validation warning.
  11. Validation warning description provides a detailed description of the validation warning and the reason behind it.
  12. Severity of validation warning indicates the severity level of the validation warning and can be one of the following: 
    * error\n* warning\n* info\n* debug\n
  13. Hash is a unique identifier of the validation warning. It is used to resolve the warning in the config file

Note

A validation warning with a severity level of \"error\" is considered critical and must be addressed before the dump operation can proceed. Failure to resolve such warnings will prevent the dump operation from being executed.

Schema diff changed output example
2024-03-15T19:46:12+02:00 WRN Database schema has been changed Hint=\"Check schema changes before making new dump\" PreviousDumpId=1710520855501\n2024-03-15T19:46:12+02:00 WRN Column renamed Event=ColumnRenamed Signature={\"CurrentColumnName\":\"id1\",\"PreviousColumnName\":\"id\",\"TableName\":\"test\",\"TableSchema\":\"public\"}\n2024-03-15T19:46:12+02:00 WRN Column type changed Event=ColumnTypeChanged Signature={\"ColumnName\":\"id\",\"CurrentColumnType\":\"bigint\",\"CurrentColumnTypeOid\":\"20\",\"PreviousColumnType\":\"integer\",\"PreviousColumnTypeOid\":\"23\",\"TableName\":\"test\",\"TableSchema\":\"public\"}\n2024-03-15T19:46:12+02:00 WRN Column created Event=ColumnCreated Signature={\"ColumnName\":\"name\",\"ColumnType\":\"text\",\"TableName\":\"test\",\"TableSchema\":\"public\"}\n2024-03-15T19:46:12+02:00 WRN Table created Event=TableCreated Signature={\"SchemaName\":\"public\",\"TableName\":\"test1\",\"TableOid\":\"20563\"}\n

Example of validation diff:

The validation diff is presented in a neatly formatted table. In this table:

  • Columns that are affected by the transformation are highlighted with a red background.
  • The pre-transformation values are displayed in green.
  • The post-transformation values are shown in red.
  • The result in --format=text can be displayed in either horizontal (--table-format=horizontal) or vertical (--table-format=vertical) format, making it easy to visualize and understand the differences between the original and transformed data.

The whole validate command may be run in json format including logging making easy to parse the structure. 

greenmask --config=config.yml validate \\\n  --warnings \\\n  --data \\\n  --diff \\\n  --schema \\\n  --format=json \\\n  --table-format=vertical \\\n  --transformed-only \\\n  --rows-limit=1 \\\n  --log-format=json\n

The json object result

The validation warningSchema diff eventsTransformation diff line 
{\n  \"level\": \"warn\",\n  \"ValidationWarning\": {\n    \"msg\": \"possible constraint violation: column has Check constraint\",\n    \"severity\": \"warning\",\n    \"meta\": {\n      \"ColumnName\": \"birthdate\",\n      \"ConstraintDef\": \"CHECK (birthdate >= '1930-01-01'::date AND birthdate <= (now() - '18 years'::interval))\",\n      \"ConstraintName\": \"humanresources\",\n      \"ConstraintSchema\": \"humanresources\",\n      \"ConstraintType\": \"Check\",\n      \"ParameterName\": \"column\",\n      \"SchemaName\": \"humanresources\",\n      \"TableName\": \"employee\",\n      \"TransformerName\": \"NoiseDate\"\n    },\n    \"hash\": \"aa808fb574a1359c6606e464833feceb\"\n  },\n  \"time\": \"2024-03-15T20:01:51+02:00\"\n}\n
{\n  \"level\": \"warn\",\n  \"PreviousDumpId\": \"1710520855501\",\n  \"Diff\": [\n    {\n      \"event\": \"ColumnRenamed\",\n      \"signature\": {\n        \"CurrentColumnName\": \"id1\",\n        \"PreviousColumnName\": \"id\",\n        \"TableName\": \"test\",\n        \"TableSchema\": \"public\"\n      }\n    },\n    {\n      \"event\": \"ColumnTypeChanged\",\n      \"signature\": {\n        \"ColumnName\": \"id\",\n        \"CurrentColumnType\": \"bigint\",\n        \"CurrentColumnTypeOid\": \"20\",\n        \"PreviousColumnType\": \"integer\",\n        \"PreviousColumnTypeOid\": \"23\",\n        \"TableName\": \"test\",\n        \"TableSchema\": \"public\"\n      }\n    },\n    {\n      \"event\": \"ColumnCreated\",\n      \"signature\": {\n        \"ColumnName\": \"name\",\n        \"ColumnType\": \"text\",\n        \"TableName\": \"test\",\n        \"TableSchema\": \"public\"\n      }\n    },\n    {\n      \"event\": \"TableCreated\",\n      \"signature\": {\n        \"SchemaName\": \"public\",\n        \"TableName\": \"test1\",\n        \"TableOid\": \"20563\"\n      }\n    }\n  ],\n  \"Hint\": \"Check schema changes before making new dump\",\n  \"time\": \"2024-03-15T20:01:51+02:00\",\n  \"message\": \"Database schema has been changed\"\n}\n
{\n  \"schema\": \"humanresources\",\n  \"name\": \"employee\",\n  \"primary_key_columns\": [\n    \"businessentityid\"\n  ],\n  \"with_diff\": true,\n  \"transformed_only\": true,\n  \"records\": [\n    {\n      \"birthdate\": {\n        \"original\": \"1969-01-29\",\n        \"transformed\": \"1964-10-20\",\n        \"equal\": false,\n        \"implicit\": true\n      },\n      \"businessentityid\": {\n        \"original\": \"1\",\n        \"transformed\": \"1\",\n        \"equal\": true,\n        \"implicit\": true\n      }\n    }\n  ]\n}\n
"},{"location":"release_notes/greenmask_0_1_0/","title":"Greenmask 0.1.0","text":"

We are excited to announce the release of Greenmask v0.1.0, marking the first production-ready version. This release addresses various bug fixes, introduces improvements, and includes documentation refactoring for enhanced clarity.

"},{"location":"release_notes/greenmask_0_1_0/#new-features","title":"New features","text":"

  • Added positional arguments for the list-transformers command, allowing specific transformer information retrieval (e.g., greenmask list-transformers RandomDate).

  • Added a version parameter --version that prints Greenmask version.

  • Added numeric parameters support for -Int and -Float transformers.

"},{"location":"release_notes/greenmask_0_1_0/#improvements","title":"Improvements","text":"

  • Improved verbosity in custom transformer interaction, accumulating stderr data and forwarding it in batches instead of writing it one by one.

  • Updated dependencies to newer versions.

  • Enhanced the stability of the JSON line interaction protocol by utilizing the stdlib JSON encoder/decoder.

  • Modified the method for sending table metadata to custom transformers; now, it is sent via stdin in the first line in JSON format instead of providing it via command arguments.

  • Refactored template functions naming.

  • Refactored NoiseDate transformer implementation for improved stability and predictability.

  • Changed the default value for the Dict transformer: fail_not_matched parameter: true.

  • Refactored the Hash transformer to provide a salt parameter and receive a base64 encoded salt. If salt is not provided, it generates one randomly.

  • Added validation for the truncate parameter of NoiseDate and RandomDate transformers that issues a warning if the provided value is invalid.

  • Increased verbosity of parameter validation warnings, now properly forwarding warnings to stdout.

"},{"location":"release_notes/greenmask_0_1_0/#fixes","title":"Fixes","text":"

  • Resolved pgx driver connection leakage issue.

  • Fixed deletion failure of dumps for S3 storage.

  • Corrected cobra autocompletion for the Greenmask utility.

  • Fixed NOT NULL constraint validation.

  • Addressed JSON API interaction issues that previously caused deadlocks and timeouts.

  • Fixed encode-decoding for binary parameters, ensuring accurate forwarding of values to custom transformers.

  • Fixed the RandomChoice transformer to correctly marshal and unmarshal values during validation.

  • Introduced the nullable property for the SetNull transformer to enhance NOT NULL constraint validation.

  • Resolved text wrapping issues for the validate command.

  • Fixed build failures on Windows due to Linux platform dependencies.

  • Corrected stdout readline buffer reading during interaction with custom transformers.

  • Fixed integration tests.

"},{"location":"release_notes/greenmask_0_1_0/#ecosystem-changes","title":"Ecosystem changes","text":"

  • Implemented CI/CD pipelines for the entire project.

  • Established a user-friendly playground in Docker compose, including:

  • Deployed Minio storage container.

  • PostgreSQL container containing both the original database (Adventure Works) and the transformed (empty DB).

  • Greenmask container itself.

  • Refactored current readme files.

"},{"location":"release_notes/greenmask_0_1_0/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_0_beta/","title":"Greenmask 0.0.1 Beta","text":"

We are excited to announce the beta release of Greenmask, a versatile and open-source utility for PostgreSQL logical backup dumping, anonymization, and restoration. Greenmask is perfect for routine backup and restoration tasks. It facilitates anonymization and data masking for staging environments and analytics.

This release introduces a range of features aimed at enhancing database management and security.

"},{"location":"release_notes/greenmask_0_1_0_beta/#key-features","title":"Key features","text":"
  • Cross-platform support \u2014 fully written in Go without platform dependencies.
  • Type-safe database operations \u2014 validates and encodes data, maintaining integrity.
  • Transformation validation \u2014 ensures data transformations are correct and maintainable.
  • Partitioned table support \u2014 simplifies configuration for partitioned tables.
  • Stateless and backward compatible \u2014 works alongside standard PostgreSQL utilities.
  • Parallel execution \u2014 enhances efficiency in dumping and restoration processes.
  • Multiple storage options \u2014 supports both local (directory) and remote (S3-like) storage solutions.
"},{"location":"release_notes/greenmask_0_1_0_beta/#download","title":"Download","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_1/","title":"Greenmask 0.1.1","text":"

This release introduces a suite of new transformers, significantly enhancing Greenmask's capabilities for obfuscating PostgreSQL databases.

"},{"location":"release_notes/greenmask_0_1_1/#new-features","title":"New features","text":"

Added the following new transformers:

Transformer Description RandomLatitude Generates a random latitude value RandomLongitude Generates a random longitude value RandomUnixTime Generates a random Unix timestamp RandomMonthName Generates the name of a random month RandomYearString Generates a random year as a string RandomDayOfWeek Generates a random day of the week RandomDayOfMonth Generates a random day of the month RandomCentury Generates a random century RandomTimezone Generates a random timezone RandomEmail Generates a random email address RandomMacAddress Generates a random MAC address RandomDomainName Generates a random domain name RandomURL Generates a random URL RandomUsername Generates a random username RandomIPv4 Generates a random IPv4 address RandomIPv6 Generates a random IPv6 address RandomPassword Generates a random password RandomWord Generates a random word RandomSentence Generates a random sentence RandomParagraph Generates a random paragraph RandomCCType Generates a random credit card type RandomCCNumber Generates a random credit card number RandomCurrency Generates a random currency code RandomAmountWithCurrency Generates a random monetary amount with currency RandomTitleMale Generates a random title for males RandomTitleFemale Generates a random title for females RandomFirstName Generates a random first name RandomFirstNameMale Generates a random male first name RandomFirstNameFemale Generates a random female first name RandomLastName Generates a random last name RandomName Generates a full random name RandomPhoneNumber Generates a random phone number RandomTollFreePhoneNumber Generates a random toll-free phone number RandomE164PhoneNumber Generates a random phone number in E.164 format RealAddress Generates a real address"},{"location":"release_notes/greenmask_0_1_1/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_10/","title":"Greenmask 0.1.10","text":"

This release introduces improvements and bug fixes

"},{"location":"release_notes/greenmask_0_1_10/#changes","title":"Changes","text":"
  • Fixed panic caused in RandomString transformer
  • Fixed wrong table size calculation. Now the table size includes TOAST table size
  • Added custom transformer interaction API defaults if not set
  • Changed docker workdir to greenmask home
  • Removed bucket name from object path prefix
"},{"location":"release_notes/greenmask_0_1_10/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_11/","title":"Greenmask 0.1.11","text":"

This release introduces improvements and bug fixes

"},{"location":"release_notes/greenmask_0_1_11/#changes","title":"Changes","text":"
  • Added support for generated columns in the table
  • Fixed transformer parameters encoding issue caused by spf13/viper
  • Fixed table scoring for transformed table
  • Refactored connection management logic in restore command - fixes connection idle timeout
"},{"location":"release_notes/greenmask_0_1_11/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_12/","title":"Greenmask 0.1.12","text":"

This release introduces improvements and bug fixes

"},{"location":"release_notes/greenmask_0_1_12/#changes","title":"Changes","text":"
  • Fixed config decoding issue caused
  • Fixed TOC entries merge behavior when data section is empty
  • Fixed integration tests for S3 storage
"},{"location":"release_notes/greenmask_0_1_12/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_13/","title":"Greenmask 0.1.13","text":"

This release introduces only improvements in documentation deployment. The core greenmask utility does not contain any changes.

"},{"location":"release_notes/greenmask_0_1_13/#changes","title":"Changes","text":"
  • Added documentation deployment with versioning
"},{"location":"release_notes/greenmask_0_1_13/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_14/","title":"Greenmask 0.1.14","text":"

This release introduces bug fixes.

"},{"location":"release_notes/greenmask_0_1_14/#changes","title":"Changes","text":"
  • Fixed large panic caused in Large Object dumper
"},{"location":"release_notes/greenmask_0_1_14/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_2/","title":"Greenmask 0.1.2","text":"

This release introduces bug fixes.

"},{"location":"release_notes/greenmask_0_1_2/#fixes","title":"Fixes","text":"
  • Fixed bug when raw COPY lines were parsed incorrectly
  • Fixed --version parameter behavior
  • Fixed --dbname parameter - now it correctly works with PostgreSQL connection string in URI format postgresql:///
"},{"location":"release_notes/greenmask_0_1_2/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_3/","title":"Greenmask 0.1.3","text":"

This release introduces bug fixes.

"},{"location":"release_notes/greenmask_0_1_3/#fixes","title":"Fixes","text":"
  • Fixed the JSON transformer's parsing for the operations fields
  • Fixed database connection string builder in pg_restore and pg_dump
"},{"location":"release_notes/greenmask_0_1_3/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_4/","title":"Greenmask 0.1.4","text":"

This release introduces bug fixes.

"},{"location":"release_notes/greenmask_0_1_4/#fixes","title":"Fixes","text":"
  • Fixed database connection string behavior fields
"},{"location":"release_notes/greenmask_0_1_4/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_5/","title":"Greenmask 0.1.5","text":"

This release introduces a new Greenmask command, improvements, bug fixes, and numerous documentation updates.

"},{"location":"release_notes/greenmask_0_1_5/#new-features","title":"New features","text":"

Added a new Greenmask CLI command\u2014show-transformer that shows detailed information about a specified transformer.

"},{"location":"release_notes/greenmask_0_1_5/#improvements","title":"Improvements","text":"
  • The Hash transformer has been completely remastered and now has the function parameter to choose from several hash algorithm options and the max_length parameter to truncate the hash tail.
  • Split information about transformers between the list-transformers and new show-transformer CLI commands, which allows for more comprehensible and useful outputs for both commands
  • Added error severity for the Cmd parameter validator
  • Improved UX for the Greenmask release binaries
"},{"location":"release_notes/greenmask_0_1_5/#fixes","title":"Fixes","text":"
  • Fixed metadata enrichment for validation warnings caused by RawValueValidator
  • Fixed a typo in the credit_card value for the type parameter of the Masking transformer
  • Fixed Greenmask Playground environment variables and the cleanup command
  • Fixed list-dump, list-transformers, and restore commands exit code on error
"},{"location":"release_notes/greenmask_0_1_5/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_6/","title":"Greenmask 0.1.6","text":"

This is a minor release that introduces a bug hotfix

"},{"location":"release_notes/greenmask_0_1_6/#fixes","title":"Fixes","text":"
  • Fixed uncontrolled buffer growth in the restore command
"},{"location":"release_notes/greenmask_0_1_6/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_7/","title":"Greenmask 0.1.7","text":"

This release introduces a new Greenmask command, improvements, bug fixes, and documentation update.

"},{"location":"release_notes/greenmask_0_1_7/#new-features","title":"New features","text":"
  • Added restoration filtering by --table, --schema and --exclude-schema parameters
  • Validate parameters without parameters validates only configuration file
  • Added the --schema parameter, which allows to make a schema diff between the previous dump and the current. This is useful when you want to check if the schema has changed after the migration. By controlling it we can exclude data leakage after migration
  • Validate command divided by many stages that can be controlled using parameters
    • Configuration validation
    • Transformer validation
    • Constraint violation check
    • Data difference check
"},{"location":"release_notes/greenmask_0_1_7/#improvements","title":"Improvements","text":"
  • Improved Hash transformer
    • Added salt parameter that can be set via config or via GREENMASK_GLOBAL_SALT
    • Added sha3 functions support in different modes (sha3-224, sha3-256, sha3-384, sha3-512)
  • Refactored Cmd transformer logic
    • Json API: Now it allows to use of column names instead of column indexes in JSON format
    • Csv API: Now it can use the column order from config via column remapping
  • The validate command was rewritten almost from scratch.
    • New option --transformed-only - displays only columns that are transformed with primary key (if exists). This allows to reduce the output data and make it more readable
    • Implemented json format for output
    • Added the --table-format parameter which is responsible for the vertical and horizontal table orientation. This works only when --format=text
    • Added the --warnings parameter, if it is specified then not only fatal-warnings will be displayed, but also those with a lower severity
"},{"location":"release_notes/greenmask_0_1_7/#fixes","title":"Fixes","text":"
  • Fixed --use-list option - now it applies toc entries according to the order in list file
  • Fixed --use-list option behaviour together with --list-format option (json or text). Now it generates temporal list file in text format for providing it to the pg_restore call
  • Updated documentation according to the latest changes
"},{"location":"release_notes/greenmask_0_1_7/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_8/","title":"Greenmask 0.1.8","text":"

This release introduces improvements and bug fixes

"},{"location":"release_notes/greenmask_0_1_8/#improvements","title":"Improvements","text":"
  • Implemented --exit-on-error parameter for pg_restore run. But it does not play for \"data\" section restoration now. If any error is caused in data section greenmask exits with the error whether --exit-on-error was provided or not. This might be fixed later
"},{"location":"release_notes/greenmask_0_1_8/#fixes","title":"Fixes","text":"
  • Fixed dependent objects dropping when running with the restore command with the --clean parameter. Useful when restoring and overriding only required tables
  • Fixed show-dump command output in text mode
  • Disabled CGO. Fixes problem when downloaded binary from repo cannot run
  • Fixed delete dump operation
"},{"location":"release_notes/greenmask_0_1_8/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_1_9/","title":"Greenmask 0.1.9","text":"

This release introduces improvements and bug fixes

"},{"location":"release_notes/greenmask_0_1_9/#improvements","title":"Improvements","text":"
  • Implemented tables scoring according to the table size and transformation costs. This correctly spread the tables dumping between the requested workers pool and reduces the execution time. Now greenmask introspects the table size, adds the transformation scoring using the formula score = tableSizeInBytes + (tableSizeInBytes * 0.03 * tableTransformationsCount), and uses the strategy \"Largest First\". The problem is described here
  • Introduced no_verify_ssl parameter for S3 storage
  • Adjusted Dockerfile
    • Changed entrypoint to greenmask binary
    • The greenmask container now runs under greenmask user and groups
  • Refactored storage config structure. Now it contains the type that is used for the storage type determination
  • Most of the attributes may be overridden with environment variables where the letters are capitalized and the dots are replaced with underscores. For instance, the setting storage.type might be represented with the environment variable STORAGE_TYPE
  • Parameter --config is not required anymore. This simplifies the greenmask utility user experience
  • Directory storage set as the default
  • Set the default temporary directory as /tmp
  • Added environment variable section to the configuration docs
"},{"location":"release_notes/greenmask_0_1_9/#fixes","title":"Fixes","text":"
  • Fixed S3_REGION environment variable usage. Tested cases where the S3 storage is set up using S3 variables that uses by github.com/aws/aws-sdk-go
  • Updated project dependencies to the latest version
"},{"location":"release_notes/greenmask_0_1_9/#assets","title":"Assets","text":"

To download the Greenmask binary compatible with your system, see the release's assets list.

"},{"location":"release_notes/greenmask_0_2_0/","title":"Greenmask 0.2.0","text":"

This is one of the biggest releases since Greenmask was founded. We've been in close contact with our users, gathering feedback, and working hard to make Greenmask more flexible, reliable, and user-friendly.

This major release introduces exciting new features such as database subsetting, pgzip support, restoration in topological order, and refactored transformers, significantly enhancing Greenmask's flexibility to better meet business needs. It also includes several fixes and improvements.

"},{"location":"release_notes/greenmask_0_2_0/#preface","title":"Preface","text":"

This release is a major milestone that significantly expands Greenmask's functionality, transforming it into a simple, extensible, and reliable solution for database security, data anonymization, and everyday operations. Our goal is to create a core system that can serve as a foundation for comprehensive dynamic staging environments and robust data security.

"},{"location":"release_notes/greenmask_0_2_0/#notable-changes","title":"Notable changes","text":"

  • PostgreSQL 17 support - revised ported library to support PostgreSQL 17

  • Database Subset - a new feature that allows you to define a subset of the database, allowing you to scale down the dump size (#110). This is robust for multipurpose and especially useful for testing and development environments. It supports:

    • References with NULL values - generate the LEFT JOIN query for the FK reference with NULL values to include them in the subset.
    • Supports virtual references (virtual foreign keys) - create a logical FK in Greenmask that will be used for subset dependencies graph. The virtual reference can be defined for a column or an expression, allowing you to get the value from JSON and similar.
    • Supports circular references - Greenmask will automatically resolve circular dependencies in the subset by generating a recursive query. The query is generated with integrity checks of the subset ensuring that the data gathered from circular dependencies is consistent.
    • Fully covered with documentation including troubleshooting and examples.
    • Supports FK and PK that have more than one column (or expression).
    • Multi-cycles resolution in one strong connected component (SCC) is supported - Greenmask will generate a recursive query for the SCC whether it is a single cycle or multiple cycles, making the subset system universal for any database schema.
    • Supports polymorphic relationships - You can define a virtual reference for a table with polymorphic references using polymorphic_exprs attribute and use greenmask to generate a subset for such tables.

  • pgzip support for faster compression and decompression \u2014 setting --pgzip can speed up the dump and restoration processes through parallel compression. In some tests, it shows up to 5x faster dump and restore operations.

  • Restoration in topological order - This flag ensures that dependent tables are not restored until the tables they depend on have been restored. This is useful when you want to be notified of errors as immediately as possible without waiting for the entire table to be restored.

  • Insert format restoration - For a flexible restoration process, Greenmask now supports data restoration in the INSERT format. It generates the insert statements based on COPY records from the dump. You do not need to re-dump your data to use this feature; it can be defined in the restore command. The list of new features related to the INSERT format:

    • Generate INSERT statements with the **ON CONFLICT DO NOTHING** clause if the flag --on-conflict-do-nothing is set.
    • Error exclusion list in the config to skip certain errors and continue inserting subsequent rows from the dump.
    • Use cases - incremental dump and restoration for logical data. For example, if you have a database, and you want to insert data periodically from another source, this can be used together with the database subset and transformations to catch up the target database.

  • Restore data batching (#173) - By default, the COPY protocol returns the error only on transaction commit. To override this behavior, use the --batch-size flag to specify the number of rows to insert in a single batch during the COPY command. This is useful when you want to control the transaction size and commit.

  • Introduced keep_null parameter for RandomPerson transformer.

  • Introduced dynamic parameters in the transformers

    • Most transformers now support dynamic parameters where applicable.
    • Dynamic parameters are strictly enforced. If you need to cast values to another type, Greenmask provides templates and predefined cast functions accessible via cast_to. These functions cover frequent operations such as UnixTimestampToDate and IntToBool.
  • The transformation logic has been significantly refactored, making transformers more customizable and flexible than before.

  • Introduced transformation engines

    • random - generates transformer values based on pseudo-random algorithms.
    • hash - generates transformer values using hash functions. Currently, it utilizes sha3 hash functions, which are secure but perform slowly. In the stable release, there will be an option to choose between sha3 and SipHash.

  • Introduced static parameters value template

  • Dumps retention management - Introduced retention parameters (#201) for the delete command. Introduced two new statuses: failed and in progress. A dump is considered failed if it lacks a \"done\" heartbeat or if the last heartbeat timestamp exceeds 30 minutes. The delete command now supports the following retention parameters:

    • --dry-run: Runs the deletion operation in test mode with verbose output, without actually deleting anything.
    • --before-date 2024-08-27T23:50:54+00:00: Deletes dumps older than the specified date. The date must be provided in RFC3339Nano format, for example: 2021-01-01T00:00:00Z.
    • --retain-recent 10: Retains the N most recent dumps, where N is specified by the user.
    • --retain-for 1w2d3h4m5s6ms7us8ns: Retains dumps for the specified duration. The format supports weeks (w), days (d), hours (h), minutes (m), seconds (s), milliseconds (ms), microseconds (us), and nanoseconds (ns).
    • --prune-failed: Prunes (removes) all dumps that have failed.
    • --prune-unsafe: Prunes dumps with \"unknown-or-failed\" statuses. This option only works in conjunction with --prune-failed.

  • Docker image mirroring into the GitHub Container Registry

"},{"location":"release_notes/greenmask_0_2_0/#core","title":"Core","text":"
  • Introduced the Parametrizer interface, now implemented for both dynamic and static parameters.
  • Renamed most of the toolkit types for enhanced clarity and comprehensive documentation coverage.
  • Refactored the Driver initialization logic.
  • Added validation warnings for overridden types in the Driver.
  • Migrated existing built-in transformers to utilize the new Parametrizer interface.
  • Implemented a new abstraction, TransformationContext, as the first step towards enabling new feature transformation conditions (#34).
  • Optimized most transformers for performance in both dynamic and static modes. While dynamic mode offers flexibility, static mode ensures performance remains high. Using only the necessary transformation features helps keep transformation time predictable.
"},{"location":"release_notes/greenmask_0_2_0/#transformers","title":"Transformers","text":"

  • RandomEmail - Introduces a new transformer that supports both random and deterministic engines. It allows for flexible email value generation; you can use column values in the template and choose to keep the original domain or select any from the domains parameter.

  • NoiseDate, NoiseFloat, NoiseInt - These transformers support both random and deterministic engines, offering dynamic mode parameters that control the noise thresholds within the min and max range. Unlike previous implementations which used a single ratio parameter, the new release features min_ratio and max_ratio parameters to define noise values more precisely. Utilizing the hash engine in these transformers enhances security by complicating statistical analysis for attackers, especially when the same salt is used consistently over long periods.

  • NoiseNumeric - A newly implemented transformer, sharing features with NoiseInt and NoiseFloat, but specifically designed for numeric values (large integers or floats). It provides a decimal parameter to handle values with fractions.

  • RandomChoice - Now supports the hash engine

  • RandomDate, RandomFloat, RandomInt - Now enhanced with hash engine support. Threshold parameters min and max have been updated to support dynamic mode, allowing for more flexible configurations.

  • RandomNumeric - A new transformer specifically designed for numeric types (large integers or floats), sharing similar features with RandomInt and RandomFloat, but tailored for handling huge numeric values.

  • RandomString - Now supports hash engine mode

  • RandomUnixTimestamp - This new transformer generates Unix timestamps with selectable units (second, millisecond, microsecond, nanosecond). Similar in function to RandomDate, it supports the hash engine and dynamic parameters for min and max thresholds, with the ability to override these units using min_unit and max_unit parameters.

  • RandomUuid - Added hash engine support

  • RandomPerson - Implemented a new transformer that replaces RandomName, RandomLastName, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, RandomTitleMale, and RandomTitleFemale. This new transformer offers enhanced customizability while providing similar functionalities as the previous versions. It generates personal data such as FirstName, LastName, and Title, based on the provided gender parameter, which now supports dynamic mode. Future minor versions will allow for overriding the default names database.

  • Added tsModify - a new template function for time.Time objects modification

  • Introduced a new RandomIp transformer capable of generating a random IP address based on the specified netmask.

  • Added a new RandomMac transformer for generating random Mac addresses.

  • Deleted transformers include RandomMacAddress, RandomIPv4, RandomIPv6, RandomUnixTime, RandomTitleMale, RandomTitleFemale, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, RandomLastName, and RandomName due to the introduction of more flexible and unified options.

"},{"location":"release_notes/greenmask_0_2_0/#fixes-and-improvements","title":"Fixes and improvements","text":"
  • Fixed validate command with the --table flag, which had the wrong order of the table name representation {{ table_name }}.{{ schema }} instead of {{ schema }}.{{ table_name }}.
  • Fixed Row.SetColumn out of range validation.
  • Fixed restoreWorker panic caused when the worker received an error from pgx.
  • Fixed error handling in the restore command.
  • Fixed restore jobs now start a transaction for each table restoration and commit it after the table restoration is done.
  • Fixed --exit-on-error works incorrectly in the restore command. Now, the --exit-on-error flag works correctly with the data section.
  • Fixed transaction rollback in the validate command.
  • Fixed typo in documentation.
  • Fixed a CI/CD bug related to retrieving current tags.
  • Fixed the Docker image tag for latest to exclude specific keywords.
  • Fixed a case where the hashing value was not set for each column in the RandomPerson transformer.
  • Fixed original email value parsing conditions.
  • Subset docs revision.
  • Fixes a case where data entries were excluded by exclusion parameters such as --exclude-table, --table, etc.
  • Fixed zero bytes that were written in the buffer due to the wrong buffer limit in the Email transformer.
  • Fixed a case where the overridden type of column via columns_type_override did not work.
  • Fixed a case where an unknown option provided in the config was just ignored instead of throwing an error.
  • Fixed a case where min and max parameter values were ignored in transformers NoiseDate, NoiseNumeric, NoiseFloat, NoiseInt, RandomNumeric, RandomFloat, and RandomInt.
  • Fixed TOC entry COPY restoration statement - added missing newline and semicolon. Now backward pg_dump call pg_restore 1724504511561 --file 1724504511561.sql is backward compatible and works as expected.
  • Fixed a case where dump/restore fails when masking tables with a generated column.
  • Updated go version (v1.22) and dependencies
  • Revised installation section of doc
  • PostgreSQL 17 support - revised ported library to support PostgreSQL 17
  • Fixed integration tests - reset the go test cache on each iteration
  • Push docker images to ghcr.io registry
  • A bunch of refactoring and code cleanup to make the codebase more maintainable and readable.
"},{"location":"release_notes/greenmask_0_2_0/#full-changelog-v0114v020","title":"Full Changelog: v0.1.14...v0.2.0","text":""},{"location":"release_notes/greenmask_0_2_0/#links","title":"Links","text":"

Feel free to reach out to us if you have any questions or need assistance:

  • Greenmask Roadmap
  • Email
  • Twitter
  • Telegram
  • Discord
  • DockerHub
"},{"location":"release_notes/greenmask_0_2_0_b1/","title":"Greenmask 0.2.0b1 (pre-release)","text":"

This major beta release introduces new features and refactored transformers, significantly enhancing Greenmask's flexibility to better meet business needs.

"},{"location":"release_notes/greenmask_0_2_0_b1/#changes-overview","title":"Changes overview","text":"
  • Introduced dynamic parameters in the transformers
    • Most transformers now support dynamic parameters where applicable.
    • Dynamic parameters are strictly enforced. If you need to cast values to another type, Greenmask provides templates and predefined cast functions accessible via cast_to. These functions cover frequent operations such as UnixTimestampToDate and IntToBool.
  • The transformation logic has been significantly refactored, making transformers more customizable and flexible than before.

  • Introduced transformation engines

    • random - generates transformer values based on pseudo-random algorithms.
    • hash - generates transformer values using hash functions. Currently, it utilizes sha3 hash functions, which are secure but perform slowly. In the stable release, there will be an option to choose between sha3 and SipHash.

  • Introduced static parameters value template

"},{"location":"release_notes/greenmask_0_2_0_b1/#notable-changes","title":"Notable changes","text":""},{"location":"release_notes/greenmask_0_2_0_b1/#core","title":"Core","text":"
  • Introduced the Parametrizer interface, now implemented for both dynamic and static parameters.
  • Renamed most of the toolkit types for enhanced clarity and comprehensive documentation coverage.
  • Refactored the Driver initialization logic.
  • Added validation warnings for overridden types in the Driver.
  • Migrated existing built-in transformers to utilize the new Parametrizer interface.
  • Implemented a new abstraction, TransformationContext, as the first step towards enabling new feature transformation conditions (#34).
  • Optimized most transformers for performance in both dynamic and static modes. While dynamic mode offers flexibility, static mode ensures performance remains high. Using only the necessary transformation features helps keep transformation time predictable.
"},{"location":"release_notes/greenmask_0_2_0_b1/#documentation","title":"Documentation","text":"

Documentation has been significantly refactored. New information about features and updates to transformer descriptions have been added.

"},{"location":"release_notes/greenmask_0_2_0_b1/#transformers","title":"Transformers","text":"

  • RandomEmail - Introduces a new transformer that supports both random and deterministic engines. It allows for flexible email value generation; you can use column values in the template and choose to keep the original domain or select any from the domains parameter.

  • NoiseDate, NoiseFloat, NoiseInt - These transformers support both random and deterministic engines, offering dynamic mode parameters that control the noise thresholds within the min and max range. Unlike previous implementations which used a single ratio parameter, the new release features min_ratio and max_ratio parameters to define noise values more precisely. Utilizing the hash engine in these transformers enhances security by complicating statistical analysis for attackers, especially when the same salt is used consistently over long periods.

  • NoiseNumeric - A newly implemented transformer, sharing features with NoiseInt and NoiseFloat, but specifically designed for numeric values (large integers or floats). It provides a decimal parameter to handle values with fractions.

  • RandomChoice - Now supports the hash engine

  • RandomDate, RandomFloat, RandomInt - Now enhanced with hash engine support. Threshold parameters min and max have been updated to support dynamic mode, allowing for more flexible configurations.

  • RandomNumeric - A new transformer specifically designed for numeric types (large integers or floats), sharing similar features with RandomInt and RandomFloat, but tailored for handling huge numeric values.

  • RandomString - Now supports hash engine mode

  • RandomUnixTimestamp - This new transformer generates Unix timestamps with selectable units (second, millisecond, microsecond, nanosecond). Similar in function to RandomDate, it supports the hash engine and dynamic parameters for min and max thresholds, with the ability to override these units using min_unit and max_unit parameters.

  • RandomUuid - Added hash engine support

  • RandomPerson - Implemented a new transformer that replaces RandomName, RandomLastName, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, RandomTitleMale, and RandomTitleFemale. This new transformer offers enhanced customizability while providing similar functionalities as the previous versions. It generates personal data such as FirstName, LastName, and Title, based on the provided gender parameter, which now supports dynamic mode. Future minor versions will allow for overriding the default names database.

  • Added tsModify - a new template function for time.Time objects modification

  • Introduced a new RandomIp transformer capable of generating a random IP address based on the specified netmask.

  • Added a new RandomMac transformer for generating random Mac addresses.

  • Deleted transformers include RandomMacAddress, RandomIPv4, RandomIPv6, RandomUnixTime, RandomTitleMale, RandomTitleFemale, RandomFirstName, RandomFirstNameMale, RandomFirstNameFemale, RandomLastName, and RandomName due to the introduction of more flexible and unified options.

"},{"location":"release_notes/greenmask_0_2_0_b1/#full-changelog-v0114v020b1","title":"Full Changelog: v0.1.14...v0.2.0b1","text":""},{"location":"release_notes/greenmask_0_2_0_b1/#playground-usage-for-beta-version","title":"Playground usage for beta version","text":"

If you want to run a Greenmask playground for the beta version v0.2.0b1 execute:

git checkout tags/v0.2.0b1 -b v0.2.0b1\ndocker-compose run greenmask-from-source\n
"},{"location":"release_notes/greenmask_0_2_0_b1/#links","title":"Links","text":"

Feel free to reach out to us if you have any questions or need assistance:

  • Greenmask Roadmap
  • Email
  • Twitter
  • Telegram
  • Discord
  • DockerHub
"},{"location":"release_notes/greenmask_0_2_0_b2/","title":"Greenmask 0.2.0b2 (pre-release)","text":"

This major beta release introduces new features such as the database subset, pgzip support, restoration in topological and many more. It also includes fixes and improvements.

"},{"location":"release_notes/greenmask_0_2_0_b2/#preface","title":"Preface","text":"

This release is a major milestone that significantly expands Greenmask's functionality, transforming it into a simple, extensible, and reliable solution for database security, data anonymization, and everyday operations. Our goal is to create a core system that can serve as a foundation for comprehensive dynamic staging environments and robust data security.

"},{"location":"release_notes/greenmask_0_2_0_b2/#notable-changes","title":"Notable changes","text":"

  • Database Subset - a new feature that allows you to define a subset of the database, allowing you to scale down the dump size (#110). This is robust for multipurpose and especially useful for testing and development environments. It supports:

    • References with NULL values - generate the LEFT JOIN query for the FK reference with NULL values to include them in the subset.
    • Supports virtual references (virtual foreign keys) - create a logical FK in Greenmask that will be used for subset dependencies graph. The virtual reference can be defined for a column or an expression, allowing you to get the value from JSON and similar.
    • Supports circular references - Greenmask will automatically resolve circular dependencies in the subset by generating a recursive query. The query is generated with integrity checks of the subset ensuring that the data gathered from circular dependencies is consistent.
    • Fully covered with documentation including troubleshooting and examples.
    • Supports FK and PK that have more than one column (or expression).
    • Multi-cycles resolution in one strong connected component (SCC) is supported - Greenmask will generate a recursive query for the SCC whether it is a single cycle or multiple cycles, making the subset system universal for any database schema.

  • pgzip support for faster compression and decompression \u2014 setting --pgzip can speed up the dump and restoration processes through parallel compression. In some tests, it shows up to 5x faster dump and restore operations.

  • Restoration in topological order - This flag ensures that dependent tables are not restored until the tables they depend on have been restored. This is useful when you want to be notified of errors as immediately as possible without waiting for the entire table to be restored.

  • Insert format restoration - For a flexible restoration process, Greenmask now supports data restoration in the INSERT format. It generates the insert statements based on COPY records from the dump. You do not need to re-dump your data to use this feature; it can be defined in the restore command. The list of new features related to the INSERT format:

    • Generate INSERT statements with the **ON CONFLICT DO NOTHING** clause if the flag --on-conflict-do-nothing is set.
    • Error exclusion list in the config to skip certain errors and continue inserting subsequent rows from the dump.
    • Use cases - incremental dump and restoration for logical data. For example, if you have a database, and you want to insert data periodically from another source, this can be used together with the database subset and transformations to catch up the target database.

  • Restore data batching (#173) - By default, the COPY protocol returns the error only on transaction commit. To override this behavior, use the --batch-size flag to specify the number of rows to insert in a single batch during the COPY command. This is useful when you want to control the transaction size and commit.

  • Introduced keep_null parameter for RandomPerson transformer.
"},{"location":"release_notes/greenmask_0_2_0_b2/#fixes-and-improvements","title":"Fixes and improvements","text":"
  • Fixed validate command with the --table flag, which had the wrong order of the table name representation {{ table_name }}.{{ schema }} instead of {{ schema }}.{{ table_name }}.
  • Fixed Row.SetColumn out of range validation.
  • Fixed restoreWorker panic caused when the worker received an error from pgx.
  • Fixed error handling in the restore command.
  • Fixed restore jobs now start a transaction for each table restoration and commit it after the table restoration is done.
  • Fixed --exit-on-error works incorrectly in the restore command. Now, the --exit-on-error flag works correctly with the data section.
  • Fixed transaction rollback in the validate command.
  • Fixed typo in documentation.
  • Fixed a CI/CD bug related to retrieving current tags.
  • Fixed the Docker image tag for latest to exclude specific keywords.
  • Fixed a case where the hashing value was not set for each column in the RandomPerson transformer.
  • Fixed original email value parsing conditions.
  • Subset docs revision.
  • Fixes a case where data entries were excluded by exclusion parameters such as --exclude-table, --table, etc.
  • Fixed zero bytes that were written in the buffer due to the wrong buffer limit in the Email transformer.
  • Fixed a case where the overridden type of column via columns_type_override did not work.
  • Fixed a case where an unknown option provided in the config was just ignored instead of throwing an error.
  • Fixed a case where min and max parameter values were ignored in transformers NoiseDate, NoiseNumeric, NoiseFloat, NoiseInt, RandomNumeric, RandomFloat, and RandomInt.
  • Fixed TOC entry COPY restoration statement - added missing newline and semicolon. Now backward pg_dump call pg_restore 1724504511561 --file 1724504511561.sql is backward compatible and works as expected.
  • Fixed a case where dump/restore fails when masking tables with a generated column.
  • Updated go version (v1.22) and dependencies
  • Revised installation section of doc
  • A bunch of refactoring and code cleanup to make the codebase more maintainable and readable.
"},{"location":"release_notes/greenmask_0_2_0_b2/#full-changelog-v020b1v020b2","title":"Full Changelog: v0.2.0b1...v0.2.0b2","text":""},{"location":"release_notes/greenmask_0_2_0_b2/#playground-usage-for-beta-version","title":"Playground usage for beta version","text":"

If you want to run a Greenmask playground for the beta version v0.2.0b2 execute:

git checkout tags/v0.2.0b2 -b v0.2.0b2\ndocker-compose run greenmask-from-source\n
"},{"location":"release_notes/greenmask_0_2_0_b2/#links","title":"Links","text":"

Feel free to reach out to us if you have any questions or need assistance:

  • Greenmask Roadmap
  • Email
  • Twitter
  • Telegram
  • Discord
  • DockerHub
"},{"location":"release_notes/greenmask_0_2_1/","title":"Greenmask 0.2.1","text":"

This release introduces two new features transformation conditions and transformation inheritance for primary and foreign keys. It also includes several bug fixes and improvements.

"},{"location":"release_notes/greenmask_0_2_1/#changes","title":"Changes","text":"
  • Feat: Transformation conditions execute a defined transformation only if a specified condition is met. #133
  • Feat: Transformation inheritance - transformation inheritance for partitioned tables and tables with foreign keys. Define once and apply to all.
  • CI/CD: Add golangci-lint job to pull request check #223
  • CI/CD: Deploy development version of the documentation (main branch) and divided jobs into separate blocks and made them reusable #212
  • Fix: Fixed type in subset documentation #211
  • Fix: Bump go and python dependencies #219
  • Fix: Fatal validation error in playground #224
  • Fix: Code refactoring and golangci-lint warns fixes #226
  • Docs: Revised README.md - added badges, updated the description, added getting started section, added greenmask design schema #216 #217 #218
  • Docs: main page errors in docs #221
  • Docs: Revised README.md according to the latest changes #225
  • Docs: moved documentation to docs.greenmask.io, added feedback form and GA integration #220
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Feel free to reach out to us if you have any questions or need assistance:

  • Greenmask Roadmap
  • Email
  • Twitter
  • Telegram
  • Discord
  • DockerHub
"},{"location":"release_notes/greenmask_0_2_2/","title":"Greenmask 0.2.2","text":"

This release introduces bug fixes.

"},{"location":"release_notes/greenmask_0_2_2/#changes","title":"Changes","text":"
  • Fixed a case when apply_for_references applies validation to all transformations even if they are not marked as apply_for_references #236.
  • Fixed issue with the latest tag disappearing in the documentation #234.
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Feel free to reach out to us if you have any questions or need assistance:

  • Greenmask Roadmap
  • Email
  • Twitter
  • Telegram
  • Discord
  • DockerHub
"},{"location":"release_notes/greenmask_0_2_3/","title":"Greenmask 0.2.3","text":"

This release introduces bug fixes.

"},{"location":"release_notes/greenmask_0_2_3/#changes","title":"Changes","text":"
  • Fixed an issue where the partitioned table itself was executed in the restore worker, resulting in a \"file not found\" error in storage. Closes bug: restoring partitioned tables fails #238 #242.
  • Fixed template function availability #239. Renamed methods according to the documentation: GetColumnRawValue is now GetRawColumnValue, and SetColumnRawValue is now SetRawColumnValue #242
  • Resolved an issue where Dump.createTocEntries processed partitioned tables as if they were physical entities, despite being logical #241
  • Corrected merging in the pre-data, data, and post-data sections, which previously caused a panic in dump command when the post-data section was excluded #241
  • Fixed an issue where dumps created with --load-via-partition-root did not use the root partition table in --inserts generation during restoration #241
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Feel free to reach out to us if you have any questions or need assistance:

  • Greenmask Roadmap
  • Email
  • Twitter
  • Telegram
  • Discord
  • DockerHub
"},{"location":"release_notes/greenmask_0_2_4/","title":"Greenmask 0.2.4","text":"

This release introduces bug fixes.

"},{"location":"release_notes/greenmask_0_2_4/#changes","title":"Changes","text":"
  • Fixed a bug #244 that caused incorrect subset and transformer inheritance behavior. See the merge request #245.
"},{"location":"release_notes/greenmask_0_2_4/#full-changelog-v023v024","title":"Full Changelog: v0.2.3...v0.2.4","text":""},{"location":"release_notes/greenmask_0_2_4/#links","title":"Links","text":"

Feel free to reach out to us if you have any questions or need assistance:

  • Greenmask Roadmap
  • Email
  • Twitter
  • Telegram
  • Discord
  • DockerHub
"},{"location":"release_notes/greenmask_0_2_5/","title":"Greenmask 0.2.5","text":"

This release introduces bug fixes.

"},{"location":"release_notes/greenmask_0_2_5/#changes","title":"Changes","text":"
  • Fixed a bug where a subset query was not generated when provided #247.
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Feel free to reach out to us if you have any questions or need assistance:

  • Greenmask Roadmap
  • Email
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.state-title{fill:var(--md-mermaid-label-fg-color)!important;font-family:var(--md-mermaid-font-family)}g.stateGroup .composit{fill:var(--md-mermaid-label-bg-color)}.nodeLabel,.nodeLabel p{color:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}a .nodeLabel{text-decoration:underline}.node circle.state-end,.node circle.state-start,.start-state{fill:var(--md-mermaid-edge-color);stroke:none}.end-state-inner,.end-state-outer{fill:var(--md-mermaid-edge-color)}.end-state-inner,.node circle.state-end{stroke:var(--md-mermaid-label-bg-color)}.transition{stroke:var(--md-mermaid-edge-color)}[id^=state-fork] rect,[id^=state-join] rect{fill:var(--md-mermaid-edge-color)!important;stroke:none!important}.statediagram-cluster.statediagram-cluster .inner{fill:var(--md-default-bg-color)}.statediagram-cluster rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}.statediagram-state rect.divider{fill:var(--md-default-fg-color--lightest);stroke:var(--md-default-fg-color--lighter)}defs #statediagram-barbEnd{stroke:var(--md-mermaid-edge-color)}.attributeBoxEven,.attributeBoxOdd{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}.entityBox{fill:var(--md-mermaid-label-bg-color);stroke:var(--md-mermaid-node-fg-color)}.entityLabel{fill:var(--md-mermaid-label-fg-color);font-family:var(--md-mermaid-font-family)}.relationshipLabelBox{fill:var(--md-mermaid-label-bg-color);fill-opacity:1;background-color:var(--md-mermaid-label-bg-color);opacity:1}.relationshipLabel{fill:var(--md-mermaid-label-fg-color)}.relationshipLine{stroke:var(--md-mermaid-edge-color)}defs #ONE_OR_MORE_END *,defs #ONE_OR_MORE_START *,defs #ONLY_ONE_END *,defs #ONLY_ONE_START *,defs #ZERO_OR_MORE_END *,defs #ZERO_OR_MORE_START *,defs #ZERO_OR_ONE_END *,defs #ZERO_OR_ONE_START *{stroke:var(--md-mermaid-edge-color)!important}defs #ZERO_OR_MORE_END circle,defs #ZERO_OR_MORE_START circle{fill:var(--md-mermaid-label-bg-color)}.actor{fill:var(--md-mermaid-sequence-actor-bg-color);stroke:var(--md-mermaid-sequence-actor-border-color)}text.actor>tspan{fill:var(--md-mermaid-sequence-actor-fg-color);font-family:var(--md-mermaid-font-family)}line{stroke:var(--md-mermaid-sequence-actor-line-color)}.actor-man circle,.actor-man line{fill:var(--md-mermaid-sequence-actorman-bg-color);stroke:var(--md-mermaid-sequence-actorman-line-color)}.messageLine0,.messageLine1{stroke:var(--md-mermaid-sequence-message-line-color)}.note{fill:var(--md-mermaid-sequence-note-bg-color);stroke:var(--md-mermaid-sequence-note-border-color)}.loopText,.loopText>tspan,.messageText,.noteText>tspan{stroke:none;font-family:var(--md-mermaid-font-family)!important}.messageText{fill:var(--md-mermaid-sequence-message-fg-color)}.loopText,.loopText>tspan{fill:var(--md-mermaid-sequence-loop-fg-color)}.noteText>tspan{fill:var(--md-mermaid-sequence-note-fg-color)}#arrowhead path{fill:var(--md-mermaid-sequence-message-line-color);stroke:none}.loopLine{fill:var(--md-mermaid-sequence-loop-bg-color);stroke:var(--md-mermaid-sequence-loop-border-color)}.labelBox{fill:var(--md-mermaid-sequence-label-bg-color);stroke:none}.labelText,.labelText>span{fill:var(--md-mermaid-sequence-label-fg-color);font-family:var(--md-mermaid-font-family)}.sequenceNumber{fill:var(--md-mermaid-sequence-number-fg-color)}rect.rect{fill:var(--md-mermaid-sequence-box-bg-color);stroke:none}rect.rect+text.text{fill:var(--md-mermaid-sequence-box-fg-color)}defs #sequencenumber{fill:var(--md-mermaid-sequence-number-bg-color)!important}";var Gr,Qa=0;function Ka(){return typeof mermaid=="undefined"||mermaid instanceof Element?Tt("https://unpkg.com/mermaid@11/dist/mermaid.min.js"):I(void 0)}function Wn(e){return 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g,p=s.pipe(Z(),ie(!0));z([s,ge(e),tt(e)]).pipe(W(p),Me(1,me)).subscribe({next([{active:c},l]){let f=Ve(c),{width:u}=ce(c);e.style.setProperty("--md-indicator-x",`${f.x}px`),e.style.setProperty("--md-indicator-width",`${u}px`);let d=pr(o);(f.xd.x+l.width)&&o.scrollTo({left:Math.max(0,f.x-16),behavior:"smooth"})},complete(){e.style.removeProperty("--md-indicator-x"),e.style.removeProperty("--md-indicator-width")}}),z([Ne(o),ge(o)]).pipe(W(p)).subscribe(([c,l])=>{let f=St(o);i.hidden=c.x<16,a.hidden=c.x>f.width-l.width-16}),O(h(i,"click").pipe(m(()=>-1)),h(a,"click").pipe(m(()=>1))).pipe(W(p)).subscribe(c=>{let{width:l}=ce(o);o.scrollBy({left:l*c,behavior:"smooth"})}),r.pipe(W(p),b(c=>n.includes(c))).subscribe(c=>c.click()),o.classList.add("tabbed-labels--linked");for(let c of n){let l=R(`label[for="${c.id}"]`);l.replaceChildren(x("a",{href:`#${l.htmlFor}`,tabIndex:-1},...Array.from(l.childNodes))),h(l.firstElementChild,"click").pipe(W(p),b(f=>!(f.metaKey||f.ctrlKey)),w(f=>{f.preventDefault(),f.stopPropagation()})).subscribe(()=>{history.replaceState({},"",`#${l.htmlFor}`),l.click()})}return B("content.tabs.link")&&s.pipe(Ce(1),re(t)).subscribe(([{active:c},{offset:l}])=>{let f=c.innerText.trim();if(c.hasAttribute("data-md-switching"))c.removeAttribute("data-md-switching");else{let u=e.offsetTop-l.y;for(let y of P("[data-tabs]"))for(let L of P(":scope > input",y)){let X=R(`label[for="${L.id}"]`);if(X!==c&&X.innerText.trim()===f){X.setAttribute("data-md-switching",""),L.click();break}}window.scrollTo({top:e.offsetTop-u});let d=__md_get("__tabs")||[];__md_set("__tabs",[...new Set([f,...d])])}}),s.pipe(W(p)).subscribe(()=>{for(let c of P("audio, video",e))c.pause()}),Ya(n).pipe(w(c=>s.next(c)),_(()=>s.complete()),m(c=>$({ref:e},c)))}).pipe(Ke(se))}function zn(e,{viewport$:t,target$:r,print$:o}){return O(...P(".annotate:not(.highlight)",e).map(n=>Pn(n,{target$:r,print$:o})),...P("pre:not(.mermaid) > code",e).map(n=>jn(n,{target$:r,print$:o})),...P("pre.mermaid",e).map(n=>Wn(n)),...P("table:not([class])",e).map(n=>Vn(n)),...P("details",e).map(n=>Fn(n,{target$:r,print$:o})),...P("[data-tabs]",e).map(n=>Nn(n,{viewport$:t,target$:r})),...P("[title]",e).filter(()=>B("content.tooltips")).map(n=>mt(n,{viewport$:t})))}function Ba(e,{alert$:t}){return t.pipe(v(r=>O(I(!0),I(!1).pipe(Ge(2e3))).pipe(m(o=>({message:r,active:o})))))}function qn(e,t){let r=R(".md-typeset",e);return C(()=>{let o=new g;return o.subscribe(({message:n,active:i})=>{e.classList.toggle("md-dialog--active",i),r.textContent=n}),Ba(e,t).pipe(w(n=>o.next(n)),_(()=>o.complete()),m(n=>$({ref:e},n)))})}var Ga=0;function Ja(e,t){document.body.append(e);let{width:r}=ce(e);e.style.setProperty("--md-tooltip-width",`${r}px`),e.remove();let o=cr(t),n=typeof o!="undefined"?Ne(o):I({x:0,y:0}),i=O(et(t),$t(t)).pipe(K());return z([i,n]).pipe(m(([a,s])=>{let{x:p,y:c}=Ve(t),l=ce(t),f=t.closest("table");return f&&t.parentElement&&(p+=f.offsetLeft+t.parentElement.offsetLeft,c+=f.offsetTop+t.parentElement.offsetTop),{active:a,offset:{x:p-s.x+l.width/2-r/2,y:c-s.y+l.height+8}}}))}function Qn(e){let t=e.title;if(!t.length)return S;let r=`__tooltip_${Ga++}`,o=Rt(r,"inline"),n=R(".md-typeset",o);return n.innerHTML=t,C(()=>{let i=new g;return i.subscribe({next({offset:a}){o.style.setProperty("--md-tooltip-x",`${a.x}px`),o.style.setProperty("--md-tooltip-y",`${a.y}px`)},complete(){o.style.removeProperty("--md-tooltip-x"),o.style.removeProperty("--md-tooltip-y")}}),O(i.pipe(b(({active:a})=>a)),i.pipe(_e(250),b(({active:a})=>!a))).subscribe({next({active:a}){a?(e.insertAdjacentElement("afterend",o),e.setAttribute("aria-describedby",r),e.removeAttribute("title")):(o.remove(),e.removeAttribute("aria-describedby"),e.setAttribute("title",t))},complete(){o.remove(),e.removeAttribute("aria-describedby"),e.setAttribute("title",t)}}),i.pipe(Me(16,me)).subscribe(({active:a})=>{o.classList.toggle("md-tooltip--active",a)}),i.pipe(pt(125,me),b(()=>!!e.offsetParent),m(()=>e.offsetParent.getBoundingClientRect()),m(({x:a})=>a)).subscribe({next(a){a?o.style.setProperty("--md-tooltip-0",`${-a}px`):o.style.removeProperty("--md-tooltip-0")},complete(){o.style.removeProperty("--md-tooltip-0")}}),Ja(o,e).pipe(w(a=>i.next(a)),_(()=>i.complete()),m(a=>$({ref:e},a)))}).pipe(Ke(se))}function Xa({viewport$:e}){if(!B("header.autohide"))return I(!1);let t=e.pipe(m(({offset:{y:n}})=>n),Be(2,1),m(([n,i])=>[nMath.abs(i-n.y)>100),m(([,[n]])=>n),K()),o=ze("search");return z([e,o]).pipe(m(([{offset:n},i])=>n.y>400&&!i),K(),v(n=>n?r:I(!1)),Q(!1))}function Kn(e,t){return C(()=>z([ge(e),Xa(t)])).pipe(m(([{height:r},o])=>({height:r,hidden:o})),K((r,o)=>r.height===o.height&&r.hidden===o.hidden),G(1))}function Yn(e,{header$:t,main$:r}){return C(()=>{let o=new g,n=o.pipe(Z(),ie(!0));o.pipe(ee("active"),He(t)).subscribe(([{active:a},{hidden:s}])=>{e.classList.toggle("md-header--shadow",a&&!s),e.hidden=s});let i=ue(P("[title]",e)).pipe(b(()=>B("content.tooltips")),ne(a=>Qn(a)));return r.subscribe(o),t.pipe(W(n),m(a=>$({ref:e},a)),Re(i.pipe(W(n))))})}function Za(e,{viewport$:t,header$:r}){return mr(e,{viewport$:t,header$:r}).pipe(m(({offset:{y:o}})=>{let{height:n}=ce(e);return{active:o>=n}}),ee("active"))}function Bn(e,t){return C(()=>{let r=new g;r.subscribe({next({active:n}){e.classList.toggle("md-header__title--active",n)},complete(){e.classList.remove("md-header__title--active")}});let o=fe(".md-content h1");return typeof o=="undefined"?S:Za(o,t).pipe(w(n=>r.next(n)),_(()=>r.complete()),m(n=>$({ref:e},n)))})}function Gn(e,{viewport$:t,header$:r}){let o=r.pipe(m(({height:i})=>i),K()),n=o.pipe(v(()=>ge(e).pipe(m(({height:i})=>({top:e.offsetTop,bottom:e.offsetTop+i})),ee("bottom"))));return z([o,n,t]).pipe(m(([i,{top:a,bottom:s},{offset:{y:p},size:{height:c}}])=>(c=Math.max(0,c-Math.max(0,a-p,i)-Math.max(0,c+p-s)),{offset:a-i,height:c,active:a-i<=p})),K((i,a)=>i.offset===a.offset&&i.height===a.height&&i.active===a.active))}function es(e){let t=__md_get("__palette")||{index:e.findIndex(o=>matchMedia(o.getAttribute("data-md-color-media")).matches)},r=Math.max(0,Math.min(t.index,e.length-1));return I(...e).pipe(ne(o=>h(o,"change").pipe(m(()=>o))),Q(e[r]),m(o=>({index:e.indexOf(o),color:{media:o.getAttribute("data-md-color-media"),scheme:o.getAttribute("data-md-color-scheme"),primary:o.getAttribute("data-md-color-primary"),accent:o.getAttribute("data-md-color-accent")}})),G(1))}function Jn(e){let t=P("input",e),r=x("meta",{name:"theme-color"});document.head.appendChild(r);let o=x("meta",{name:"color-scheme"});document.head.appendChild(o);let n=Pt("(prefers-color-scheme: light)");return C(()=>{let i=new g;return i.subscribe(a=>{if(document.body.setAttribute("data-md-color-switching",""),a.color.media==="(prefers-color-scheme)"){let s=matchMedia("(prefers-color-scheme: light)"),p=document.querySelector(s.matches?"[data-md-color-media='(prefers-color-scheme: light)']":"[data-md-color-media='(prefers-color-scheme: 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Jr=Mt(Br());function ts(e){e.setAttribute("data-md-copying","");let t=e.closest("[data-copy]"),r=t?t.getAttribute("data-copy"):e.innerText;return e.removeAttribute("data-md-copying"),r.trimEnd()}function Zn({alert$:e}){Jr.default.isSupported()&&new j(t=>{new Jr.default("[data-clipboard-target], [data-clipboard-text]",{text:r=>r.getAttribute("data-clipboard-text")||ts(R(r.getAttribute("data-clipboard-target")))}).on("success",r=>t.next(r))}).pipe(w(t=>{t.trigger.focus()}),m(()=>Ee("clipboard.copied"))).subscribe(e)}function ei(e,t){return e.protocol=t.protocol,e.hostname=t.hostname,e}function rs(e,t){let r=new Map;for(let o of P("url",e)){let n=R("loc",o),i=[ei(new URL(n.textContent),t)];r.set(`${i[0]}`,i);for(let a of P("[rel=alternate]",o)){let s=a.getAttribute("href");s!=null&&i.push(ei(new URL(s),t))}}return r}function ur(e){return un(new URL("sitemap.xml",e)).pipe(m(t=>rs(t,new URL(e))),de(()=>I(new Map)))}function os(e,t){if(!(e.target instanceof Element))return S;let r=e.target.closest("a");if(r===null)return S;if(r.target||e.metaKey||e.ctrlKey)return S;let o=new URL(r.href);return o.search=o.hash="",t.has(`${o}`)?(e.preventDefault(),I(new URL(r.href))):S}function ti(e){let t=new Map;for(let r of P(":scope > *",e.head))t.set(r.outerHTML,r);return t}function ri(e){for(let t of P("[href], [src]",e))for(let r of["href","src"]){let o=t.getAttribute(r);if(o&&!/^(?:[a-z]+:)?\/\//i.test(o)){t[r]=t[r];break}}return I(e)}function ns(e){for(let o of["[data-md-component=announce]","[data-md-component=container]","[data-md-component=header-topic]","[data-md-component=outdated]","[data-md-component=logo]","[data-md-component=skip]",...B("navigation.tabs.sticky")?["[data-md-component=tabs]"]:[]]){let n=fe(o),i=fe(o,e);typeof n!="undefined"&&typeof i!="undefined"&&n.replaceWith(i)}let t=ti(document);for(let[o,n]of ti(e))t.has(o)?t.delete(o):document.head.appendChild(n);for(let o of t.values()){let 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t.pipe(m(({value:r})=>{let o=ye();return o.hash="",r=r.replace(/\s+/g,"+").replace(/&/g,"%26").replace(/=/g,"%3D"),o.search=`q=${r}`,{url:o}}))}function mi(e,t){let r=new g,o=r.pipe(Z(),ie(!0));return r.subscribe(({url:n})=>{e.setAttribute("data-clipboard-text",e.href),e.href=`${n}`}),h(e,"click").pipe(W(o)).subscribe(n=>n.preventDefault()),ms(e,t).pipe(w(n=>r.next(n)),_(()=>r.complete()),m(n=>$({ref:e},n)))}function fi(e,{worker$:t,keyboard$:r}){let o=new g,n=Se("search-query"),i=O(h(n,"keydown"),h(n,"focus")).pipe(ve(se),m(()=>n.value),K());return o.pipe(He(i),m(([{suggest:s},p])=>{let c=p.split(/([\s-]+)/);if(s!=null&&s.length&&c[c.length-1]){let l=s[s.length-1];l.startsWith(c[c.length-1])&&(c[c.length-1]=l)}else c.length=0;return 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rt=Kn(Se("header"),{viewport$:Oe}),Ft=ot.pipe(m(()=>Se("main")),v(e=>Gn(e,{viewport$:Oe,header$:rt})),G(1)),xs=O(...ae("consent").map(e=>En(e,{target$:Lt})),...ae("dialog").map(e=>qn(e,{alert$:ro})),...ae("header").map(e=>Yn(e,{viewport$:Oe,header$:rt,main$:Ft})),...ae("palette").map(e=>Jn(e)),...ae("progress").map(e=>Xn(e,{progress$:oo})),...ae("search").map(e=>ui(e,{index$:Ai,keyboard$:to})),...ae("source").map(e=>gi(e))),Es=C(()=>O(...ae("announce").map(e=>xn(e)),...ae("content").map(e=>zn(e,{viewport$:Oe,target$:Lt,print$:_i})),...ae("content").map(e=>B("search.highlight")?di(e,{index$:Ai,location$:Ut}):S),...ae("header-title").map(e=>Bn(e,{viewport$:Oe,header$:rt})),...ae("sidebar").map(e=>e.getAttribute("data-md-type")==="navigation"?Nr(Mi,()=>Zr(e,{viewport$:Oe,header$:rt,main$:Ft})):Nr(hr,()=>Zr(e,{viewport$:Oe,header$:rt,main$:Ft}))),...ae("tabs").map(e=>yi(e,{viewport$:Oe,header$:rt})),...ae("toc").map(e=>xi(e,{viewport$:Oe,header$:rt,main$:Ft,target$:Lt})),...ae("top").map(e=>Ei(e,{viewport$:Oe,header$:rt,main$:Ft,target$:Lt})))),Ci=ot.pipe(v(()=>Es),Re(xs),G(1));Ci.subscribe();window.document$=ot;window.location$=Ut;window.target$=Lt;window.keyboard$=to;window.viewport$=Oe;window.tablet$=hr;window.screen$=Mi;window.print$=_i;window.alert$=ro;window.progress$=oo;window.component$=Ci;})(); +//# sourceMappingURL=bundle.525ec568.min.js.map + diff --git a/v0.2.5/assets/javascripts/bundle.525ec568.min.js.map b/v0.2.5/assets/javascripts/bundle.525ec568.min.js.map new file mode 100644 index 00000000..ef5d8d34 --- /dev/null +++ b/v0.2.5/assets/javascripts/bundle.525ec568.min.js.map @@ -0,0 +1,7 @@ +{ + "version": 3, + "sources": ["node_modules/focus-visible/dist/focus-visible.js", "node_modules/escape-html/index.js", "node_modules/clipboard/dist/clipboard.js", "src/templates/assets/javascripts/bundle.ts", "node_modules/tslib/tslib.es6.mjs", "node_modules/rxjs/src/internal/util/isFunction.ts", "node_modules/rxjs/src/internal/util/createErrorClass.ts", "node_modules/rxjs/src/internal/util/UnsubscriptionError.ts", "node_modules/rxjs/src/internal/util/arrRemove.ts", "node_modules/rxjs/src/internal/Subscription.ts", "node_modules/rxjs/src/internal/config.ts", "node_modules/rxjs/src/internal/scheduler/timeoutProvider.ts", "node_modules/rxjs/src/internal/util/reportUnhandledError.ts", "node_modules/rxjs/src/internal/util/noop.ts", "node_modules/rxjs/src/internal/NotificationFactories.ts", "node_modules/rxjs/src/internal/util/errorContext.ts", "node_modules/rxjs/src/internal/Subscriber.ts", "node_modules/rxjs/src/internal/symbol/observable.ts", "node_modules/rxjs/src/internal/util/identity.ts", "node_modules/rxjs/src/internal/util/pipe.ts", "node_modules/rxjs/src/internal/Observable.ts", "node_modules/rxjs/src/internal/util/lift.ts", "node_modules/rxjs/src/internal/operators/OperatorSubscriber.ts", "node_modules/rxjs/src/internal/scheduler/animationFrameProvider.ts", "node_modules/rxjs/src/internal/util/ObjectUnsubscribedError.ts", "node_modules/rxjs/src/internal/Subject.ts", "node_modules/rxjs/src/internal/BehaviorSubject.ts", "node_modules/rxjs/src/internal/scheduler/dateTimestampProvider.ts", "node_modules/rxjs/src/internal/ReplaySubject.ts", "node_modules/rxjs/src/internal/scheduler/Action.ts", "node_modules/rxjs/src/internal/scheduler/intervalProvider.ts", "node_modules/rxjs/src/internal/scheduler/AsyncAction.ts", "node_modules/rxjs/src/internal/Scheduler.ts", "node_modules/rxjs/src/internal/scheduler/AsyncScheduler.ts", "node_modules/rxjs/src/internal/scheduler/async.ts", "node_modules/rxjs/src/internal/scheduler/QueueAction.ts", "node_modules/rxjs/src/internal/scheduler/QueueScheduler.ts", "node_modules/rxjs/src/internal/scheduler/queue.ts", "node_modules/rxjs/src/internal/scheduler/AnimationFrameAction.ts", "node_modules/rxjs/src/internal/scheduler/AnimationFrameScheduler.ts", "node_modules/rxjs/src/internal/scheduler/animationFrame.ts", "node_modules/rxjs/src/internal/observable/empty.ts", "node_modules/rxjs/src/internal/util/isScheduler.ts", "node_modules/rxjs/src/internal/util/args.ts", "node_modules/rxjs/src/internal/util/isArrayLike.ts", "node_modules/rxjs/src/internal/util/isPromise.ts", "node_modules/rxjs/src/internal/util/isInteropObservable.ts", "node_modules/rxjs/src/internal/util/isAsyncIterable.ts", "node_modules/rxjs/src/internal/util/throwUnobservableError.ts", "node_modules/rxjs/src/internal/symbol/iterator.ts", "node_modules/rxjs/src/internal/util/isIterable.ts", "node_modules/rxjs/src/internal/util/isReadableStreamLike.ts", "node_modules/rxjs/src/internal/observable/innerFrom.ts", "node_modules/rxjs/src/internal/util/executeSchedule.ts", "node_modules/rxjs/src/internal/operators/observeOn.ts", "node_modules/rxjs/src/internal/operators/subscribeOn.ts", "node_modules/rxjs/src/internal/scheduled/scheduleObservable.ts", "node_modules/rxjs/src/internal/scheduled/schedulePromise.ts", "node_modules/rxjs/src/internal/scheduled/scheduleArray.ts", "node_modules/rxjs/src/internal/scheduled/scheduleIterable.ts", "node_modules/rxjs/src/internal/scheduled/scheduleAsyncIterable.ts", "node_modules/rxjs/src/internal/scheduled/scheduleReadableStreamLike.ts", "node_modules/rxjs/src/internal/scheduled/scheduled.ts", "node_modules/rxjs/src/internal/observable/from.ts", "node_modules/rxjs/src/internal/observable/of.ts", "node_modules/rxjs/src/internal/observable/throwError.ts", "node_modules/rxjs/src/internal/util/EmptyError.ts", "node_modules/rxjs/src/internal/util/isDate.ts", "node_modules/rxjs/src/internal/operators/map.ts", "node_modules/rxjs/src/internal/util/mapOneOrManyArgs.ts", "node_modules/rxjs/src/internal/util/argsArgArrayOrObject.ts", "node_modules/rxjs/src/internal/util/createObject.ts", "node_modules/rxjs/src/internal/observable/combineLatest.ts", "node_modules/rxjs/src/internal/operators/mergeInternals.ts", "node_modules/rxjs/src/internal/operators/mergeMap.ts", "node_modules/rxjs/src/internal/operators/mergeAll.ts", "node_modules/rxjs/src/internal/operators/concatAll.ts", "node_modules/rxjs/src/internal/observable/concat.ts", "node_modules/rxjs/src/internal/observable/defer.ts", "node_modules/rxjs/src/internal/observable/fromEvent.ts", "node_modules/rxjs/src/internal/observable/fromEventPattern.ts", "node_modules/rxjs/src/internal/observable/timer.ts", "node_modules/rxjs/src/internal/observable/merge.ts", "node_modules/rxjs/src/internal/observable/never.ts", "node_modules/rxjs/src/internal/util/argsOrArgArray.ts", "node_modules/rxjs/src/internal/operators/filter.ts", "node_modules/rxjs/src/internal/observable/zip.ts", "node_modules/rxjs/src/internal/operators/audit.ts", "node_modules/rxjs/src/internal/operators/auditTime.ts", "node_modules/rxjs/src/internal/operators/bufferCount.ts", "node_modules/rxjs/src/internal/operators/catchError.ts", "node_modules/rxjs/src/internal/operators/scanInternals.ts", "node_modules/rxjs/src/internal/operators/combineLatest.ts", "node_modules/rxjs/src/internal/operators/combineLatestWith.ts", "node_modules/rxjs/src/internal/operators/debounce.ts", "node_modules/rxjs/src/internal/operators/debounceTime.ts", "node_modules/rxjs/src/internal/operators/defaultIfEmpty.ts", "node_modules/rxjs/src/internal/operators/take.ts", "node_modules/rxjs/src/internal/operators/ignoreElements.ts", "node_modules/rxjs/src/internal/operators/mapTo.ts", "node_modules/rxjs/src/internal/operators/delayWhen.ts", "node_modules/rxjs/src/internal/operators/delay.ts", "node_modules/rxjs/src/internal/operators/distinctUntilChanged.ts", "node_modules/rxjs/src/internal/operators/distinctUntilKeyChanged.ts", "node_modules/rxjs/src/internal/operators/throwIfEmpty.ts", "node_modules/rxjs/src/internal/operators/endWith.ts", "node_modules/rxjs/src/internal/operators/finalize.ts", "node_modules/rxjs/src/internal/operators/first.ts", "node_modules/rxjs/src/internal/operators/takeLast.ts", "node_modules/rxjs/src/internal/operators/merge.ts", "node_modules/rxjs/src/internal/operators/mergeWith.ts", "node_modules/rxjs/src/internal/operators/repeat.ts", "node_modules/rxjs/src/internal/operators/scan.ts", "node_modules/rxjs/src/internal/operators/share.ts", "node_modules/rxjs/src/internal/operators/shareReplay.ts", 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"src/templates/assets/javascripts/utilities/round/index.ts", "src/templates/assets/javascripts/browser/script/index.ts", "src/templates/assets/javascripts/browser/element/size/_/index.ts", "src/templates/assets/javascripts/browser/element/size/content/index.ts", "src/templates/assets/javascripts/browser/element/offset/_/index.ts", "src/templates/assets/javascripts/browser/element/offset/content/index.ts", "src/templates/assets/javascripts/browser/element/visibility/index.ts", "src/templates/assets/javascripts/browser/toggle/index.ts", "src/templates/assets/javascripts/browser/keyboard/index.ts", "src/templates/assets/javascripts/browser/location/_/index.ts", "src/templates/assets/javascripts/browser/location/hash/index.ts", "src/templates/assets/javascripts/browser/media/index.ts", "src/templates/assets/javascripts/browser/request/index.ts", "src/templates/assets/javascripts/browser/viewport/offset/index.ts", "src/templates/assets/javascripts/browser/viewport/size/index.ts", "src/templates/assets/javascripts/browser/viewport/_/index.ts", "src/templates/assets/javascripts/browser/viewport/at/index.ts", "src/templates/assets/javascripts/browser/worker/index.ts", "src/templates/assets/javascripts/_/index.ts", "src/templates/assets/javascripts/components/_/index.ts", "src/templates/assets/javascripts/components/announce/index.ts", "src/templates/assets/javascripts/components/consent/index.ts", "src/templates/assets/javascripts/templates/tooltip/index.tsx", "src/templates/assets/javascripts/templates/annotation/index.tsx", "src/templates/assets/javascripts/templates/clipboard/index.tsx", "src/templates/assets/javascripts/templates/search/index.tsx", "src/templates/assets/javascripts/templates/source/index.tsx", "src/templates/assets/javascripts/templates/tabbed/index.tsx", "src/templates/assets/javascripts/templates/table/index.tsx", "src/templates/assets/javascripts/templates/version/index.tsx", "src/templates/assets/javascripts/components/tooltip2/index.ts", "src/templates/assets/javascripts/components/content/annotation/_/index.ts", "src/templates/assets/javascripts/components/content/annotation/list/index.ts", "src/templates/assets/javascripts/components/content/annotation/block/index.ts", "src/templates/assets/javascripts/components/content/code/_/index.ts", "src/templates/assets/javascripts/components/content/details/index.ts", "src/templates/assets/javascripts/components/content/mermaid/index.css", "src/templates/assets/javascripts/components/content/mermaid/index.ts", "src/templates/assets/javascripts/components/content/table/index.ts", "src/templates/assets/javascripts/components/content/tabs/index.ts", "src/templates/assets/javascripts/components/content/_/index.ts", "src/templates/assets/javascripts/components/dialog/index.ts", "src/templates/assets/javascripts/components/tooltip/index.ts", "src/templates/assets/javascripts/components/header/_/index.ts", "src/templates/assets/javascripts/components/header/title/index.ts", "src/templates/assets/javascripts/components/main/index.ts", "src/templates/assets/javascripts/components/palette/index.ts", "src/templates/assets/javascripts/components/progress/index.ts", "src/templates/assets/javascripts/integrations/clipboard/index.ts", "src/templates/assets/javascripts/integrations/sitemap/index.ts", "src/templates/assets/javascripts/integrations/instant/index.ts", "src/templates/assets/javascripts/integrations/search/highlighter/index.ts", "src/templates/assets/javascripts/integrations/search/worker/message/index.ts", "src/templates/assets/javascripts/integrations/search/worker/_/index.ts", "src/templates/assets/javascripts/integrations/version/findurl/index.ts", "src/templates/assets/javascripts/integrations/version/index.ts", "src/templates/assets/javascripts/components/search/query/index.ts", "src/templates/assets/javascripts/components/search/result/index.ts", "src/templates/assets/javascripts/components/search/share/index.ts", "src/templates/assets/javascripts/components/search/suggest/index.ts", "src/templates/assets/javascripts/components/search/_/index.ts", "src/templates/assets/javascripts/components/search/highlight/index.ts", "src/templates/assets/javascripts/components/sidebar/index.ts", "src/templates/assets/javascripts/components/source/facts/github/index.ts", "src/templates/assets/javascripts/components/source/facts/gitlab/index.ts", "src/templates/assets/javascripts/components/source/facts/_/index.ts", "src/templates/assets/javascripts/components/source/_/index.ts", "src/templates/assets/javascripts/components/tabs/index.ts", "src/templates/assets/javascripts/components/toc/index.ts", "src/templates/assets/javascripts/components/top/index.ts", "src/templates/assets/javascripts/patches/ellipsis/index.ts", "src/templates/assets/javascripts/patches/indeterminate/index.ts", "src/templates/assets/javascripts/patches/scrollfix/index.ts", "src/templates/assets/javascripts/patches/scrolllock/index.ts", "src/templates/assets/javascripts/polyfills/index.ts"], + "sourcesContent": ["(function (global, factory) {\n typeof exports === 'object' && typeof module !== 'undefined' ? factory() :\n typeof define === 'function' && define.amd ? define(factory) :\n (factory());\n}(this, (function () { 'use strict';\n\n /**\n * Applies the :focus-visible polyfill at the given scope.\n * A scope in this case is either the top-level Document or a Shadow Root.\n *\n * @param {(Document|ShadowRoot)} scope\n * @see https://github.com/WICG/focus-visible\n */\n function applyFocusVisiblePolyfill(scope) {\n var hadKeyboardEvent = true;\n var hadFocusVisibleRecently = false;\n var hadFocusVisibleRecentlyTimeout = null;\n\n var inputTypesAllowlist = {\n text: true,\n search: true,\n url: true,\n tel: true,\n email: true,\n password: true,\n number: true,\n date: true,\n month: true,\n week: true,\n time: true,\n datetime: true,\n 'datetime-local': true\n };\n\n /**\n * Helper function for legacy browsers and iframes which sometimes focus\n * elements like document, body, and non-interactive SVG.\n * @param {Element} el\n */\n function isValidFocusTarget(el) {\n if (\n el &&\n el !== document &&\n el.nodeName !== 'HTML' &&\n el.nodeName !== 'BODY' &&\n 'classList' in el &&\n 'contains' in el.classList\n ) {\n return true;\n }\n return false;\n }\n\n /**\n * Computes whether the given element should automatically trigger the\n * `focus-visible` class being added, i.e. whether it should always match\n * `:focus-visible` when focused.\n * @param {Element} el\n * @return {boolean}\n */\n function focusTriggersKeyboardModality(el) {\n var type = el.type;\n var tagName = el.tagName;\n\n if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n return true;\n }\n\n if (tagName === 'TEXTAREA' && !el.readOnly) {\n return true;\n }\n\n if (el.isContentEditable) {\n return true;\n }\n\n return false;\n }\n\n /**\n * Add the `focus-visible` class to the given element if it was not added by\n * the author.\n * @param {Element} el\n */\n function addFocusVisibleClass(el) {\n if (el.classList.contains('focus-visible')) {\n return;\n }\n el.classList.add('focus-visible');\n el.setAttribute('data-focus-visible-added', '');\n }\n\n /**\n * Remove the `focus-visible` class from the given element if it was not\n * originally added by the author.\n * @param {Element} el\n */\n function removeFocusVisibleClass(el) {\n if (!el.hasAttribute('data-focus-visible-added')) {\n return;\n }\n el.classList.remove('focus-visible');\n el.removeAttribute('data-focus-visible-added');\n }\n\n /**\n * If the most recent user interaction was via the keyboard;\n * and the key press did not include a meta, alt/option, or control key;\n * then the modality is keyboard. Otherwise, the modality is not keyboard.\n * Apply `focus-visible` to any current active element and keep track\n * of our keyboard modality state with `hadKeyboardEvent`.\n * @param {KeyboardEvent} e\n */\n function onKeyDown(e) {\n if (e.metaKey || e.altKey || e.ctrlKey) {\n return;\n }\n\n if (isValidFocusTarget(scope.activeElement)) {\n addFocusVisibleClass(scope.activeElement);\n }\n\n hadKeyboardEvent = true;\n }\n\n /**\n * If at any point a user clicks with a pointing device, ensure that we change\n * the modality away from keyboard.\n * This avoids the situation where a user presses a key on an already focused\n * element, and then clicks on a different element, focusing it with a\n * pointing device, while we still think we're in keyboard modality.\n * @param {Event} e\n */\n function onPointerDown(e) {\n hadKeyboardEvent = false;\n }\n\n /**\n * On `focus`, add the `focus-visible` class to the target if:\n * - the target received focus as a result of keyboard navigation, or\n * - the event target is an element that will likely require interaction\n * via the keyboard (e.g. a text box)\n * @param {Event} e\n */\n function onFocus(e) {\n // Prevent IE from focusing the document or HTML element.\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n addFocusVisibleClass(e.target);\n }\n }\n\n /**\n * On `blur`, remove the `focus-visible` class from the target.\n * @param {Event} e\n */\n function onBlur(e) {\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (\n e.target.classList.contains('focus-visible') ||\n e.target.hasAttribute('data-focus-visible-added')\n ) {\n // To detect a tab/window switch, we look for a blur event followed\n // rapidly by a visibility change.\n // If we don't see a visibility change within 100ms, it's probably a\n // regular focus change.\n hadFocusVisibleRecently = true;\n window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n hadFocusVisibleRecently = false;\n }, 100);\n removeFocusVisibleClass(e.target);\n }\n }\n\n /**\n * If the user changes tabs, keep track of whether or not the previously\n * focused element had .focus-visible.\n * @param {Event} e\n */\n function onVisibilityChange(e) {\n if (document.visibilityState === 'hidden') {\n // If the tab becomes active again, the browser will handle calling focus\n // on the element (Safari actually calls it twice).\n // If this tab change caused a blur on an element with focus-visible,\n // re-apply the class when the user switches back to the tab.\n if (hadFocusVisibleRecently) {\n hadKeyboardEvent = true;\n }\n addInitialPointerMoveListeners();\n }\n }\n\n /**\n * Add a group of listeners to detect usage of any pointing devices.\n * These listeners will be added when the polyfill first loads, and anytime\n * the window is blurred, so that they are active when the window regains\n * focus.\n */\n function addInitialPointerMoveListeners() {\n document.addEventListener('mousemove', onInitialPointerMove);\n document.addEventListener('mousedown', onInitialPointerMove);\n document.addEventListener('mouseup', onInitialPointerMove);\n document.addEventListener('pointermove', onInitialPointerMove);\n document.addEventListener('pointerdown', onInitialPointerMove);\n document.addEventListener('pointerup', onInitialPointerMove);\n document.addEventListener('touchmove', onInitialPointerMove);\n document.addEventListener('touchstart', onInitialPointerMove);\n document.addEventListener('touchend', onInitialPointerMove);\n }\n\n function removeInitialPointerMoveListeners() {\n document.removeEventListener('mousemove', onInitialPointerMove);\n document.removeEventListener('mousedown', onInitialPointerMove);\n document.removeEventListener('mouseup', onInitialPointerMove);\n document.removeEventListener('pointermove', onInitialPointerMove);\n document.removeEventListener('pointerdown', onInitialPointerMove);\n document.removeEventListener('pointerup', onInitialPointerMove);\n document.removeEventListener('touchmove', onInitialPointerMove);\n document.removeEventListener('touchstart', onInitialPointerMove);\n document.removeEventListener('touchend', onInitialPointerMove);\n }\n\n /**\n * When the polfyill first loads, assume the user is in keyboard modality.\n * If any event is received from a pointing device (e.g. mouse, pointer,\n * touch), turn off keyboard modality.\n * This accounts for situations where focus enters the page from the URL bar.\n * @param {Event} e\n */\n function onInitialPointerMove(e) {\n // Work around a Safari quirk that fires a mousemove on whenever the\n // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n return;\n }\n\n hadKeyboardEvent = false;\n removeInitialPointerMoveListeners();\n }\n\n // For some kinds of state, we are interested in changes at the global scope\n // only. For example, global pointer input, global key presses and global\n // visibility change should affect the state at every scope:\n document.addEventListener('keydown', onKeyDown, true);\n document.addEventListener('mousedown', onPointerDown, true);\n document.addEventListener('pointerdown', onPointerDown, true);\n document.addEventListener('touchstart', onPointerDown, true);\n document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n addInitialPointerMoveListeners();\n\n // For focus and blur, we specifically care about state changes in the local\n // scope. This is because focus / blur events that originate from within a\n // shadow root are not re-dispatched from the host element if it was already\n // the active element in its own scope:\n scope.addEventListener('focus', onFocus, true);\n scope.addEventListener('blur', onBlur, true);\n\n // We detect that a node is a ShadowRoot by ensuring that it is a\n // DocumentFragment and also has a host property. This check covers native\n // implementation and polyfill implementation transparently. If we only cared\n // about the native implementation, we could just check if the scope was\n // an instance of a ShadowRoot.\n if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n // have a root element to add a class to. So, we add this attribute to the\n // host element instead:\n scope.host.setAttribute('data-js-focus-visible', '');\n } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n document.documentElement.classList.add('js-focus-visible');\n document.documentElement.setAttribute('data-js-focus-visible', '');\n }\n }\n\n // It is important to wrap all references to global window and document in\n // these checks to support server-side rendering use cases\n // @see https://github.com/WICG/focus-visible/issues/199\n if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n // Make the polyfill helper globally available. This can be used as a signal\n // to interested libraries that wish to coordinate with the polyfill for e.g.,\n // applying the polyfill to a shadow root:\n window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n // Notify interested libraries of the polyfill's presence, in case the\n // polyfill was loaded lazily:\n var event;\n\n try {\n event = new CustomEvent('focus-visible-polyfill-ready');\n } catch (error) {\n // IE11 does not support using CustomEvent as a constructor directly:\n event = document.createEvent('CustomEvent');\n event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n }\n\n window.dispatchEvent(event);\n }\n\n if (typeof document !== 'undefined') {\n // Apply the polyfill to the global document, so that no JavaScript\n // coordination is required to use the polyfill in the top-level document:\n applyFocusVisiblePolyfill(document);\n }\n\n})));\n", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n var str = '' + string;\n var match = matchHtmlRegExp.exec(str);\n\n if (!match) {\n return str;\n }\n\n var escape;\n var html = '';\n var index = 0;\n var lastIndex = 0;\n\n for (index = match.index; index < str.length; index++) {\n switch (str.charCodeAt(index)) {\n case 34: // \"\n escape = '"';\n break;\n case 38: // &\n escape = '&';\n break;\n case 39: // '\n escape = ''';\n break;\n case 60: // <\n escape = '<';\n break;\n case 62: // >\n escape = '>';\n break;\n default:\n continue;\n }\n\n if (lastIndex !== index) {\n html += str.substring(lastIndex, index);\n }\n\n lastIndex = index + 1;\n html += escape;\n }\n\n return lastIndex !== index\n ? html + str.substring(lastIndex, index)\n : html;\n}\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n try {\n return document.execCommand(type);\n } catch (err) {\n return false;\n }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n var selectedText = select_default()(target);\n command('cut');\n return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n fakeElement.style.fontSize = '12pt'; // Reset box model\n\n fakeElement.style.border = '0';\n fakeElement.style.padding = '0';\n fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n fakeElement.style.position = 'absolute';\n fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n fakeElement.style.top = \"\".concat(yPosition, \"px\");\n fakeElement.setAttribute('readonly', '');\n fakeElement.value = value;\n return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n var fakeElement = createFakeElement(value);\n options.container.appendChild(fakeElement);\n var selectedText = select_default()(fakeElement);\n command('copy');\n fakeElement.remove();\n return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n var selectedText = '';\n\n if (typeof target === 'string') {\n selectedText = fakeCopyAction(target, options);\n } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n selectedText = fakeCopyAction(target.value, options);\n } else {\n selectedText = select_default()(target);\n command('copy');\n }\n\n return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n // Defines base properties passed from constructor.\n var _options$action = options.action,\n action = _options$action === void 0 ? 'copy' : _options$action,\n container = options.container,\n target = options.target,\n text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n if (action !== 'copy' && action !== 'cut') {\n throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n } // Sets the `target` property using an element that will be have its content copied.\n\n\n if (target !== undefined) {\n if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n if (action === 'copy' && target.hasAttribute('disabled')) {\n throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n }\n\n if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n }\n } else {\n throw new Error('Invalid \"target\" value, use a valid Element');\n }\n } // Define selection strategy based on `text` property.\n\n\n if (text) {\n return actions_copy(text, {\n container: container\n });\n } // Defines which selection strategy based on `target` property.\n\n\n if (target) {\n return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n container: container\n });\n }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n var attribute = \"data-clipboard-\".concat(suffix);\n\n if (!element.hasAttribute(attribute)) {\n return;\n }\n\n return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n _inherits(Clipboard, _Emitter);\n\n var _super = _createSuper(Clipboard);\n\n /**\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n * @param {Object} options\n */\n function Clipboard(trigger, options) {\n var _this;\n\n _classCallCheck(this, Clipboard);\n\n _this = _super.call(this);\n\n _this.resolveOptions(options);\n\n _this.listenClick(trigger);\n\n return _this;\n }\n /**\n * Defines if attributes would be resolved using internal setter functions\n * or custom functions that were passed in the constructor.\n * @param {Object} options\n */\n\n\n _createClass(Clipboard, [{\n key: \"resolveOptions\",\n value: function resolveOptions() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n }\n /**\n * Adds a click event listener to the passed trigger.\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n */\n\n }, {\n key: \"listenClick\",\n value: function listenClick(trigger) {\n var _this2 = this;\n\n this.listener = listen_default()(trigger, 'click', function (e) {\n return _this2.onClick(e);\n });\n }\n /**\n * Defines a new `ClipboardAction` on each click event.\n * @param {Event} e\n */\n\n }, {\n key: \"onClick\",\n value: function onClick(e) {\n var trigger = e.delegateTarget || e.currentTarget;\n var action = this.action(trigger) || 'copy';\n var text = actions_default({\n action: action,\n container: this.container,\n target: this.target(trigger),\n text: this.text(trigger)\n }); // Fires an event based on the copy operation result.\n\n this.emit(text ? 'success' : 'error', {\n action: action,\n text: text,\n trigger: trigger,\n clearSelection: function clearSelection() {\n if (trigger) {\n trigger.focus();\n }\n\n window.getSelection().removeAllRanges();\n }\n });\n }\n /**\n * Default `action` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultAction\",\n value: function defaultAction(trigger) {\n return getAttributeValue('action', trigger);\n }\n /**\n * Default `target` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultTarget\",\n value: function defaultTarget(trigger) {\n var selector = getAttributeValue('target', trigger);\n\n if (selector) {\n return document.querySelector(selector);\n }\n }\n /**\n * Allow fire programmatically a copy action\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @returns Text copied.\n */\n\n }, {\n key: \"defaultText\",\n\n /**\n * Default `text` lookup function.\n * @param {Element} trigger\n */\n value: function defaultText(trigger) {\n return getAttributeValue('text', trigger);\n }\n /**\n * Destroy lifecycle.\n */\n\n }, {\n key: \"destroy\",\n value: function destroy() {\n this.listener.destroy();\n }\n }], [{\n key: \"copy\",\n value: function copy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n return actions_copy(target, options);\n }\n /**\n * Allow fire programmatically a cut action\n * @param {String|HTMLElement} target\n * @returns Text cutted.\n */\n\n }, {\n key: \"cut\",\n value: function cut(target) {\n return actions_cut(target);\n }\n /**\n * Returns the support of the given action, or all actions if no action is\n * given.\n * @param {String} [action]\n */\n\n }, {\n key: \"isSupported\",\n value: function isSupported() {\n var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n var actions = typeof action === 'string' ? [action] : action;\n var support = !!document.queryCommandSupported;\n actions.forEach(function (action) {\n support = support && !!document.queryCommandSupported(action);\n });\n return support;\n }\n }]);\n\n return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n var proto = Element.prototype;\n\n proto.matches = proto.matchesSelector ||\n proto.mozMatchesSelector ||\n proto.msMatchesSelector ||\n proto.oMatchesSelector ||\n proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n if (typeof element.matches === 'function' &&\n element.matches(selector)) {\n return element;\n }\n element = element.parentNode;\n }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n var listenerFn = listener.apply(this, arguments);\n\n element.addEventListener(type, listenerFn, useCapture);\n\n return {\n destroy: function() {\n element.removeEventListener(type, listenerFn, useCapture);\n }\n }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n // Handle the regular Element usage\n if (typeof elements.addEventListener === 'function') {\n return _delegate.apply(null, arguments);\n }\n\n // Handle Element-less usage, it defaults to global delegation\n if (typeof type === 'function') {\n // Use `document` as the first parameter, then apply arguments\n // This is a short way to .unshift `arguments` without running into deoptimizations\n return _delegate.bind(null, document).apply(null, arguments);\n }\n\n // Handle Selector-based usage\n if (typeof elements === 'string') {\n elements = document.querySelectorAll(elements);\n }\n\n // Handle Array-like based usage\n return Array.prototype.map.call(elements, function (element) {\n return _delegate(element, selector, type, callback, useCapture);\n });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n return function(e) {\n e.delegateTarget = closest(e.target, selector);\n\n if (e.delegateTarget) {\n callback.call(element, e);\n }\n }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n return value !== undefined\n && value instanceof HTMLElement\n && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return value !== undefined\n && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n && ('length' in value)\n && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n return typeof value === 'string'\n || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n if (!target && !type && !callback) {\n throw new Error('Missing required arguments');\n }\n\n if (!is.string(type)) {\n throw new TypeError('Second argument must be a String');\n }\n\n if (!is.fn(callback)) {\n throw new TypeError('Third argument must be a Function');\n }\n\n if (is.node(target)) {\n return listenNode(target, type, callback);\n }\n else if (is.nodeList(target)) {\n return listenNodeList(target, type, callback);\n }\n else if (is.string(target)) {\n return listenSelector(target, type, callback);\n }\n else {\n throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n node.addEventListener(type, callback);\n\n return {\n destroy: function() {\n node.removeEventListener(type, callback);\n }\n }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.addEventListener(type, callback);\n });\n\n return {\n destroy: function() {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.removeEventListener(type, callback);\n });\n }\n }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n var selectedText;\n\n if (element.nodeName === 'SELECT') {\n element.focus();\n\n selectedText = element.value;\n }\n else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n var isReadOnly = element.hasAttribute('readonly');\n\n if (!isReadOnly) {\n element.setAttribute('readonly', '');\n }\n\n element.select();\n element.setSelectionRange(0, element.value.length);\n\n if (!isReadOnly) {\n element.removeAttribute('readonly');\n }\n\n selectedText = element.value;\n }\n else {\n if (element.hasAttribute('contenteditable')) {\n element.focus();\n }\n\n var selection = window.getSelection();\n var range = document.createRange();\n\n range.selectNodeContents(element);\n selection.removeAllRanges();\n selection.addRange(range);\n\n selectedText = selection.toString();\n }\n\n return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n // Keep this empty so it's easier to inherit from\n // (via https://github.com/lipsmack from https://github.com/scottcorgan/tiny-emitter/issues/3)\n}\n\nE.prototype = {\n on: function (name, callback, ctx) {\n var e = this.e || (this.e = {});\n\n (e[name] || (e[name] = [])).push({\n fn: callback,\n ctx: ctx\n });\n\n return this;\n },\n\n once: function (name, callback, ctx) {\n var self = this;\n function listener () {\n self.off(name, listener);\n callback.apply(ctx, arguments);\n };\n\n listener._ = callback\n return this.on(name, listener, ctx);\n },\n\n emit: function (name) {\n var data = [].slice.call(arguments, 1);\n var evtArr = ((this.e || (this.e = {}))[name] || []).slice();\n var i = 0;\n var len = evtArr.length;\n\n for (i; i < len; i++) {\n evtArr[i].fn.apply(evtArr[i].ctx, data);\n }\n\n return this;\n },\n\n off: function (name, callback) {\n var e = this.e || (this.e = {});\n var evts = e[name];\n var liveEvents = [];\n\n if (evts && callback) {\n for (var i = 0, len = evts.length; i < len; i++) {\n if (evts[i].fn !== callback && evts[i].fn._ !== callback)\n liveEvents.push(evts[i]);\n }\n }\n\n // Remove event from queue to prevent memory leak\n // Suggested by https://github.com/lazd\n // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n (liveEvents.length)\n ? e[name] = liveEvents\n : delete e[name];\n\n return this;\n }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*\n * Copyright (c) 2016-2024 Martin Donath \n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"focus-visible\"\n\nimport {\n EMPTY,\n NEVER,\n Observable,\n Subject,\n defer,\n delay,\n filter,\n map,\n merge,\n mergeWith,\n shareReplay,\n switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n at,\n getActiveElement,\n getOptionalElement,\n requestJSON,\n setLocation,\n setToggle,\n watchDocument,\n watchKeyboard,\n watchLocation,\n watchLocationTarget,\n watchMedia,\n watchPrint,\n watchScript,\n watchViewport\n} from \"./browser\"\nimport {\n getComponentElement,\n getComponentElements,\n mountAnnounce,\n mountBackToTop,\n mountConsent,\n mountContent,\n mountDialog,\n mountHeader,\n mountHeaderTitle,\n mountPalette,\n mountProgress,\n mountSearch,\n mountSearchHiglight,\n mountSidebar,\n mountSource,\n mountTableOfContents,\n mountTabs,\n watchHeader,\n watchMain\n} from \"./components\"\nimport {\n SearchIndex,\n setupClipboardJS,\n setupInstantNavigation,\n setupVersionSelector\n} from \"./integrations\"\nimport {\n patchEllipsis,\n patchIndeterminate,\n patchScrollfix,\n patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Functions - @todo refactor\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch search index\n *\n * @returns Search index observable\n */\nfunction fetchSearchIndex(): Observable {\n if (location.protocol === \"file:\") {\n return watchScript(\n `${new URL(\"search/search_index.js\", config.base)}`\n )\n .pipe(\n // @ts-ignore - @todo fix typings\n map(() => __index),\n shareReplay(1)\n )\n } else {\n return requestJSON(\n new URL(\"search/search_index.json\", config.base)\n )\n }\n}\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$ = watchLocationTarget(location$)\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$ = watchMedia(\"(min-width: 960px)\")\nconst screen$ = watchMedia(\"(min-width: 1220px)\")\nconst print$ = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n ? fetchSearchIndex()\n : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject()\nsetupClipboardJS({ alert$ })\n\n/* Set up progress indicator */\nconst progress$ = new Subject()\n\n/* Set up instant navigation, if enabled */\nif (feature(\"navigation.instant\"))\n setupInstantNavigation({ location$, viewport$, progress$ })\n .subscribe(document$)\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n .pipe(\n delay(125)\n )\n .subscribe(() => {\n setToggle(\"drawer\", false)\n setToggle(\"search\", false)\n })\n\n/* Set up global keyboard handlers */\nkeyboard$\n .pipe(\n filter(({ mode }) => mode === \"global\")\n )\n .subscribe(key => {\n switch (key.type) {\n\n /* Go to previous page */\n case \"p\":\n case \",\":\n const prev = getOptionalElement(\"link[rel=prev]\")\n if (typeof prev !== \"undefined\")\n setLocation(prev)\n break\n\n /* Go to next page */\n case \"n\":\n case \".\":\n const next = getOptionalElement(\"link[rel=next]\")\n if (typeof next !== \"undefined\")\n setLocation(next)\n break\n\n /* Expand navigation, see https://bit.ly/3ZjG5io */\n case \"Enter\":\n const active = getActiveElement()\n if (active instanceof HTMLLabelElement)\n active.click()\n }\n })\n\n/* Set up patches */\npatchEllipsis({ viewport$, document$ })\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n .pipe(\n map(() => getComponentElement(\"main\")),\n switchMap(el => watchMain(el, { viewport$, header$ })),\n shareReplay(1)\n )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n /* Consent */\n ...getComponentElements(\"consent\")\n .map(el => mountConsent(el, { target$ })),\n\n /* Dialog */\n ...getComponentElements(\"dialog\")\n .map(el => mountDialog(el, { alert$ })),\n\n /* Header */\n ...getComponentElements(\"header\")\n .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n /* Color palette */\n ...getComponentElements(\"palette\")\n .map(el => mountPalette(el)),\n\n /* Progress bar */\n ...getComponentElements(\"progress\")\n .map(el => mountProgress(el, { progress$ })),\n\n /* Search */\n ...getComponentElements(\"search\")\n .map(el => mountSearch(el, { index$, keyboard$ })),\n\n /* Repository information */\n ...getComponentElements(\"source\")\n .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n /* Announcement bar */\n ...getComponentElements(\"announce\")\n .map(el => mountAnnounce(el)),\n\n /* Content */\n ...getComponentElements(\"content\")\n .map(el => mountContent(el, { viewport$, target$, print$ })),\n\n /* Search highlighting */\n ...getComponentElements(\"content\")\n .map(el => feature(\"search.highlight\")\n ? mountSearchHiglight(el, { index$, location$ })\n : EMPTY\n ),\n\n /* Header title */\n ...getComponentElements(\"header-title\")\n .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n /* Sidebar */\n ...getComponentElements(\"sidebar\")\n .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n ),\n\n /* Navigation tabs */\n ...getComponentElements(\"tabs\")\n .map(el => mountTabs(el, { viewport$, header$ })),\n\n /* Table of contents */\n ...getComponentElements(\"toc\")\n .map(el => mountTableOfContents(el, {\n viewport$, header$, main$, target$\n })),\n\n /* Back-to-top button */\n ...getComponentElements(\"top\")\n .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n .pipe(\n switchMap(() => content$),\n mergeWith(control$),\n shareReplay(1)\n )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$ = document$ /* Document observable */\nwindow.location$ = location$ /* Location subject */\nwindow.target$ = target$ /* Location target observable */\nwindow.keyboard$ = keyboard$ /* Keyboard observable */\nwindow.viewport$ = viewport$ /* Viewport observable */\nwindow.tablet$ = tablet$ /* Media tablet observable */\nwindow.screen$ = screen$ /* Media screen observable */\nwindow.print$ = print$ /* Media print observable */\nwindow.alert$ = alert$ /* Alert subject */\nwindow.progress$ = progress$ /* Progress indicator subject */\nwindow.component$ = component$ /* Component observable */\n", "/******************************************************************************\nCopyright (c) Microsoft Corporation.\n\nPermission to use, copy, modify, and/or distribute this software for any\npurpose with or without fee is hereby granted.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\nPERFORMANCE OF THIS SOFTWARE.\n***************************************************************************** */\n/* global Reflect, Promise, SuppressedError, Symbol, Iterator */\n\nvar extendStatics = function(d, b) {\n extendStatics = Object.setPrototypeOf ||\n ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\n function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\n return extendStatics(d, b);\n};\n\nexport function __extends(d, b) {\n if (typeof b !== \"function\" && b !== null)\n throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\n extendStatics(d, b);\n function __() { this.constructor = d; }\n d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\n}\n\nexport var __assign = function() {\n __assign = Object.assign || function __assign(t) {\n for (var s, i = 1, n = arguments.length; i < n; i++) {\n s = arguments[i];\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\n }\n return t;\n }\n return __assign.apply(this, arguments);\n}\n\nexport function __rest(s, e) {\n var t = {};\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\n t[p] = s[p];\n if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\n for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\n if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\n t[p[i]] = s[p[i]];\n }\n return t;\n}\n\nexport function __decorate(decorators, target, key, desc) {\n var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\n if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\n else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\n return c > 3 && r && Object.defineProperty(target, key, r), r;\n}\n\nexport function __param(paramIndex, decorator) {\n return function (target, key) { decorator(target, key, paramIndex); }\n}\n\nexport function __esDecorate(ctor, descriptorIn, decorators, contextIn, initializers, extraInitializers) {\n function accept(f) { if (f !== void 0 && typeof f !== \"function\") throw new TypeError(\"Function expected\"); return f; }\n var kind = contextIn.kind, key = kind === \"getter\" ? \"get\" : kind === \"setter\" ? \"set\" : \"value\";\n var target = !descriptorIn && ctor ? contextIn[\"static\"] ? ctor : ctor.prototype : null;\n var descriptor = descriptorIn || (target ? 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(function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n var desc = Object.getOwnPropertyDescriptor(m, k);\n if (!desc || (\"get\" in desc ? !m.__esModule : desc.writable || desc.configurable)) {\n desc = { enumerable: true, get: function() { return m[k]; } };\n }\n Object.defineProperty(o, k2, desc);\n}) : (function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n o[k2] = m[k];\n});\n\nexport function __exportStar(m, o) {\n for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\n}\n\nexport function __values(o) {\n var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\n if (m) return m.call(o);\n if (o && typeof o.length === \"number\") return {\n next: function () {\n if (o && i >= o.length) o = void 0;\n return { value: o && o[i++], done: !o };\n }\n };\n throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\n}\n\nexport function __read(o, n) {\n var m = typeof Symbol === \"function\" && o[Symbol.iterator];\n if (!m) return o;\n var i = m.call(o), r, ar = [], e;\n try {\n while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\n }\n catch (error) { e = { error: error }; }\n finally {\n try {\n if (r && !r.done && (m = i[\"return\"])) m.call(i);\n }\n finally { if (e) throw e.error; }\n }\n return ar;\n}\n\n/** @deprecated */\nexport function __spread() {\n for (var ar = [], i = 0; i < arguments.length; i++)\n ar = ar.concat(__read(arguments[i]));\n return ar;\n}\n\n/** @deprecated */\nexport function __spreadArrays() {\n for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\n for (var r = Array(s), k = 0, i = 0; i < il; i++)\n for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\n r[k] = a[j];\n return r;\n}\n\nexport function __spreadArray(to, from, pack) {\n if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\n if (ar || !(i in from)) {\n if (!ar) ar = Array.prototype.slice.call(from, 0, i);\n ar[i] = from[i];\n }\n }\n return to.concat(ar || Array.prototype.slice.call(from));\n}\n\nexport function __await(v) {\n return this instanceof __await ? (this.v = v, this) : new __await(v);\n}\n\nexport function __asyncGenerator(thisArg, _arguments, generator) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var g = generator.apply(thisArg, _arguments || []), i, q = [];\n return i = Object.create((typeof AsyncIterator === \"function\" ? AsyncIterator : Object).prototype), verb(\"next\"), verb(\"throw\"), verb(\"return\", awaitReturn), i[Symbol.asyncIterator] = function () { return this; }, i;\n function awaitReturn(f) { return function (v) { return Promise.resolve(v).then(f, reject); }; }\n function verb(n, f) { if (g[n]) { i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; if (f) i[n] = f(i[n]); } }\n function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\n function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r); }\n function fulfill(value) { resume(\"next\", value); }\n function reject(value) { resume(\"throw\", value); }\n function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\n}\n\nexport function __asyncDelegator(o) {\n var i, p;\n return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\n function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: false } : f ? f(v) : v; } : f; }\n}\n\nexport function __asyncValues(o) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var m = o[Symbol.asyncIterator], i;\n return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\n function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\n function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\n}\n\nexport function __makeTemplateObject(cooked, raw) {\n if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\n return cooked;\n};\n\nvar __setModuleDefault = Object.create ? (function(o, v) {\n Object.defineProperty(o, \"default\", { enumerable: true, value: v });\n}) : function(o, v) {\n o[\"default\"] = v;\n};\n\nexport function __importStar(mod) {\n if (mod && mod.__esModule) return mod;\n var result = {};\n if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\n __setModuleDefault(result, mod);\n return result;\n}\n\nexport function __importDefault(mod) {\n return (mod && mod.__esModule) ? mod : { default: mod };\n}\n\nexport function __classPrivateFieldGet(receiver, state, kind, f) {\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\n return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\n}\n\nexport function __classPrivateFieldSet(receiver, state, value, kind, f) {\n if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\n return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\n}\n\nexport function __classPrivateFieldIn(state, receiver) {\n if (receiver === null || (typeof receiver !== \"object\" && typeof receiver !== \"function\")) throw new TypeError(\"Cannot use 'in' operator on non-object\");\n return typeof state === \"function\" ? receiver === state : state.has(receiver);\n}\n\nexport function __addDisposableResource(env, value, async) {\n if (value !== null && value !== void 0) {\n if (typeof value !== \"object\" && typeof value !== \"function\") throw new TypeError(\"Object expected.\");\n var dispose, inner;\n if (async) {\n if (!Symbol.asyncDispose) throw new TypeError(\"Symbol.asyncDispose is not defined.\");\n dispose = value[Symbol.asyncDispose];\n }\n if (dispose === void 0) {\n if (!Symbol.dispose) throw new TypeError(\"Symbol.dispose is not defined.\");\n dispose = value[Symbol.dispose];\n if (async) inner = dispose;\n }\n if (typeof dispose !== \"function\") throw new TypeError(\"Object not disposable.\");\n if (inner) dispose = function() { try { inner.call(this); } catch (e) { return Promise.reject(e); } };\n env.stack.push({ value: value, dispose: dispose, async: async });\n }\n else if (async) {\n env.stack.push({ async: true });\n }\n return value;\n}\n\nvar _SuppressedError = typeof SuppressedError === \"function\" ? SuppressedError : function (error, suppressed, message) {\n var e = new Error(message);\n return e.name = \"SuppressedError\", e.error = error, e.suppressed = suppressed, e;\n};\n\nexport function __disposeResources(env) {\n function fail(e) {\n env.error = env.hasError ? new _SuppressedError(e, env.error, \"An error was suppressed during disposal.\") : e;\n env.hasError = true;\n }\n var r, s = 0;\n function next() {\n while (r = env.stack.pop()) {\n try {\n if (!r.async && s === 1) return s = 0, env.stack.push(r), Promise.resolve().then(next);\n if (r.dispose) {\n var result = r.dispose.call(r.value);\n if (r.async) return s |= 2, Promise.resolve(result).then(next, function(e) { fail(e); return next(); });\n }\n else s |= 1;\n }\n catch (e) {\n fail(e);\n }\n }\n if (s === 1) return env.hasError ? Promise.reject(env.error) : Promise.resolve();\n if (env.hasError) throw env.error;\n }\n return next();\n}\n\nexport default {\n __extends,\n __assign,\n __rest,\n __decorate,\n __param,\n __metadata,\n __awaiter,\n __generator,\n __createBinding,\n __exportStar,\n __values,\n __read,\n __spread,\n __spreadArrays,\n __spreadArray,\n __await,\n __asyncGenerator,\n __asyncDelegator,\n __asyncValues,\n __makeTemplateObject,\n __importStar,\n __importDefault,\n __classPrivateFieldGet,\n __classPrivateFieldSet,\n __classPrivateFieldIn,\n __addDisposableResource,\n __disposeResources,\n};\n", "/**\n * Returns true if the object is a function.\n * @param value The value to check\n */\nexport function isFunction(value: any): value is (...args: any[]) => any {\n return typeof value === 'function';\n}\n", "/**\n * Used to create Error subclasses until the community moves away from ES5.\n *\n * This is because compiling from TypeScript down to ES5 has issues with subclassing Errors\n * as well as other built-in types: https://github.com/Microsoft/TypeScript/issues/12123\n *\n * @param createImpl A factory function to create the actual constructor implementation. The returned\n * function should be a named function that calls `_super` internally.\n */\nexport function createErrorClass(createImpl: (_super: any) => any): T {\n const _super = (instance: any) => {\n Error.call(instance);\n instance.stack = new Error().stack;\n };\n\n const ctorFunc = createImpl(_super);\n ctorFunc.prototype = Object.create(Error.prototype);\n ctorFunc.prototype.constructor = ctorFunc;\n return ctorFunc;\n}\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface UnsubscriptionError extends Error {\n readonly errors: any[];\n}\n\nexport interface UnsubscriptionErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (errors: any[]): UnsubscriptionError;\n}\n\n/**\n * An error thrown when one or more errors have occurred during the\n * `unsubscribe` of a {@link Subscription}.\n */\nexport const UnsubscriptionError: UnsubscriptionErrorCtor = createErrorClass(\n (_super) =>\n function UnsubscriptionErrorImpl(this: any, errors: (Error | string)[]) {\n _super(this);\n this.message = errors\n ? `${errors.length} errors occurred during unsubscription:\n${errors.map((err, i) => `${i + 1}) ${err.toString()}`).join('\\n ')}`\n : '';\n this.name = 'UnsubscriptionError';\n this.errors = errors;\n }\n);\n", "/**\n * Removes an item from an array, mutating it.\n * @param arr The array to remove the item from\n * @param item The item to remove\n */\nexport function arrRemove(arr: T[] | undefined | null, item: T) {\n if (arr) {\n const index = arr.indexOf(item);\n 0 <= index && arr.splice(index, 1);\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { UnsubscriptionError } from './util/UnsubscriptionError';\nimport { SubscriptionLike, TeardownLogic, Unsubscribable } from './types';\nimport { arrRemove } from './util/arrRemove';\n\n/**\n * Represents a disposable resource, such as the execution of an Observable. A\n * Subscription has one important method, `unsubscribe`, that takes no argument\n * and just disposes the resource held by the subscription.\n *\n * Additionally, subscriptions may be grouped together through the `add()`\n * method, which will attach a child Subscription to the current Subscription.\n * When a Subscription is unsubscribed, all its children (and its grandchildren)\n * will be unsubscribed as well.\n *\n * @class Subscription\n */\nexport class Subscription implements SubscriptionLike {\n /** @nocollapse */\n public static EMPTY = (() => {\n const empty = new Subscription();\n empty.closed = true;\n return empty;\n })();\n\n /**\n * A flag to indicate whether this Subscription has already been unsubscribed.\n */\n public closed = false;\n\n private _parentage: Subscription[] | Subscription | null = null;\n\n /**\n * The list of registered finalizers to execute upon unsubscription. Adding and removing from this\n * list occurs in the {@link #add} and {@link #remove} methods.\n */\n private _finalizers: Exclude[] | null = null;\n\n /**\n * @param initialTeardown A function executed first as part of the finalization\n * process that is kicked off when {@link #unsubscribe} is called.\n */\n constructor(private initialTeardown?: () => void) {}\n\n /**\n * Disposes the resources held by the subscription. May, for instance, cancel\n * an ongoing Observable execution or cancel any other type of work that\n * started when the Subscription was created.\n * @return {void}\n */\n unsubscribe(): void {\n let errors: any[] | undefined;\n\n if (!this.closed) {\n this.closed = true;\n\n // Remove this from it's parents.\n const { _parentage } = this;\n if (_parentage) {\n this._parentage = null;\n if (Array.isArray(_parentage)) {\n for (const parent of _parentage) {\n parent.remove(this);\n }\n } else {\n _parentage.remove(this);\n }\n }\n\n const { initialTeardown: initialFinalizer } = this;\n if (isFunction(initialFinalizer)) {\n try {\n initialFinalizer();\n } catch (e) {\n errors = e instanceof UnsubscriptionError ? e.errors : [e];\n }\n }\n\n const { _finalizers } = this;\n if (_finalizers) {\n this._finalizers = null;\n for (const finalizer of _finalizers) {\n try {\n execFinalizer(finalizer);\n } catch (err) {\n errors = errors ?? [];\n if (err instanceof UnsubscriptionError) {\n errors = [...errors, ...err.errors];\n } else {\n errors.push(err);\n }\n }\n }\n }\n\n if (errors) {\n throw new UnsubscriptionError(errors);\n }\n }\n }\n\n /**\n * Adds a finalizer to this subscription, so that finalization will be unsubscribed/called\n * when this subscription is unsubscribed. If this subscription is already {@link #closed},\n * because it has already been unsubscribed, then whatever finalizer is passed to it\n * will automatically be executed (unless the finalizer itself is also a closed subscription).\n *\n * Closed Subscriptions cannot be added as finalizers to any subscription. Adding a closed\n * subscription to a any subscription will result in no operation. (A noop).\n *\n * Adding a subscription to itself, or adding `null` or `undefined` will not perform any\n * operation at all. (A noop).\n *\n * `Subscription` instances that are added to this instance will automatically remove themselves\n * if they are unsubscribed. Functions and {@link Unsubscribable} objects that you wish to remove\n * will need to be removed manually with {@link #remove}\n *\n * @param teardown The finalization logic to add to this subscription.\n */\n add(teardown: TeardownLogic): void {\n // Only add the finalizer if it's not undefined\n // and don't add a subscription to itself.\n if (teardown && teardown !== this) {\n if (this.closed) {\n // If this subscription is already closed,\n // execute whatever finalizer is handed to it automatically.\n execFinalizer(teardown);\n } else {\n if (teardown instanceof Subscription) {\n // We don't add closed subscriptions, and we don't add the same subscription\n // twice. Subscription unsubscribe is idempotent.\n if (teardown.closed || teardown._hasParent(this)) {\n return;\n }\n teardown._addParent(this);\n }\n (this._finalizers = this._finalizers ?? []).push(teardown);\n }\n }\n }\n\n /**\n * Checks to see if a this subscription already has a particular parent.\n * This will signal that this subscription has already been added to the parent in question.\n * @param parent the parent to check for\n */\n private _hasParent(parent: Subscription) {\n const { _parentage } = this;\n return _parentage === parent || (Array.isArray(_parentage) && _parentage.includes(parent));\n }\n\n /**\n * Adds a parent to this subscription so it can be removed from the parent if it\n * unsubscribes on it's own.\n *\n * NOTE: THIS ASSUMES THAT {@link _hasParent} HAS ALREADY BEEN CHECKED.\n * @param parent The parent subscription to add\n */\n private _addParent(parent: Subscription) {\n const { _parentage } = this;\n this._parentage = Array.isArray(_parentage) ? (_parentage.push(parent), _parentage) : _parentage ? [_parentage, parent] : parent;\n }\n\n /**\n * Called on a child when it is removed via {@link #remove}.\n * @param parent The parent to remove\n */\n private _removeParent(parent: Subscription) {\n const { _parentage } = this;\n if (_parentage === parent) {\n this._parentage = null;\n } else if (Array.isArray(_parentage)) {\n arrRemove(_parentage, parent);\n }\n }\n\n /**\n * Removes a finalizer from this subscription that was previously added with the {@link #add} method.\n *\n * Note that `Subscription` instances, when unsubscribed, will automatically remove themselves\n * from every other `Subscription` they have been added to. This means that using the `remove` method\n * is not a common thing and should be used thoughtfully.\n *\n * If you add the same finalizer instance of a function or an unsubscribable object to a `Subscription` instance\n * more than once, you will need to call `remove` the same number of times to remove all instances.\n *\n * All finalizer instances are removed to free up memory upon unsubscription.\n *\n * @param teardown The finalizer to remove from this subscription\n */\n remove(teardown: Exclude): void {\n const { _finalizers } = this;\n _finalizers && arrRemove(_finalizers, teardown);\n\n if (teardown instanceof Subscription) {\n teardown._removeParent(this);\n }\n }\n}\n\nexport const EMPTY_SUBSCRIPTION = Subscription.EMPTY;\n\nexport function isSubscription(value: any): value is Subscription {\n return (\n value instanceof Subscription ||\n (value && 'closed' in value && isFunction(value.remove) && isFunction(value.add) && isFunction(value.unsubscribe))\n );\n}\n\nfunction execFinalizer(finalizer: Unsubscribable | (() => void)) {\n if (isFunction(finalizer)) {\n finalizer();\n } else {\n finalizer.unsubscribe();\n }\n}\n", "import { Subscriber } from './Subscriber';\nimport { ObservableNotification } from './types';\n\n/**\n * The {@link GlobalConfig} object for RxJS. It is used to configure things\n * like how to react on unhandled errors.\n */\nexport const config: GlobalConfig = {\n onUnhandledError: null,\n onStoppedNotification: null,\n Promise: undefined,\n useDeprecatedSynchronousErrorHandling: false,\n useDeprecatedNextContext: false,\n};\n\n/**\n * The global configuration object for RxJS, used to configure things\n * like how to react on unhandled errors. Accessible via {@link config}\n * object.\n */\nexport interface GlobalConfig {\n /**\n * A registration point for unhandled errors from RxJS. These are errors that\n * cannot were not handled by consuming code in the usual subscription path. For\n * example, if you have this configured, and you subscribe to an observable without\n * providing an error handler, errors from that subscription will end up here. This\n * will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onUnhandledError: ((err: any) => void) | null;\n\n /**\n * A registration point for notifications that cannot be sent to subscribers because they\n * have completed, errored or have been explicitly unsubscribed. By default, next, complete\n * and error notifications sent to stopped subscribers are noops. However, sometimes callers\n * might want a different behavior. For example, with sources that attempt to report errors\n * to stopped subscribers, a caller can configure RxJS to throw an unhandled error instead.\n * This will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onStoppedNotification: ((notification: ObservableNotification, subscriber: Subscriber) => void) | null;\n\n /**\n * The promise constructor used by default for {@link Observable#toPromise toPromise} and {@link Observable#forEach forEach}\n * methods.\n *\n * @deprecated As of version 8, RxJS will no longer support this sort of injection of a\n * Promise constructor. If you need a Promise implementation other than native promises,\n * please polyfill/patch Promise as you see appropriate. Will be removed in v8.\n */\n Promise?: PromiseConstructorLike;\n\n /**\n * If true, turns on synchronous error rethrowing, which is a deprecated behavior\n * in v6 and higher. This behavior enables bad patterns like wrapping a subscribe\n * call in a try/catch block. It also enables producer interference, a nasty bug\n * where a multicast can be broken for all observers by a downstream consumer with\n * an unhandled error. DO NOT USE THIS FLAG UNLESS IT'S NEEDED TO BUY TIME\n * FOR MIGRATION REASONS.\n *\n * @deprecated As of version 8, RxJS will no longer support synchronous throwing\n * of unhandled errors. All errors will be thrown on a separate call stack to prevent bad\n * behaviors described above. Will be removed in v8.\n */\n useDeprecatedSynchronousErrorHandling: boolean;\n\n /**\n * If true, enables an as-of-yet undocumented feature from v5: The ability to access\n * `unsubscribe()` via `this` context in `next` functions created in observers passed\n * to `subscribe`.\n *\n * This is being removed because the performance was severely problematic, and it could also cause\n * issues when types other than POJOs are passed to subscribe as subscribers, as they will likely have\n * their `this` context overwritten.\n *\n * @deprecated As of version 8, RxJS will no longer support altering the\n * context of next functions provided as part of an observer to Subscribe. Instead,\n * you will have access to a subscription or a signal or token that will allow you to do things like\n * unsubscribe and test closed status. Will be removed in v8.\n */\n useDeprecatedNextContext: boolean;\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetTimeoutFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearTimeoutFunction = (handle: TimerHandle) => void;\n\ninterface TimeoutProvider {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n delegate:\n | {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n }\n | undefined;\n}\n\nexport const timeoutProvider: TimeoutProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setTimeout(handler: () => void, timeout?: number, ...args) {\n const { delegate } = timeoutProvider;\n if (delegate?.setTimeout) {\n return delegate.setTimeout(handler, timeout, ...args);\n }\n return setTimeout(handler, timeout, ...args);\n },\n clearTimeout(handle) {\n const { delegate } = timeoutProvider;\n return (delegate?.clearTimeout || clearTimeout)(handle as any);\n },\n delegate: undefined,\n};\n", "import { config } from '../config';\nimport { timeoutProvider } from '../scheduler/timeoutProvider';\n\n/**\n * Handles an error on another job either with the user-configured {@link onUnhandledError},\n * or by throwing it on that new job so it can be picked up by `window.onerror`, `process.on('error')`, etc.\n *\n * This should be called whenever there is an error that is out-of-band with the subscription\n * or when an error hits a terminal boundary of the subscription and no error handler was provided.\n *\n * @param err the error to report\n */\nexport function reportUnhandledError(err: any) {\n timeoutProvider.setTimeout(() => {\n const { onUnhandledError } = config;\n if (onUnhandledError) {\n // Execute the user-configured error handler.\n onUnhandledError(err);\n } else {\n // Throw so it is picked up by the runtime's uncaught error mechanism.\n throw err;\n }\n });\n}\n", "/* tslint:disable:no-empty */\nexport function noop() { }\n", "import { CompleteNotification, NextNotification, ErrorNotification } from './types';\n\n/**\n * A completion object optimized for memory use and created to be the\n * same \"shape\" as other notifications in v8.\n * @internal\n */\nexport const COMPLETE_NOTIFICATION = (() => createNotification('C', undefined, undefined) as CompleteNotification)();\n\n/**\n * Internal use only. Creates an optimized error notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function errorNotification(error: any): ErrorNotification {\n return createNotification('E', undefined, error) as any;\n}\n\n/**\n * Internal use only. Creates an optimized next notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function nextNotification(value: T) {\n return createNotification('N', value, undefined) as NextNotification;\n}\n\n/**\n * Ensures that all notifications created internally have the same \"shape\" in v8.\n *\n * TODO: This is only exported to support a crazy legacy test in `groupBy`.\n * @internal\n */\nexport function createNotification(kind: 'N' | 'E' | 'C', value: any, error: any) {\n return {\n kind,\n value,\n error,\n };\n}\n", "import { config } from '../config';\n\nlet context: { errorThrown: boolean; error: any } | null = null;\n\n/**\n * Handles dealing with errors for super-gross mode. Creates a context, in which\n * any synchronously thrown errors will be passed to {@link captureError}. Which\n * will record the error such that it will be rethrown after the call back is complete.\n * TODO: Remove in v8\n * @param cb An immediately executed function.\n */\nexport function errorContext(cb: () => void) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n const isRoot = !context;\n if (isRoot) {\n context = { errorThrown: false, error: null };\n }\n cb();\n if (isRoot) {\n const { errorThrown, error } = context!;\n context = null;\n if (errorThrown) {\n throw error;\n }\n }\n } else {\n // This is the general non-deprecated path for everyone that\n // isn't crazy enough to use super-gross mode (useDeprecatedSynchronousErrorHandling)\n cb();\n }\n}\n\n/**\n * Captures errors only in super-gross mode.\n * @param err the error to capture\n */\nexport function captureError(err: any) {\n if (config.useDeprecatedSynchronousErrorHandling && context) {\n context.errorThrown = true;\n context.error = err;\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { Observer, ObservableNotification } from './types';\nimport { isSubscription, Subscription } from './Subscription';\nimport { config } from './config';\nimport { reportUnhandledError } from './util/reportUnhandledError';\nimport { noop } from './util/noop';\nimport { nextNotification, errorNotification, COMPLETE_NOTIFICATION } from './NotificationFactories';\nimport { timeoutProvider } from './scheduler/timeoutProvider';\nimport { captureError } from './util/errorContext';\n\n/**\n * Implements the {@link Observer} interface and extends the\n * {@link Subscription} class. While the {@link Observer} is the public API for\n * consuming the values of an {@link Observable}, all Observers get converted to\n * a Subscriber, in order to provide Subscription-like capabilities such as\n * `unsubscribe`. Subscriber is a common type in RxJS, and crucial for\n * implementing operators, but it is rarely used as a public API.\n *\n * @class Subscriber\n */\nexport class Subscriber extends Subscription implements Observer {\n /**\n * A static factory for a Subscriber, given a (potentially partial) definition\n * of an Observer.\n * @param next The `next` callback of an Observer.\n * @param error The `error` callback of an\n * Observer.\n * @param complete The `complete` callback of an\n * Observer.\n * @return A Subscriber wrapping the (partially defined)\n * Observer represented by the given arguments.\n * @nocollapse\n * @deprecated Do not use. Will be removed in v8. There is no replacement for this\n * method, and there is no reason to be creating instances of `Subscriber` directly.\n * If you have a specific use case, please file an issue.\n */\n static create(next?: (x?: T) => void, error?: (e?: any) => void, complete?: () => void): Subscriber {\n return new SafeSubscriber(next, error, complete);\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected isStopped: boolean = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected destination: Subscriber | Observer; // this `any` is the escape hatch to erase extra type param (e.g. R)\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * There is no reason to directly create an instance of Subscriber. This type is exported for typings reasons.\n */\n constructor(destination?: Subscriber | Observer) {\n super();\n if (destination) {\n this.destination = destination;\n // Automatically chain subscriptions together here.\n // if destination is a Subscription, then it is a Subscriber.\n if (isSubscription(destination)) {\n destination.add(this);\n }\n } else {\n this.destination = EMPTY_OBSERVER;\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `next` from\n * the Observable, with a value. The Observable may call this method 0 or more\n * times.\n * @param {T} [value] The `next` value.\n * @return {void}\n */\n next(value?: T): void {\n if (this.isStopped) {\n handleStoppedNotification(nextNotification(value), this);\n } else {\n this._next(value!);\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `error` from\n * the Observable, with an attached `Error`. Notifies the Observer that\n * the Observable has experienced an error condition.\n * @param {any} [err] The `error` exception.\n * @return {void}\n */\n error(err?: any): void {\n if (this.isStopped) {\n handleStoppedNotification(errorNotification(err), this);\n } else {\n this.isStopped = true;\n this._error(err);\n }\n }\n\n /**\n * The {@link Observer} callback to receive a valueless notification of type\n * `complete` from the Observable. Notifies the Observer that the Observable\n * has finished sending push-based notifications.\n * @return {void}\n */\n complete(): void {\n if (this.isStopped) {\n handleStoppedNotification(COMPLETE_NOTIFICATION, this);\n } else {\n this.isStopped = true;\n this._complete();\n }\n }\n\n unsubscribe(): void {\n if (!this.closed) {\n this.isStopped = true;\n super.unsubscribe();\n this.destination = null!;\n }\n }\n\n protected _next(value: T): void {\n this.destination.next(value);\n }\n\n protected _error(err: any): void {\n try {\n this.destination.error(err);\n } finally {\n this.unsubscribe();\n }\n }\n\n protected _complete(): void {\n try {\n this.destination.complete();\n } finally {\n this.unsubscribe();\n }\n }\n}\n\n/**\n * This bind is captured here because we want to be able to have\n * compatibility with monoid libraries that tend to use a method named\n * `bind`. In particular, a library called Monio requires this.\n */\nconst _bind = Function.prototype.bind;\n\nfunction bind any>(fn: Fn, thisArg: any): Fn {\n return _bind.call(fn, thisArg);\n}\n\n/**\n * Internal optimization only, DO NOT EXPOSE.\n * @internal\n */\nclass ConsumerObserver implements Observer {\n constructor(private partialObserver: Partial>) {}\n\n next(value: T): void {\n const { partialObserver } = this;\n if (partialObserver.next) {\n try {\n partialObserver.next(value);\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n\n error(err: any): void {\n const { partialObserver } = this;\n if (partialObserver.error) {\n try {\n partialObserver.error(err);\n } catch (error) {\n handleUnhandledError(error);\n }\n } else {\n handleUnhandledError(err);\n }\n }\n\n complete(): void {\n const { partialObserver } = this;\n if (partialObserver.complete) {\n try {\n partialObserver.complete();\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n}\n\nexport class SafeSubscriber extends Subscriber {\n constructor(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((e?: any) => void) | null,\n complete?: (() => void) | null\n ) {\n super();\n\n let partialObserver: Partial>;\n if (isFunction(observerOrNext) || !observerOrNext) {\n // The first argument is a function, not an observer. The next\n // two arguments *could* be observers, or they could be empty.\n partialObserver = {\n next: (observerOrNext ?? undefined) as (((value: T) => void) | undefined),\n error: error ?? undefined,\n complete: complete ?? undefined,\n };\n } else {\n // The first argument is a partial observer.\n let context: any;\n if (this && config.useDeprecatedNextContext) {\n // This is a deprecated path that made `this.unsubscribe()` available in\n // next handler functions passed to subscribe. This only exists behind a flag\n // now, as it is *very* slow.\n context = Object.create(observerOrNext);\n context.unsubscribe = () => this.unsubscribe();\n partialObserver = {\n next: observerOrNext.next && bind(observerOrNext.next, context),\n error: observerOrNext.error && bind(observerOrNext.error, context),\n complete: observerOrNext.complete && bind(observerOrNext.complete, context),\n };\n } else {\n // The \"normal\" path. Just use the partial observer directly.\n partialObserver = observerOrNext;\n }\n }\n\n // Wrap the partial observer to ensure it's a full observer, and\n // make sure proper error handling is accounted for.\n this.destination = new ConsumerObserver(partialObserver);\n }\n}\n\nfunction handleUnhandledError(error: any) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n captureError(error);\n } else {\n // Ideal path, we report this as an unhandled error,\n // which is thrown on a new call stack.\n reportUnhandledError(error);\n }\n}\n\n/**\n * An error handler used when no error handler was supplied\n * to the SafeSubscriber -- meaning no error handler was supplied\n * do the `subscribe` call on our observable.\n * @param err The error to handle\n */\nfunction defaultErrorHandler(err: any) {\n throw err;\n}\n\n/**\n * A handler for notifications that cannot be sent to a stopped subscriber.\n * @param notification The notification being sent\n * @param subscriber The stopped subscriber\n */\nfunction handleStoppedNotification(notification: ObservableNotification, subscriber: Subscriber) {\n const { onStoppedNotification } = config;\n onStoppedNotification && timeoutProvider.setTimeout(() => onStoppedNotification(notification, subscriber));\n}\n\n/**\n * The observer used as a stub for subscriptions where the user did not\n * pass any arguments to `subscribe`. Comes with the default error handling\n * behavior.\n */\nexport const EMPTY_OBSERVER: Readonly> & { closed: true } = {\n closed: true,\n next: noop,\n error: defaultErrorHandler,\n complete: noop,\n};\n", "/**\n * Symbol.observable or a string \"@@observable\". Used for interop\n *\n * @deprecated We will no longer be exporting this symbol in upcoming versions of RxJS.\n * Instead polyfill and use Symbol.observable directly *or* use https://www.npmjs.com/package/symbol-observable\n */\nexport const observable: string | symbol = (() => (typeof Symbol === 'function' && Symbol.observable) || '@@observable')();\n", "/**\n * This function takes one parameter and just returns it. Simply put,\n * this is like `(x: T): T => x`.\n *\n * ## Examples\n *\n * This is useful in some cases when using things like `mergeMap`\n *\n * ```ts\n * import { interval, take, map, range, mergeMap, identity } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(5));\n *\n * const result$ = source$.pipe(\n * map(i => range(i)),\n * mergeMap(identity) // same as mergeMap(x => x)\n * );\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * Or when you want to selectively apply an operator\n *\n * ```ts\n * import { interval, take, identity } from 'rxjs';\n *\n * const shouldLimit = () => Math.random() < 0.5;\n *\n * const source$ = interval(1000);\n *\n * const result$ = source$.pipe(shouldLimit() ? take(5) : identity);\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * @param x Any value that is returned by this function\n * @returns The value passed as the first parameter to this function\n */\nexport function identity(x: T): T {\n return x;\n}\n", "import { identity } from './identity';\nimport { UnaryFunction } from '../types';\n\nexport function pipe(): typeof identity;\nexport function pipe(fn1: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction, fn3: UnaryFunction): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction,\n ...fns: UnaryFunction[]\n): UnaryFunction;\n\n/**\n * pipe() can be called on one or more functions, each of which can take one argument (\"UnaryFunction\")\n * and uses it to return a value.\n * It returns a function that takes one argument, passes it to the first UnaryFunction, and then\n * passes the result to the next one, passes that result to the next one, and so on. \n */\nexport function pipe(...fns: Array>): UnaryFunction {\n return pipeFromArray(fns);\n}\n\n/** @internal */\nexport function pipeFromArray(fns: Array>): UnaryFunction {\n if (fns.length === 0) {\n return identity as UnaryFunction;\n }\n\n if (fns.length === 1) {\n return fns[0];\n }\n\n return function piped(input: T): R {\n return fns.reduce((prev: any, fn: UnaryFunction) => fn(prev), input as any);\n };\n}\n", "import { Operator } from './Operator';\nimport { SafeSubscriber, Subscriber } from './Subscriber';\nimport { isSubscription, Subscription } from './Subscription';\nimport { TeardownLogic, OperatorFunction, Subscribable, Observer } from './types';\nimport { observable as Symbol_observable } from './symbol/observable';\nimport { pipeFromArray } from './util/pipe';\nimport { config } from './config';\nimport { isFunction } from './util/isFunction';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A representation of any set of values over any amount of time. This is the most basic building block\n * of RxJS.\n *\n * @class Observable\n */\nexport class Observable implements Subscribable {\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n source: Observable | undefined;\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n operator: Operator | undefined;\n\n /**\n * @constructor\n * @param {Function} subscribe the function that is called when the Observable is\n * initially subscribed to. This function is given a Subscriber, to which new values\n * can be `next`ed, or an `error` method can be called to raise an error, or\n * `complete` can be called to notify of a successful completion.\n */\n constructor(subscribe?: (this: Observable, subscriber: Subscriber) => TeardownLogic) {\n if (subscribe) {\n this._subscribe = subscribe;\n }\n }\n\n // HACK: Since TypeScript inherits static properties too, we have to\n // fight against TypeScript here so Subject can have a different static create signature\n /**\n * Creates a new Observable by calling the Observable constructor\n * @owner Observable\n * @method create\n * @param {Function} subscribe? the subscriber function to be passed to the Observable constructor\n * @return {Observable} a new observable\n * @nocollapse\n * @deprecated Use `new Observable()` instead. Will be removed in v8.\n */\n static create: (...args: any[]) => any = (subscribe?: (subscriber: Subscriber) => TeardownLogic) => {\n return new Observable(subscribe);\n };\n\n /**\n * Creates a new Observable, with this Observable instance as the source, and the passed\n * operator defined as the new observable's operator.\n * @method lift\n * @param operator the operator defining the operation to take on the observable\n * @return a new observable with the Operator applied\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * If you have implemented an operator using `lift`, it is recommended that you create an\n * operator by simply returning `new Observable()` directly. See \"Creating new operators from\n * scratch\" section here: https://rxjs.dev/guide/operators\n */\n lift(operator?: Operator): Observable {\n const observable = new Observable();\n observable.source = this;\n observable.operator = operator;\n return observable;\n }\n\n subscribe(observerOrNext?: Partial> | ((value: T) => void)): Subscription;\n /** @deprecated Instead of passing separate callback arguments, use an observer argument. Signatures taking separate callback arguments will be removed in v8. Details: https://rxjs.dev/deprecations/subscribe-arguments */\n subscribe(next?: ((value: T) => void) | null, error?: ((error: any) => void) | null, complete?: (() => void) | null): Subscription;\n /**\n * Invokes an execution of an Observable and registers Observer handlers for notifications it will emit.\n *\n * Use it when you have all these Observables, but still nothing is happening.\n *\n * `subscribe` is not a regular operator, but a method that calls Observable's internal `subscribe` function. It\n * might be for example a function that you passed to Observable's constructor, but most of the time it is\n * a library implementation, which defines what will be emitted by an Observable, and when it be will emitted. This means\n * that calling `subscribe` is actually the moment when Observable starts its work, not when it is created, as it is often\n * the thought.\n *\n * Apart from starting the execution of an Observable, this method allows you to listen for values\n * that an Observable emits, as well as for when it completes or errors. You can achieve this in two\n * of the following ways.\n *\n * The first way is creating an object that implements {@link Observer} interface. It should have methods\n * defined by that interface, but note that it should be just a regular JavaScript object, which you can create\n * yourself in any way you want (ES6 class, classic function constructor, object literal etc.). In particular, do\n * not attempt to use any RxJS implementation details to create Observers - you don't need them. Remember also\n * that your object does not have to implement all methods. If you find yourself creating a method that doesn't\n * do anything, you can simply omit it. Note however, if the `error` method is not provided and an error happens,\n * it will be thrown asynchronously. Errors thrown asynchronously cannot be caught using `try`/`catch`. Instead,\n * use the {@link onUnhandledError} configuration option or use a runtime handler (like `window.onerror` or\n * `process.on('error)`) to be notified of unhandled errors. Because of this, it's recommended that you provide\n * an `error` method to avoid missing thrown errors.\n *\n * The second way is to give up on Observer object altogether and simply provide callback functions in place of its methods.\n * This means you can provide three functions as arguments to `subscribe`, where the first function is equivalent\n * of a `next` method, the second of an `error` method and the third of a `complete` method. Just as in case of an Observer,\n * if you do not need to listen for something, you can omit a function by passing `undefined` or `null`,\n * since `subscribe` recognizes these functions by where they were placed in function call. When it comes\n * to the `error` function, as with an Observer, if not provided, errors emitted by an Observable will be thrown asynchronously.\n *\n * You can, however, subscribe with no parameters at all. This may be the case where you're not interested in terminal events\n * and you also handled emissions internally by using operators (e.g. using `tap`).\n *\n * Whichever style of calling `subscribe` you use, in both cases it returns a Subscription object.\n * This object allows you to call `unsubscribe` on it, which in turn will stop the work that an Observable does and will clean\n * up all resources that an Observable used. Note that cancelling a subscription will not call `complete` callback\n * provided to `subscribe` function, which is reserved for a regular completion signal that comes from an Observable.\n *\n * Remember that callbacks provided to `subscribe` are not guaranteed to be called asynchronously.\n * It is an Observable itself that decides when these functions will be called. For example {@link of}\n * by default emits all its values synchronously. Always check documentation for how given Observable\n * will behave when subscribed and if its default behavior can be modified with a `scheduler`.\n *\n * #### Examples\n *\n * Subscribe with an {@link guide/observer Observer}\n *\n * ```ts\n * import { of } from 'rxjs';\n *\n * const sumObserver = {\n * sum: 0,\n * next(value) {\n * console.log('Adding: ' + value);\n * this.sum = this.sum + value;\n * },\n * error() {\n * // We actually could just remove this method,\n * // since we do not really care about errors right now.\n * },\n * complete() {\n * console.log('Sum equals: ' + this.sum);\n * }\n * };\n *\n * of(1, 2, 3) // Synchronously emits 1, 2, 3 and then completes.\n * .subscribe(sumObserver);\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Subscribe with functions ({@link deprecations/subscribe-arguments deprecated})\n *\n * ```ts\n * import { of } from 'rxjs'\n *\n * let sum = 0;\n *\n * of(1, 2, 3).subscribe(\n * value => {\n * console.log('Adding: ' + value);\n * sum = sum + value;\n * },\n * undefined,\n * () => console.log('Sum equals: ' + sum)\n * );\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Cancel a subscription\n *\n * ```ts\n * import { interval } from 'rxjs';\n *\n * const subscription = interval(1000).subscribe({\n * next(num) {\n * console.log(num)\n * },\n * complete() {\n * // Will not be called, even when cancelling subscription.\n * console.log('completed!');\n * }\n * });\n *\n * setTimeout(() => {\n * subscription.unsubscribe();\n * console.log('unsubscribed!');\n * }, 2500);\n *\n * // Logs:\n * // 0 after 1s\n * // 1 after 2s\n * // 'unsubscribed!' after 2.5s\n * ```\n *\n * @param {Observer|Function} observerOrNext (optional) Either an observer with methods to be called,\n * or the first of three possible handlers, which is the handler for each value emitted from the subscribed\n * Observable.\n * @param {Function} error (optional) A handler for a terminal event resulting from an error. If no error handler is provided,\n * the error will be thrown asynchronously as unhandled.\n * @param {Function} complete (optional) A handler for a terminal event resulting from successful completion.\n * @return {Subscription} a subscription reference to the registered handlers\n * @method subscribe\n */\n subscribe(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((error: any) => void) | null,\n complete?: (() => void) | null\n ): Subscription {\n const subscriber = isSubscriber(observerOrNext) ? observerOrNext : new SafeSubscriber(observerOrNext, error, complete);\n\n errorContext(() => {\n const { operator, source } = this;\n subscriber.add(\n operator\n ? // We're dealing with a subscription in the\n // operator chain to one of our lifted operators.\n operator.call(subscriber, source)\n : source\n ? // If `source` has a value, but `operator` does not, something that\n // had intimate knowledge of our API, like our `Subject`, must have\n // set it. We're going to just call `_subscribe` directly.\n this._subscribe(subscriber)\n : // In all other cases, we're likely wrapping a user-provided initializer\n // function, so we need to catch errors and handle them appropriately.\n this._trySubscribe(subscriber)\n );\n });\n\n return subscriber;\n }\n\n /** @internal */\n protected _trySubscribe(sink: Subscriber): TeardownLogic {\n try {\n return this._subscribe(sink);\n } catch (err) {\n // We don't need to return anything in this case,\n // because it's just going to try to `add()` to a subscription\n // above.\n sink.error(err);\n }\n }\n\n /**\n * Used as a NON-CANCELLABLE means of subscribing to an observable, for use with\n * APIs that expect promises, like `async/await`. You cannot unsubscribe from this.\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * #### Example\n *\n * ```ts\n * import { interval, take } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(4));\n *\n * async function getTotal() {\n * let total = 0;\n *\n * await source$.forEach(value => {\n * total += value;\n * console.log('observable -> ' + value);\n * });\n *\n * return total;\n * }\n *\n * getTotal().then(\n * total => console.log('Total: ' + total)\n * );\n *\n * // Expected:\n * // 'observable -> 0'\n * // 'observable -> 1'\n * // 'observable -> 2'\n * // 'observable -> 3'\n * // 'Total: 6'\n * ```\n *\n * @param next a handler for each value emitted by the observable\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n */\n forEach(next: (value: T) => void): Promise;\n\n /**\n * @param next a handler for each value emitted by the observable\n * @param promiseCtor a constructor function used to instantiate the Promise\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n * @deprecated Passing a Promise constructor will no longer be available\n * in upcoming versions of RxJS. This is because it adds weight to the library, for very\n * little benefit. If you need this functionality, it is recommended that you either\n * polyfill Promise, or you create an adapter to convert the returned native promise\n * to whatever promise implementation you wanted. Will be removed in v8.\n */\n forEach(next: (value: T) => void, promiseCtor: PromiseConstructorLike): Promise;\n\n forEach(next: (value: T) => void, promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n const subscriber = new SafeSubscriber({\n next: (value) => {\n try {\n next(value);\n } catch (err) {\n reject(err);\n subscriber.unsubscribe();\n }\n },\n error: reject,\n complete: resolve,\n });\n this.subscribe(subscriber);\n }) as Promise;\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): TeardownLogic {\n return this.source?.subscribe(subscriber);\n }\n\n /**\n * An interop point defined by the es7-observable spec https://github.com/zenparsing/es-observable\n * @method Symbol.observable\n * @return {Observable} this instance of the observable\n */\n [Symbol_observable]() {\n return this;\n }\n\n /* tslint:disable:max-line-length */\n pipe(): Observable;\n pipe(op1: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction, op3: OperatorFunction): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction,\n ...operations: OperatorFunction[]\n ): Observable;\n /* tslint:enable:max-line-length */\n\n /**\n * Used to stitch together functional operators into a chain.\n * @method pipe\n * @return {Observable} the Observable result of all of the operators having\n * been called in the order they were passed in.\n *\n * ## Example\n *\n * ```ts\n * import { interval, filter, map, scan } from 'rxjs';\n *\n * interval(1000)\n * .pipe(\n * filter(x => x % 2 === 0),\n * map(x => x + x),\n * scan((acc, x) => acc + x)\n * )\n * .subscribe(x => console.log(x));\n * ```\n */\n pipe(...operations: OperatorFunction[]): Observable {\n return pipeFromArray(operations)(this);\n }\n\n /* tslint:disable:max-line-length */\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: typeof Promise): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: PromiseConstructorLike): Promise;\n /* tslint:enable:max-line-length */\n\n /**\n * Subscribe to this Observable and get a Promise resolving on\n * `complete` with the last emission (if any).\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * @method toPromise\n * @param [promiseCtor] a constructor function used to instantiate\n * the Promise\n * @return A Promise that resolves with the last value emit, or\n * rejects on an error. If there were no emissions, Promise\n * resolves with undefined.\n * @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise\n */\n toPromise(promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n let value: T | undefined;\n this.subscribe(\n (x: T) => (value = x),\n (err: any) => reject(err),\n () => resolve(value)\n );\n }) as Promise;\n }\n}\n\n/**\n * Decides between a passed promise constructor from consuming code,\n * A default configured promise constructor, and the native promise\n * constructor and returns it. If nothing can be found, it will throw\n * an error.\n * @param promiseCtor The optional promise constructor to passed by consuming code\n */\nfunction getPromiseCtor(promiseCtor: PromiseConstructorLike | undefined) {\n return promiseCtor ?? config.Promise ?? Promise;\n}\n\nfunction isObserver(value: any): value is Observer {\n return value && isFunction(value.next) && isFunction(value.error) && isFunction(value.complete);\n}\n\nfunction isSubscriber(value: any): value is Subscriber {\n return (value && value instanceof Subscriber) || (isObserver(value) && isSubscription(value));\n}\n", "import { Observable } from '../Observable';\nimport { Subscriber } from '../Subscriber';\nimport { OperatorFunction } from '../types';\nimport { isFunction } from './isFunction';\n\n/**\n * Used to determine if an object is an Observable with a lift function.\n */\nexport function hasLift(source: any): source is { lift: InstanceType['lift'] } {\n return isFunction(source?.lift);\n}\n\n/**\n * Creates an `OperatorFunction`. Used to define operators throughout the library in a concise way.\n * @param init The logic to connect the liftedSource to the subscriber at the moment of subscription.\n */\nexport function operate(\n init: (liftedSource: Observable, subscriber: Subscriber) => (() => void) | void\n): OperatorFunction {\n return (source: Observable) => {\n if (hasLift(source)) {\n return source.lift(function (this: Subscriber, liftedSource: Observable) {\n try {\n return init(liftedSource, this);\n } catch (err) {\n this.error(err);\n }\n });\n }\n throw new TypeError('Unable to lift unknown Observable type');\n };\n}\n", "import { Subscriber } from '../Subscriber';\n\n/**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional teardown logic here. This will only be called on teardown if the\n * subscriber itself is not already closed. This is called after all other teardown logic is executed.\n */\nexport function createOperatorSubscriber(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n onFinalize?: () => void\n): Subscriber {\n return new OperatorSubscriber(destination, onNext, onComplete, onError, onFinalize);\n}\n\n/**\n * A generic helper for allowing operators to be created with a Subscriber and\n * use closures to capture necessary state from the operator function itself.\n */\nexport class OperatorSubscriber extends Subscriber {\n /**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional finalization logic here. This will only be called on finalization if the\n * subscriber itself is not already closed. This is called after all other finalization logic is executed.\n * @param shouldUnsubscribe An optional check to see if an unsubscribe call should truly unsubscribe.\n * NOTE: This currently **ONLY** exists to support the strange behavior of {@link groupBy}, where unsubscription\n * to the resulting observable does not actually disconnect from the source if there are active subscriptions\n * to any grouped observable. (DO NOT EXPOSE OR USE EXTERNALLY!!!)\n */\n constructor(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n private onFinalize?: () => void,\n private shouldUnsubscribe?: () => boolean\n ) {\n // It's important - for performance reasons - that all of this class's\n // members are initialized and that they are always initialized in the same\n // order. This will ensure that all OperatorSubscriber instances have the\n // same hidden class in V8. This, in turn, will help keep the number of\n // hidden classes involved in property accesses within the base class as\n // low as possible. If the number of hidden classes involved exceeds four,\n // the property accesses will become megamorphic and performance penalties\n // will be incurred - i.e. inline caches won't be used.\n //\n // The reasons for ensuring all instances have the same hidden class are\n // further discussed in this blog post from Benedikt Meurer:\n // https://benediktmeurer.de/2018/03/23/impact-of-polymorphism-on-component-based-frameworks-like-react/\n super(destination);\n this._next = onNext\n ? function (this: OperatorSubscriber, value: T) {\n try {\n onNext(value);\n } catch (err) {\n destination.error(err);\n }\n }\n : super._next;\n this._error = onError\n ? function (this: OperatorSubscriber, err: any) {\n try {\n onError(err);\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._error;\n this._complete = onComplete\n ? function (this: OperatorSubscriber) {\n try {\n onComplete();\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._complete;\n }\n\n unsubscribe() {\n if (!this.shouldUnsubscribe || this.shouldUnsubscribe()) {\n const { closed } = this;\n super.unsubscribe();\n // Execute additional teardown if we have any and we didn't already do so.\n !closed && this.onFinalize?.();\n }\n }\n}\n", "import { Subscription } from '../Subscription';\n\ninterface AnimationFrameProvider {\n schedule(callback: FrameRequestCallback): Subscription;\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n delegate:\n | {\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n }\n | undefined;\n}\n\nexport const animationFrameProvider: AnimationFrameProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n schedule(callback) {\n let request = requestAnimationFrame;\n let cancel: typeof cancelAnimationFrame | undefined = cancelAnimationFrame;\n const { delegate } = animationFrameProvider;\n if (delegate) {\n request = delegate.requestAnimationFrame;\n cancel = delegate.cancelAnimationFrame;\n }\n const handle = request((timestamp) => {\n // Clear the cancel function. The request has been fulfilled, so\n // attempting to cancel the request upon unsubscription would be\n // pointless.\n cancel = undefined;\n callback(timestamp);\n });\n return new Subscription(() => cancel?.(handle));\n },\n requestAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.requestAnimationFrame || requestAnimationFrame)(...args);\n },\n cancelAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.cancelAnimationFrame || cancelAnimationFrame)(...args);\n },\n delegate: undefined,\n};\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface ObjectUnsubscribedError extends Error {}\n\nexport interface ObjectUnsubscribedErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (): ObjectUnsubscribedError;\n}\n\n/**\n * An error thrown when an action is invalid because the object has been\n * unsubscribed.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n *\n * @class ObjectUnsubscribedError\n */\nexport const ObjectUnsubscribedError: ObjectUnsubscribedErrorCtor = createErrorClass(\n (_super) =>\n function ObjectUnsubscribedErrorImpl(this: any) {\n _super(this);\n this.name = 'ObjectUnsubscribedError';\n this.message = 'object unsubscribed';\n }\n);\n", "import { Operator } from './Operator';\nimport { Observable } from './Observable';\nimport { Subscriber } from './Subscriber';\nimport { Subscription, EMPTY_SUBSCRIPTION } from './Subscription';\nimport { Observer, SubscriptionLike, TeardownLogic } from './types';\nimport { ObjectUnsubscribedError } from './util/ObjectUnsubscribedError';\nimport { arrRemove } from './util/arrRemove';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A Subject is a special type of Observable that allows values to be\n * multicasted to many Observers. Subjects are like EventEmitters.\n *\n * Every Subject is an Observable and an Observer. You can subscribe to a\n * Subject, and you can call next to feed values as well as error and complete.\n */\nexport class Subject extends Observable implements SubscriptionLike {\n closed = false;\n\n private currentObservers: Observer[] | null = null;\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n observers: Observer[] = [];\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n isStopped = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n hasError = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n thrownError: any = null;\n\n /**\n * Creates a \"subject\" by basically gluing an observer to an observable.\n *\n * @nocollapse\n * @deprecated Recommended you do not use. Will be removed at some point in the future. Plans for replacement still under discussion.\n */\n static create: (...args: any[]) => any = (destination: Observer, source: Observable): AnonymousSubject => {\n return new AnonymousSubject(destination, source);\n };\n\n constructor() {\n // NOTE: This must be here to obscure Observable's constructor.\n super();\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n lift(operator: Operator): Observable {\n const subject = new AnonymousSubject(this, this);\n subject.operator = operator as any;\n return subject as any;\n }\n\n /** @internal */\n protected _throwIfClosed() {\n if (this.closed) {\n throw new ObjectUnsubscribedError();\n }\n }\n\n next(value: T) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n if (!this.currentObservers) {\n this.currentObservers = Array.from(this.observers);\n }\n for (const observer of this.currentObservers) {\n observer.next(value);\n }\n }\n });\n }\n\n error(err: any) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.hasError = this.isStopped = true;\n this.thrownError = err;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.error(err);\n }\n }\n });\n }\n\n complete() {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.isStopped = true;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.complete();\n }\n }\n });\n }\n\n unsubscribe() {\n this.isStopped = this.closed = true;\n this.observers = this.currentObservers = null!;\n }\n\n get observed() {\n return this.observers?.length > 0;\n }\n\n /** @internal */\n protected _trySubscribe(subscriber: Subscriber): TeardownLogic {\n this._throwIfClosed();\n return super._trySubscribe(subscriber);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._checkFinalizedStatuses(subscriber);\n return this._innerSubscribe(subscriber);\n }\n\n /** @internal */\n protected _innerSubscribe(subscriber: Subscriber) {\n const { hasError, isStopped, observers } = this;\n if (hasError || isStopped) {\n return EMPTY_SUBSCRIPTION;\n }\n this.currentObservers = null;\n observers.push(subscriber);\n return new Subscription(() => {\n this.currentObservers = null;\n arrRemove(observers, subscriber);\n });\n }\n\n /** @internal */\n protected _checkFinalizedStatuses(subscriber: Subscriber) {\n const { hasError, thrownError, isStopped } = this;\n if (hasError) {\n subscriber.error(thrownError);\n } else if (isStopped) {\n subscriber.complete();\n }\n }\n\n /**\n * Creates a new Observable with this Subject as the source. You can do this\n * to create custom Observer-side logic of the Subject and conceal it from\n * code that uses the Observable.\n * @return {Observable} Observable that the Subject casts to\n */\n asObservable(): Observable {\n const observable: any = new Observable();\n observable.source = this;\n return observable;\n }\n}\n\n/**\n * @class AnonymousSubject\n */\nexport class AnonymousSubject extends Subject {\n constructor(\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n public destination?: Observer,\n source?: Observable\n ) {\n super();\n this.source = source;\n }\n\n next(value: T) {\n this.destination?.next?.(value);\n }\n\n error(err: any) {\n this.destination?.error?.(err);\n }\n\n complete() {\n this.destination?.complete?.();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n return this.source?.subscribe(subscriber) ?? EMPTY_SUBSCRIPTION;\n }\n}\n", "import { Subject } from './Subject';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\n\n/**\n * A variant of Subject that requires an initial value and emits its current\n * value whenever it is subscribed to.\n *\n * @class BehaviorSubject\n */\nexport class BehaviorSubject extends Subject {\n constructor(private _value: T) {\n super();\n }\n\n get value(): T {\n return this.getValue();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n const subscription = super._subscribe(subscriber);\n !subscription.closed && subscriber.next(this._value);\n return subscription;\n }\n\n getValue(): T {\n const { hasError, thrownError, _value } = this;\n if (hasError) {\n throw thrownError;\n }\n this._throwIfClosed();\n return _value;\n }\n\n next(value: T): void {\n super.next((this._value = value));\n }\n}\n", "import { TimestampProvider } from '../types';\n\ninterface DateTimestampProvider extends TimestampProvider {\n delegate: TimestampProvider | undefined;\n}\n\nexport const dateTimestampProvider: DateTimestampProvider = {\n now() {\n // Use the variable rather than `this` so that the function can be called\n // without being bound to the provider.\n return (dateTimestampProvider.delegate || Date).now();\n },\n delegate: undefined,\n};\n", "import { Subject } from './Subject';\nimport { TimestampProvider } from './types';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * A variant of {@link Subject} that \"replays\" old values to new subscribers by emitting them when they first subscribe.\n *\n * `ReplaySubject` has an internal buffer that will store a specified number of values that it has observed. Like `Subject`,\n * `ReplaySubject` \"observes\" values by having them passed to its `next` method. When it observes a value, it will store that\n * value for a time determined by the configuration of the `ReplaySubject`, as passed to its constructor.\n *\n * When a new subscriber subscribes to the `ReplaySubject` instance, it will synchronously emit all values in its buffer in\n * a First-In-First-Out (FIFO) manner. The `ReplaySubject` will also complete, if it has observed completion; and it will\n * error if it has observed an error.\n *\n * There are two main configuration items to be concerned with:\n *\n * 1. `bufferSize` - This will determine how many items are stored in the buffer, defaults to infinite.\n * 2. `windowTime` - The amount of time to hold a value in the buffer before removing it from the buffer.\n *\n * Both configurations may exist simultaneously. So if you would like to buffer a maximum of 3 values, as long as the values\n * are less than 2 seconds old, you could do so with a `new ReplaySubject(3, 2000)`.\n *\n * ### Differences with BehaviorSubject\n *\n * `BehaviorSubject` is similar to `new ReplaySubject(1)`, with a couple of exceptions:\n *\n * 1. `BehaviorSubject` comes \"primed\" with a single value upon construction.\n * 2. `ReplaySubject` will replay values, even after observing an error, where `BehaviorSubject` will not.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n * @see {@link shareReplay}\n */\nexport class ReplaySubject extends Subject {\n private _buffer: (T | number)[] = [];\n private _infiniteTimeWindow = true;\n\n /**\n * @param bufferSize The size of the buffer to replay on subscription\n * @param windowTime The amount of time the buffered items will stay buffered\n * @param timestampProvider An object with a `now()` method that provides the current timestamp. This is used to\n * calculate the amount of time something has been buffered.\n */\n constructor(\n private _bufferSize = Infinity,\n private _windowTime = Infinity,\n private _timestampProvider: TimestampProvider = dateTimestampProvider\n ) {\n super();\n this._infiniteTimeWindow = _windowTime === Infinity;\n this._bufferSize = Math.max(1, _bufferSize);\n this._windowTime = Math.max(1, _windowTime);\n }\n\n next(value: T): void {\n const { isStopped, _buffer, _infiniteTimeWindow, _timestampProvider, _windowTime } = this;\n if (!isStopped) {\n _buffer.push(value);\n !_infiniteTimeWindow && _buffer.push(_timestampProvider.now() + _windowTime);\n }\n this._trimBuffer();\n super.next(value);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._trimBuffer();\n\n const subscription = this._innerSubscribe(subscriber);\n\n const { _infiniteTimeWindow, _buffer } = this;\n // We use a copy here, so reentrant code does not mutate our array while we're\n // emitting it to a new subscriber.\n const copy = _buffer.slice();\n for (let i = 0; i < copy.length && !subscriber.closed; i += _infiniteTimeWindow ? 1 : 2) {\n subscriber.next(copy[i] as T);\n }\n\n this._checkFinalizedStatuses(subscriber);\n\n return subscription;\n }\n\n private _trimBuffer() {\n const { _bufferSize, _timestampProvider, _buffer, _infiniteTimeWindow } = this;\n // If we don't have an infinite buffer size, and we're over the length,\n // use splice to truncate the old buffer values off. Note that we have to\n // double the size for instances where we're not using an infinite time window\n // because we're storing the values and the timestamps in the same array.\n const adjustedBufferSize = (_infiniteTimeWindow ? 1 : 2) * _bufferSize;\n _bufferSize < Infinity && adjustedBufferSize < _buffer.length && _buffer.splice(0, _buffer.length - adjustedBufferSize);\n\n // Now, if we're not in an infinite time window, remove all values where the time is\n // older than what is allowed.\n if (!_infiniteTimeWindow) {\n const now = _timestampProvider.now();\n let last = 0;\n // Search the array for the first timestamp that isn't expired and\n // truncate the buffer up to that point.\n for (let i = 1; i < _buffer.length && (_buffer[i] as number) <= now; i += 2) {\n last = i;\n }\n last && _buffer.splice(0, last + 1);\n }\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Subscription } from '../Subscription';\nimport { SchedulerAction } from '../types';\n\n/**\n * A unit of work to be executed in a `scheduler`. An action is typically\n * created from within a {@link SchedulerLike} and an RxJS user does not need to concern\n * themselves about creating and manipulating an Action.\n *\n * ```ts\n * class Action extends Subscription {\n * new (scheduler: Scheduler, work: (state?: T) => void);\n * schedule(state?: T, delay: number = 0): Subscription;\n * }\n * ```\n *\n * @class Action\n */\nexport class Action extends Subscription {\n constructor(scheduler: Scheduler, work: (this: SchedulerAction, state?: T) => void) {\n super();\n }\n /**\n * Schedules this action on its parent {@link SchedulerLike} for execution. May be passed\n * some context object, `state`. May happen at some point in the future,\n * according to the `delay` parameter, if specified.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler.\n * @return {void}\n */\n public schedule(state?: T, delay: number = 0): Subscription {\n return this;\n }\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetIntervalFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearIntervalFunction = (handle: TimerHandle) => void;\n\ninterface IntervalProvider {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n delegate:\n | {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n }\n | undefined;\n}\n\nexport const intervalProvider: IntervalProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setInterval(handler: () => void, timeout?: number, ...args) {\n const { delegate } = intervalProvider;\n if (delegate?.setInterval) {\n return delegate.setInterval(handler, timeout, ...args);\n }\n return setInterval(handler, timeout, ...args);\n },\n clearInterval(handle) {\n const { delegate } = intervalProvider;\n return (delegate?.clearInterval || clearInterval)(handle as any);\n },\n delegate: undefined,\n};\n", "import { Action } from './Action';\nimport { SchedulerAction } from '../types';\nimport { Subscription } from '../Subscription';\nimport { AsyncScheduler } from './AsyncScheduler';\nimport { intervalProvider } from './intervalProvider';\nimport { arrRemove } from '../util/arrRemove';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncAction extends Action {\n public id: TimerHandle | undefined;\n public state?: T;\n // @ts-ignore: Property has no initializer and is not definitely assigned\n public delay: number;\n protected pending: boolean = false;\n\n constructor(protected scheduler: AsyncScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (this.closed) {\n return this;\n }\n\n // Always replace the current state with the new state.\n this.state = state;\n\n const id = this.id;\n const scheduler = this.scheduler;\n\n //\n // Important implementation note:\n //\n // Actions only execute once by default, unless rescheduled from within the\n // scheduled callback. This allows us to implement single and repeat\n // actions via the same code path, without adding API surface area, as well\n // as mimic traditional recursion but across asynchronous boundaries.\n //\n // However, JS runtimes and timers distinguish between intervals achieved by\n // serial `setTimeout` calls vs. a single `setInterval` call. An interval of\n // serial `setTimeout` calls can be individually delayed, which delays\n // scheduling the next `setTimeout`, and so on. `setInterval` attempts to\n // guarantee the interval callback will be invoked more precisely to the\n // interval period, regardless of load.\n //\n // Therefore, we use `setInterval` to schedule single and repeat actions.\n // If the action reschedules itself with the same delay, the interval is not\n // canceled. If the action doesn't reschedule, or reschedules with a\n // different delay, the interval will be canceled after scheduled callback\n // execution.\n //\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, delay);\n }\n\n // Set the pending flag indicating that this action has been scheduled, or\n // has recursively rescheduled itself.\n this.pending = true;\n\n this.delay = delay;\n // If this action has already an async Id, don't request a new one.\n this.id = this.id ?? this.requestAsyncId(scheduler, this.id, delay);\n\n return this;\n }\n\n protected requestAsyncId(scheduler: AsyncScheduler, _id?: TimerHandle, delay: number = 0): TimerHandle {\n return intervalProvider.setInterval(scheduler.flush.bind(scheduler, this), delay);\n }\n\n protected recycleAsyncId(_scheduler: AsyncScheduler, id?: TimerHandle, delay: number | null = 0): TimerHandle | undefined {\n // If this action is rescheduled with the same delay time, don't clear the interval id.\n if (delay != null && this.delay === delay && this.pending === false) {\n return id;\n }\n // Otherwise, if the action's delay time is different from the current delay,\n // or the action has been rescheduled before it's executed, clear the interval id\n if (id != null) {\n intervalProvider.clearInterval(id);\n }\n\n return undefined;\n }\n\n /**\n * Immediately executes this action and the `work` it contains.\n * @return {any}\n */\n public execute(state: T, delay: number): any {\n if (this.closed) {\n return new Error('executing a cancelled action');\n }\n\n this.pending = false;\n const error = this._execute(state, delay);\n if (error) {\n return error;\n } else if (this.pending === false && this.id != null) {\n // Dequeue if the action didn't reschedule itself. Don't call\n // unsubscribe(), because the action could reschedule later.\n // For example:\n // ```\n // scheduler.schedule(function doWork(counter) {\n // /* ... I'm a busy worker bee ... */\n // var originalAction = this;\n // /* wait 100ms before rescheduling the action */\n // setTimeout(function () {\n // originalAction.schedule(counter + 1);\n // }, 100);\n // }, 1000);\n // ```\n this.id = this.recycleAsyncId(this.scheduler, this.id, null);\n }\n }\n\n protected _execute(state: T, _delay: number): any {\n let errored: boolean = false;\n let errorValue: any;\n try {\n this.work(state);\n } catch (e) {\n errored = true;\n // HACK: Since code elsewhere is relying on the \"truthiness\" of the\n // return here, we can't have it return \"\" or 0 or false.\n // TODO: Clean this up when we refactor schedulers mid-version-8 or so.\n errorValue = e ? e : new Error('Scheduled action threw falsy error');\n }\n if (errored) {\n this.unsubscribe();\n return errorValue;\n }\n }\n\n unsubscribe() {\n if (!this.closed) {\n const { id, scheduler } = this;\n const { actions } = scheduler;\n\n this.work = this.state = this.scheduler = null!;\n this.pending = false;\n\n arrRemove(actions, this);\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, null);\n }\n\n this.delay = null!;\n super.unsubscribe();\n }\n }\n}\n", "import { Action } from './scheduler/Action';\nimport { Subscription } from './Subscription';\nimport { SchedulerLike, SchedulerAction } from './types';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * An execution context and a data structure to order tasks and schedule their\n * execution. Provides a notion of (potentially virtual) time, through the\n * `now()` getter method.\n *\n * Each unit of work in a Scheduler is called an `Action`.\n *\n * ```ts\n * class Scheduler {\n * now(): number;\n * schedule(work, delay?, state?): Subscription;\n * }\n * ```\n *\n * @class Scheduler\n * @deprecated Scheduler is an internal implementation detail of RxJS, and\n * should not be used directly. Rather, create your own class and implement\n * {@link SchedulerLike}. Will be made internal in v8.\n */\nexport class Scheduler implements SchedulerLike {\n public static now: () => number = dateTimestampProvider.now;\n\n constructor(private schedulerActionCtor: typeof Action, now: () => number = Scheduler.now) {\n this.now = now;\n }\n\n /**\n * A getter method that returns a number representing the current time\n * (at the time this function was called) according to the scheduler's own\n * internal clock.\n * @return {number} A number that represents the current time. May or may not\n * have a relation to wall-clock time. May or may not refer to a time unit\n * (e.g. milliseconds).\n */\n public now: () => number;\n\n /**\n * Schedules a function, `work`, for execution. May happen at some point in\n * the future, according to the `delay` parameter, if specified. May be passed\n * some context object, `state`, which will be passed to the `work` function.\n *\n * The given arguments will be processed an stored as an Action object in a\n * queue of actions.\n *\n * @param {function(state: ?T): ?Subscription} work A function representing a\n * task, or some unit of work to be executed by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler itself.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @return {Subscription} A subscription in order to be able to unsubscribe\n * the scheduled work.\n */\n public schedule(work: (this: SchedulerAction, state?: T) => void, delay: number = 0, state?: T): Subscription {\n return new this.schedulerActionCtor(this, work).schedule(state, delay);\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Action } from './Action';\nimport { AsyncAction } from './AsyncAction';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncScheduler extends Scheduler {\n public actions: Array> = [];\n /**\n * A flag to indicate whether the Scheduler is currently executing a batch of\n * queued actions.\n * @type {boolean}\n * @internal\n */\n public _active: boolean = false;\n /**\n * An internal ID used to track the latest asynchronous task such as those\n * coming from `setTimeout`, `setInterval`, `requestAnimationFrame`, and\n * others.\n * @type {any}\n * @internal\n */\n public _scheduled: TimerHandle | undefined;\n\n constructor(SchedulerAction: typeof Action, now: () => number = Scheduler.now) {\n super(SchedulerAction, now);\n }\n\n public flush(action: AsyncAction): void {\n const { actions } = this;\n\n if (this._active) {\n actions.push(action);\n return;\n }\n\n let error: any;\n this._active = true;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions.shift()!)); // exhaust the scheduler queue\n\n this._active = false;\n\n if (error) {\n while ((action = actions.shift()!)) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\n/**\n *\n * Async Scheduler\n *\n * Schedule task as if you used setTimeout(task, duration)\n *\n * `async` scheduler schedules tasks asynchronously, by putting them on the JavaScript\n * event loop queue. It is best used to delay tasks in time or to schedule tasks repeating\n * in intervals.\n *\n * If you just want to \"defer\" task, that is to perform it right after currently\n * executing synchronous code ends (commonly achieved by `setTimeout(deferredTask, 0)`),\n * better choice will be the {@link asapScheduler} scheduler.\n *\n * ## Examples\n * Use async scheduler to delay task\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * const task = () => console.log('it works!');\n *\n * asyncScheduler.schedule(task, 2000);\n *\n * // After 2 seconds logs:\n * // \"it works!\"\n * ```\n *\n * Use async scheduler to repeat task in intervals\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * function task(state) {\n * console.log(state);\n * this.schedule(state + 1, 1000); // `this` references currently executing Action,\n * // which we reschedule with new state and delay\n * }\n *\n * asyncScheduler.schedule(task, 3000, 0);\n *\n * // Logs:\n * // 0 after 3s\n * // 1 after 4s\n * // 2 after 5s\n * // 3 after 6s\n * ```\n */\n\nexport const asyncScheduler = new AsyncScheduler(AsyncAction);\n\n/**\n * @deprecated Renamed to {@link asyncScheduler}. Will be removed in v8.\n */\nexport const async = asyncScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { Subscription } from '../Subscription';\nimport { QueueScheduler } from './QueueScheduler';\nimport { SchedulerAction } from '../types';\nimport { TimerHandle } from './timerHandle';\n\nexport class QueueAction extends AsyncAction {\n constructor(protected scheduler: QueueScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (delay > 0) {\n return super.schedule(state, delay);\n }\n this.delay = delay;\n this.state = state;\n this.scheduler.flush(this);\n return this;\n }\n\n public execute(state: T, delay: number): any {\n return delay > 0 || this.closed ? super.execute(state, delay) : this._execute(state, delay);\n }\n\n protected requestAsyncId(scheduler: QueueScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n\n if ((delay != null && delay > 0) || (delay == null && this.delay > 0)) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n\n // Otherwise flush the scheduler starting with this action.\n scheduler.flush(this);\n\n // HACK: In the past, this was returning `void`. However, `void` isn't a valid\n // `TimerHandle`, and generally the return value here isn't really used. So the\n // compromise is to return `0` which is both \"falsy\" and a valid `TimerHandle`,\n // as opposed to refactoring every other instanceo of `requestAsyncId`.\n return 0;\n }\n}\n", "import { AsyncScheduler } from './AsyncScheduler';\n\nexport class QueueScheduler extends AsyncScheduler {\n}\n", "import { QueueAction } from './QueueAction';\nimport { QueueScheduler } from './QueueScheduler';\n\n/**\n *\n * Queue Scheduler\n *\n * Put every next task on a queue, instead of executing it immediately\n *\n * `queue` scheduler, when used with delay, behaves the same as {@link asyncScheduler} scheduler.\n *\n * When used without delay, it schedules given task synchronously - executes it right when\n * it is scheduled. However when called recursively, that is when inside the scheduled task,\n * another task is scheduled with queue scheduler, instead of executing immediately as well,\n * that task will be put on a queue and wait for current one to finish.\n *\n * This means that when you execute task with `queue` scheduler, you are sure it will end\n * before any other task scheduled with that scheduler will start.\n *\n * ## Examples\n * Schedule recursively first, then do something\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(() => {\n * queueScheduler.schedule(() => console.log('second')); // will not happen now, but will be put on a queue\n *\n * console.log('first');\n * });\n *\n * // Logs:\n * // \"first\"\n * // \"second\"\n * ```\n *\n * Reschedule itself recursively\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(function(state) {\n * if (state !== 0) {\n * console.log('before', state);\n * this.schedule(state - 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * console.log('after', state);\n * }\n * }, 0, 3);\n *\n * // In scheduler that runs recursively, you would expect:\n * // \"before\", 3\n * // \"before\", 2\n * // \"before\", 1\n * // \"after\", 1\n * // \"after\", 2\n * // \"after\", 3\n *\n * // But with queue it logs:\n * // \"before\", 3\n * // \"after\", 3\n * // \"before\", 2\n * // \"after\", 2\n * // \"before\", 1\n * // \"after\", 1\n * ```\n */\n\nexport const queueScheduler = new QueueScheduler(QueueAction);\n\n/**\n * @deprecated Renamed to {@link queueScheduler}. Will be removed in v8.\n */\nexport const queue = queueScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\nimport { SchedulerAction } from '../types';\nimport { animationFrameProvider } from './animationFrameProvider';\nimport { TimerHandle } from './timerHandle';\n\nexport class AnimationFrameAction extends AsyncAction {\n constructor(protected scheduler: AnimationFrameScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n protected requestAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay is greater than 0, request as an async action.\n if (delay !== null && delay > 0) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n // Push the action to the end of the scheduler queue.\n scheduler.actions.push(this);\n // If an animation frame has already been requested, don't request another\n // one. If an animation frame hasn't been requested yet, request one. Return\n // the current animation frame request id.\n return scheduler._scheduled || (scheduler._scheduled = animationFrameProvider.requestAnimationFrame(() => scheduler.flush(undefined)));\n }\n\n protected recycleAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle | undefined {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n if (delay != null ? delay > 0 : this.delay > 0) {\n return super.recycleAsyncId(scheduler, id, delay);\n }\n // If the scheduler queue has no remaining actions with the same async id,\n // cancel the requested animation frame and set the scheduled flag to\n // undefined so the next AnimationFrameAction will request its own.\n const { actions } = scheduler;\n if (id != null && actions[actions.length - 1]?.id !== id) {\n animationFrameProvider.cancelAnimationFrame(id as number);\n scheduler._scheduled = undefined;\n }\n // Return undefined so the action knows to request a new async id if it's rescheduled.\n return undefined;\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\nexport class AnimationFrameScheduler extends AsyncScheduler {\n public flush(action?: AsyncAction): void {\n this._active = true;\n // The async id that effects a call to flush is stored in _scheduled.\n // Before executing an action, it's necessary to check the action's async\n // id to determine whether it's supposed to be executed in the current\n // flush.\n // Previous implementations of this method used a count to determine this,\n // but that was unsound, as actions that are unsubscribed - i.e. cancelled -\n // are removed from the actions array and that can shift actions that are\n // scheduled to be executed in a subsequent flush into positions at which\n // they are executed within the current flush.\n const flushId = this._scheduled;\n this._scheduled = undefined;\n\n const { actions } = this;\n let error: any;\n action = action || actions.shift()!;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions[0]) && action.id === flushId && actions.shift());\n\n this._active = false;\n\n if (error) {\n while ((action = actions[0]) && action.id === flushId && actions.shift()) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AnimationFrameAction } from './AnimationFrameAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\n\n/**\n *\n * Animation Frame Scheduler\n *\n * Perform task when `window.requestAnimationFrame` would fire\n *\n * When `animationFrame` scheduler is used with delay, it will fall back to {@link asyncScheduler} scheduler\n * behaviour.\n *\n * Without delay, `animationFrame` scheduler can be used to create smooth browser animations.\n * It makes sure scheduled task will happen just before next browser content repaint,\n * thus performing animations as efficiently as possible.\n *\n * ## Example\n * Schedule div height animation\n * ```ts\n * // html: