Refactoring/65 rename bucket fs (#67)

* Replaced bucket-fs with BucketFS in docstrings

* Replaced bucket-fs with BucketFS in docstrings

doc/changes/changes_0.2.6.md

@@ -12,3 +12,4 @@ This release adds the extension wrappers and makes full use of the configuration
 * #56: [Transformers extension wrapper](https://github.com/exasol/notebook-connector/pull/56)
 * #47: [Create a Sagemaker Extension wrapper](https://github.com/exasol/notebook-connector/issues/47)
 * #60: [Start using the AILabConfig internally](https://github.com/exasol/notebook-connector/issues/60)
+* #65: [Renamed "bucket-fs" to "BucketFS" in docstrings](https://github.com/exasol/notebook-connector/issues/65)

exasol/extension_wrapper_common.py

@@ -27,11 +27,11 @@ def encapsulate_bucketfs_credentials(
 ) -> None:
     """
     Creates a connection object in the database encapsulating
-    a location in the bucket-fs and bucket-fs access credentials.
+    a location in the BucketFS and BucketFS access credentials.
 
     Parameters:
         conf:
-            The secret store. The store must hold the bucket-fs service
+            The secret store. The store must hold the BucketFS service
             parameters (bfs_host_name or db_host_name, bfs_port,
             bfs_service), the access credentials (bfs_user,
             bfs_password), and the bucket name (bfs_bucket), as well

exasol/itde_manager.py

@@ -25,7 +25,7 @@ def bring_itde_up(conf: Secrets) -> None:
     and Google name server address. Additionally, can set the following
     parameters with values collected from the secret store:
     - database port forwarding,
-    - bucket-fs port forwarding,
+    - BucketFS port forwarding,
     - database memory size (the value is assumed to be the number of gigabytes),
     - database disk size (the value is assumed to be the number of gigabytes).
 
@@ -37,7 +37,7 @@ def bring_itde_up(conf: Secrets) -> None:
     takes down the environment.
 
     The function saves the main AI-Lab configuration parameters, such as the DB and
-    bucket-fs connection parameters, in the secret store.
+    BucketFS connection parameters, in the secret store.
     """
 
     mem_size = f'{conf.get(AILabConfig.mem_size, "4")} GiB'
@@ -70,7 +70,7 @@ def bring_itde_up(conf: Secrets) -> None:
     conf.save(AILabConfig.bfs_service, "bfsdefault")
     conf.save(AILabConfig.bfs_bucket, "default")
     conf.save(AILabConfig.db_encryption, "True")
-    # The bucket-fs encryption is turned off temporarily.
+    # The BucketFS encryption is turned off temporarily.
     conf.save(AILabConfig.bfs_encryption, "False")
     conf.save(AILabConfig.cert_vld, "False")
 

exasol/sagemaker_extension_wrapper.py

@@ -17,7 +17,7 @@
 from exasol.secret_store import Secrets
 from exasol.ai_lab_config import AILabConfig as CKey
 
-# Root directory in a bucket-fs bucket where all stuff of the Sagemaker
+# Root directory in a BucketFS bucket where all stuff of the Sagemaker
 # Extension, including its language container, will be uploaded.
 PATH_IN_BUCKET = "SME"
 
@@ -49,7 +49,7 @@ def deploy_language_container(conf: Secrets, version: str) -> None:
     Parameters:
         conf:
             The secret store. The store must contain the DB connection parameters
-            and the parameters of the bucket-fs service.
+            and the parameters of the BucketFS service.
         version:
             Sagemaker Extension version.
     """
@@ -117,7 +117,7 @@ def initialize_sme_extension(conf: Secrets,
     Parameters:
         conf:
             The secret store. The store should contain all the required
-            parameters for accessing the database, bucket-fs and AWS.
+            parameters for accessing the database, BucketFS and AWS.
         version:
             Sagemaker Extension version. If not specified the hardcoded
             latest known version will be used.

exasol/transformers_extension_wrapper.py

@@ -24,7 +24,7 @@
 from exasol.secret_store import Secrets
 from exasol.ai_lab_config import AILabConfig as CKey
 
-# Root directory in a bucket-fs bucket where all stuff of the Transformers
+# Root directory in a BucketFS bucket where all stuff of the Transformers
 # Extension, including its language container, will be uploaded.
 PATH_IN_BUCKET = "TE"
 
@@ -36,11 +36,11 @@
 # store with this key.
 ACTIVATION_KEY = ACTIVATION_KEY_PREFIX + "te"
 
-# The name of the connection object with bucket-fs location and credentials
+# The name of the connection object with BucketFS location and credentials
 # will be prefixed with this string.
 BFS_CONNECTION_PREFIX = "TE_BFS"
 
-# Models will be uploaded into this directory in bucket-fs.
+# Models will be uploaded into this directory in BucketFS.
 BFS_MODELS_DIR = 'te_models'
 
 # The name of the connection object with a Huggingface token will be prefixed
@@ -71,7 +71,7 @@ def deploy_language_container(conf: Secrets,
     Parameters:
         conf:
             The secret store. The store must contain the DB connection parameters
-            and the parameters of the bucket-fs service.
+            and the parameters of the BucketFS service.
         version:
             Transformers Extension version.
         language_alias:
@@ -145,7 +145,7 @@ def initialize_te_extension(conf: Secrets,
     Parameters:
         conf:
             The secret store. The store should contain all the required
-            parameters for accessing the database and bucket-fs.
+            parameters for accessing the database and BucketFS.
         version:
             Transformers Extension version. If not specified the hardcoded
             latest known version will be used.
@@ -158,7 +158,7 @@ def initialize_te_extension(conf: Secrets,
             If set to False will skip the deployment of the UDF scripts.
         run_encapsulate_bfs_credentials:
             If set to False will skip the creation of the database connection
-            object encapsulating the bucket-fs credentials.
+            object encapsulating the BucketFS credentials.
         run_encapsulate_hf_token:
             If set to False will skip the creation of the database connection
             object encapsulating the Huggingface token.