Skip to content

Latest commit

 

History

History
281 lines (229 loc) · 13.4 KB

installation.md

File metadata and controls

281 lines (229 loc) · 13.4 KB
Raw

Install Soda Core

Soda Core is a Python library and command-line interface (CLI) tool that enables you to scan the data in your data source to surface invalid, missing, or unexpected data.


Compatibility
Requirements
Install on MacOS, Linux
Install on Windows
Install using Docker
Upgrade
Install Soda Core Scientific

Compatibility

Use Soda Core to scan a variety of data sources.

Amazon Athena
Amazon Redshift
Apache Spark DataFrames1
Apache Spark for Databricks SQL
Azure Synapse
ClickHouse
Dask and Pandas1
Denodo
Dremio
DuckDB
GCP Big Query
IBM DB2		 Local file using Dask1
MotherDuck
MS Fabric
MS SQL Server
MySQL
OracleDB
PostgreSQL
Snowflake
Teradata
Trino
Vertica
1 For use with programmatic Soda scans, only.

Requirements

To use Soda Core, you must have installed the following on your system.

  • Python 3.8 or greater. To check your existing version, use the CLI command: python --version or python3 --version If you have not already installed Python, consider using pyenv to manage multiple versions of Python in your environment.
  • Pip 21.0 or greater. To check your existing version, use the CLI command: pip --version

Install on MacOS, Linux

  1. Best practice dictates that you install the Soda Core CLI using a virtual environment. In your command-line interface tool, create a virtual environment in the .venv directory using the commands below. Depending on your version of Python, you may need to replace python with python3 in the first command. 
    python -m venv .venv
source .venv/bin/activate
  2. Upgrade pip inside your new virtual environment. 
    pip install --upgrade pip
  3. Execute the following command, replacing soda-core-postgres with the install package that matches the type of data source you use to store data. 
    pip install soda-core-postgres
Data source Install package
Amazon Athena soda-core-athena
Amazon Redshift soda-core-redshift
Apache Spark DataFrames
(For use with [programmatic Soda scans]({% link soda-core/programmatic.md %}), only.)		 soda-core-spark-df
Azure Synapse (Experimental) soda-core-sqlserver
ClickHouse (Experimental) soda-core-mysql
Dask and Pandas (Experimental) soda-core-pandas-dask
Databricks soda-core-spark[databricks]
Denodo (Experimental) soda-core-denodo
Dremio soda-core-dremio
DuckDB (Experimental) soda-core-duckdb
GCP Big Query soda-core-bigquery
IBM DB2 soda-core-db2
Local file Use Dask.
MotherDuck soda-core-duckdb
MS Fabric soda-core-fabric
MS SQL Server soda-core-sqlserver
MySQL soda-core-mysql
OracleDB soda-core-oracle
PostgreSQL soda-core-postgres
Snowflake soda-core-snowflake
Teradata soda-core-teradata
Trino soda-core-trino
Vertica (Experimental) soda-core-vertica

To deactivate the virtual environment, use the following command:

deactivate

Install on Windows

  1. Best practice dictates that you install the Soda Core CLI using a virtual environment. In your command-line interface tool, create a virtual environment in the .venv directory using the commands below. Depending on your version of Python, you may need to replace python with python3 in the first command. Reference the virtualenv documentation for activating a Windows script. 
    python -m venv .venv
.venv\Scripts\activate
  2. Upgrade pip inside your new virtual environment. 
    pip install --upgrade pip
  3. Execute the following command, replacing soda-core-postgres with the install package that matches the type of data source you use to store data. 
    pip install soda-core-postgres
Data source Install package
Amazon Athena soda-core-athena
Amazon Redshift soda-core-redshift
Apache Spark DataFrames
(For use with [programmatic Soda scans]({% link soda-core/programmatic.md %}), only.)		 soda-core-spark-df
Azure Synapse (Experimental) soda-core-sqlserver
ClickHouse (Experimental) soda-core-mysql
Dask and Pandas (Experimental) soda-core-pandas-dask
Databricks soda-core-spark[databricks]
Denodo (Experimental) soda-core-denodo
Dremio soda-core-dremio
DuckDB (Experimental) soda-core-duckdb
GCP Big Query soda-core-bigquery
IBM DB2 soda-core-db2
Local file Use Dask.
MotherDuck soda-core-duckdb
MS Fabric soda-core-fabric
MS SQL Server soda-core-sqlserver
MySQL soda-core-mysql
OracleDB soda-core-oracle
PostgreSQL soda-core-postgres
Snowflake soda-core-snowflake
Teradata soda-core-teradata
Trino soda-core-trino
Vertica (Experimental) soda-core-vertica

To deactivate the virtual environment, use the following command:

deactivate

Reference the virtualenv documentation for activating a Windows script.

Install using Docker

Use Soda's Docker image in which Soda Core Scientific is pre-installed.

  1. If you have not already done so, install Docker in your local environment.
  2. From Terminal, run the following command to pull the latest Soda Core's official Docker image. 
    docker pull sodadata/soda-core
  3. Verify the pull by running the following command. 
    docker run sodadata/soda-core --help
    Output: 
        Usage: soda [OPTIONS] COMMAND [ARGS]...

    Soda Core CLI version 3.0.xxx

    Options:
    --help  Show this message and exit.

    Commands:
    scan    runs a scan
    update-dro  updates a distribution reference file
    ```

When you run the Docker image on a non-Linux/amd64 platform, you may see the following warning from Docker, which you can ignore.

WARNING: The requested image's platform (linux/amd64) does not match the detected host platform (linux/arm64/v8) and no specific platform was requested

Run a scan with Docker

When you are ready to run a Soda scan, use the following command to run the scan via the docker image. Replace the placeholder values with your own file paths and names.

docker run -v /path/to/your_soda_directory:/sodacl sodadata/soda-core scan -d your_data_source -c /sodacl/your_configuration.yml /sodacl/your_checks.yml

Optionally, you can specify the version of Soda Core to use to execute the scan. This may be useful when you do not wish to use the latest released version of Soda Core to run your scans. The example scan command below specifies Soda Core version 3.0.0.

docker run -v /path/to/your_soda_directory:/sodacl sodadata/soda-core:v3.0.0 scan -d your_data_source -c /sodacl/your_configuration.yml /sodacl/your_checks.yml
What does the scan command do?
  • docker run ensures that the docker engine runs a specific image.
  • -v mounts your SodaCL files into the container. In other words, it makes the configuration.yml and checks.yml files in your local environment available to the docker container. The command example maps your local directory to /sodacl inside of the docker container.
  • sodadata/soda-core refers to the image that docker run must use.
  • scan instructs Soda Core to execute a scan of your data.
  • -d indicates the name of the data source to scan.
  • -c specifies the filepath and name of the configuration YAML file.

Error: Mounts denied

If you encounter the following error, follow the procedure below.

docker: Error response from daemon: Mounts denied: 
The path /soda-core-test/files is not shared from the host and is not known to Docker.
You can configure shared paths from Docker -> Preferences... -> Resources -> File Sharing.
See https://docs.docker.com/desktop/mac for more info.

You need to give Docker permission to acccess your configuration.yml and checks.yml files in your environment. To do so:

  1. Access your Docker Dashboard, then select Preferences (gear symbol).
  2. Select Resources, then follow the Docker instructions to add your Soda project directory -- the one you use to store your configuration.yml and checks.yml files -- to the list of directories that can be bind-mounted into Docker containers.
  3. Click Apply & Restart, then repeat steps above.

Error: Configuration path does not exist

If you encounter the following error, double check the syntax of the scan command in step 4 above.

  • Be sure to prepend /sodacl/ to both the congifuration.yml filepath and the checks.yml filepath.
  • Be sure to mount your files into the container by including the -v option. For example, -v /Users/MyName/soda_core_project:/sodacl.
Soda Core 3.0.xxx
Configuration path 'configuration.yml' does not exist
Path "checks.yml" does not exist
Scan summary:
No checks found, 0 checks evaluated.
2 errors.
Oops! 2 errors. 0 failures. 0 warnings. 0 pass.
ERRORS:
Configuration path 'configuration.yml' does not exist
Path "checks.yml" does not exist

Upgrade

To upgrade your existing Soda Core tool to the latest version, use the following command, replacing soda-core-redshift with the install package that matches the type of data source you are using.

pip install soda-core-redshift -U

Install Soda Core Scientific

Install Soda Core Scientific to be able to use SodaCL distribution checks or anomaly score checks.

You have two installation options to choose from:

Install Soda Core Scientific in a virtual environment (Recommended)

  1. Set up a virtual environment, as described above.
  2. Install Soda Core in your new virtual environment, as described above.
  3. Use the following command to install Soda Core Scientific. 
    pip install soda-core-scientific

Note that installing the Soda Core Scientific package also installs several scientific dependencies. Reference the soda-core-scientific setup file in the public GitHub repository for details.

Error: Library not loaded

If you have defined an anomaly score check and you use an M1 MacOS machine, you may get a Library not loaded: @rpath/libtbb.dylib error. This is a known issue in the MacOS community and is caused by issues during the installation of the prophet library. There currently are no official workarounds or releases to fix the problem, but the following adjustments may address the issue.

  1. Install soda-core-scientific as per the virtual environment installation instructions and activate the virtual environment.
  2. Use the following command to navigate to the directory in which the stan_model of the prophet package is installed in your virtual environment. 
    cd path_to_your_python_virtual_env/lib/pythonyour_version/site_packages/prophet/stan_model/
    For example, if you have created a python virtual environment in a /venvs directory in your home directory and you use Python 3.9, you would use the following command. 
    cd ~/venvs/soda-core-prophet11/lib/python3.9/site-packages/prophet/stan_model/
  3. Use the ls command to determine the version number of cmndstan that prophet installed. The cmndstan directory name includes the version number. 
    ls
cmdstan-2.26.1		prophet_model.bin
  4. Add the rpath of the tbb library to your prophet installation using the following command. 
    install_name_tool -add_rpath @executable_path/cmdstanyour_cmdstan_version/stan/lib/stan_math/lib/tbb prophet_model.bin
    With cmdstan version 2.26.1, you would use the following command. 
    install_name_tool -add_rpath @executable_path/cmdstan-2.26.1/stan/lib/stan_math/lib/tbb prophet_model.bin