great_expectations.datasource.data_connector.inferred_asset_azure_data_connector

Module Contents

Classes

InferredAssetAzureDataConnector(name: str, datasource_name: str, container: str, execution_engine: Optional[ExecutionEngine] = None, default_regex: Optional[dict] = None, sorters: Optional[list] = None, name_starts_with: str = ‘’, delimiter: str = ‘/’, azure_options: Optional[dict] = None, batch_spec_passthrough: Optional[dict] = None)

Extension of InferredAssetFilePathDataConnector used to connect to Azure Blob Storage

great_expectations.datasource.data_connector.inferred_asset_azure_data_connector.logger
great_expectations.datasource.data_connector.inferred_asset_azure_data_connector.BlobServiceClient
class great_expectations.datasource.data_connector.inferred_asset_azure_data_connector.InferredAssetAzureDataConnector(name: str, datasource_name: str, container: str, execution_engine: Optional[ExecutionEngine] = None, default_regex: Optional[dict] = None, sorters: Optional[list] = None, name_starts_with: str = '', delimiter: str = '/', azure_options: Optional[dict] = None, batch_spec_passthrough: Optional[dict] = None)

Bases: great_expectations.datasource.data_connector.inferred_asset_file_path_data_connector.InferredAssetFilePathDataConnector

Extension of InferredAssetFilePathDataConnector used to connect to Azure Blob Storage

The InferredAssetAzureDataConnector is one of two classes (ConfiguredAssetAzureDataConnector being the other one) designed for connecting to filesystem-like data, more specifically files on Azure Blob Storage. It connects to assets inferred from container, name_starts_with, and file name by default_regex.

As much of the interaction with the SDK is done through a BlobServiceClient, please refer to the official docs if a greater understanding of the supported authentication methods and general functionality is desired. Source: https://docs.microsoft.com/en-us/python/api/azure-storage-blob/azure.storage.blob.blobserviceclient?view=azure-python

build_batch_spec(self, batch_definition: BatchDefinition)

Build BatchSpec from batch_definition by calling DataConnector’s build_batch_spec function.

Parameters

batch_definition (BatchDefinition) – to be used to build batch_spec

Returns

BatchSpec built from batch_definition

_get_data_reference_list(self, data_asset_name: Optional[str] = None)

List objects in the underlying data store to create a list of data_references.

This method is used to refresh the cache.

_get_full_file_path(self, path: str, data_asset_name: Optional[str] = None)