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prefect_azure.ml_datastore

Tasks for interacting with Azure ML Datastore

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Functions

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ml_list_datastores 

ml_list_datastores(ml_credentials: 'AzureMlCredentials') -> Dict
Lists the Datastores in the Workspace. Args:
  • ml_credentials: Credentials to use for authentication with Azure.

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ml_get_datastore 

ml_get_datastore(ml_credentials: 'AzureMlCredentials', datastore_name: Optional[str] = None) -> Datastore
Gets the Datastore within the Workspace. Args:
  • ml_credentials: Credentials to use for authentication with Azure.
  • datastore_name: The name of the Datastore. If None, then the default Datastore of the Workspace is returned.

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ml_upload_datastore 

ml_upload_datastore(path: Union[str, Path, List[Union[str, Path]]], ml_credentials: 'AzureMlCredentials', target_path: Union[str, Path, None] = None, relative_root: Union[str, Path, None] = None, datastore_name: Optional[str] = None, overwrite: bool = False) -> 'DataReference'
Uploads local files to a Datastore. Args:
  • path: The path to a single file, single directory, or a list of path to files to be uploaded.
  • ml_credentials: Credentials to use for authentication with Azure.
  • target_path: The location in the blob container to upload to. If None, then upload to root.
  • relative_root: The root from which is used to determine the path of the files in the blob. For example, if we upload /path/to/file.txt, and we define base path to be /path, when file.txt is uploaded to the blob storage, it will have the path of /to/file.txt.
  • datastore_name: The name of the Datastore. If None, then the default Datastore of the Workspace is returned.
  • overwrite: Overwrite existing file(s).

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ml_register_datastore_blob_container 

ml_register_datastore_blob_container(container_name: str, ml_credentials: 'AzureMlCredentials', blob_storage_credentials: 'AzureBlobStorageCredentials', datastore_name: Optional[str] = None, create_container_if_not_exists: bool = False, overwrite: bool = False, set_as_default: bool = False) -> 'AzureBlobDatastore'
Registers a Azure Blob Storage container as a Datastore in a Azure ML service Workspace. Args:
  • container_name: The name of the container.
  • ml_credentials: Credentials to use for authentication with Azure ML.
  • blob_storage_credentials: Credentials to use for authentication with Azure Blob Storage.
  • datastore_name: The name of the datastore. If not defined, the container name will be used.
  • create_container_if_not_exists: Create a container, if one does not exist with the given name.
  • overwrite: Overwrite an existing datastore. If the datastore does not exist, it will be created.
  • set_as_default: Set the created Datastore as the default datastore for the Workspace.