great_expectations.datasource.data_connector.inferred_asset_azure_data_connector
¶
Module Contents¶
Classes¶
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Extension of InferredAssetFilePathDataConnector used to connect to Azure Blob Storage |
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great_expectations.datasource.data_connector.inferred_asset_azure_data_connector.
logger
¶
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great_expectations.datasource.data_connector.inferred_asset_azure_data_connector.
BlobServiceClient
¶
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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, id: Optional[str] = None)¶ -
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
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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
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_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.
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_get_full_file_path
(self, path: str, data_asset_name: Optional[str] = None)¶
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