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BatchDefinition

class great_expectations.core.batch.BatchDefinition(datasource_name: str, data_connector_name: str, data_asset_name: str, batch_identifiers: great_expectations.core.id_dict.IDDict, batch_spec_passthrough: Optional[dict] = None)#

Precisely identifies a set of data from a data source.

More concretely, a BatchDefinition includes all the information required to precisely identify a set of data from the external data source that should be translated into a Batch. One or more BatchDefinitions should always bereturned from the Datasource, as a result of processing the Batch Request.

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Parameters:

  • datasource_name – name of the Datasource used to connect to the data

  • data_connector_name – name of the DataConnector used to connect to the data

  • data_asset_name – name of the DataAsset used to connect to the data

  • batch_identifiers – key-value pairs that the DataConnector will use to obtain a specific set of data

  • batch_spec_passthrough – a dictionary of additional parameters that the ExecutionEngine will use to obtain a specific set of data

Returns:

BatchDefinition

to_json_dict() → Dict[str, Optional[Union[Dict[str, Optional[Union[Dict[str, JSONValues], List[JSONValues], str, int, float, bool]]], List[Optional[Union[Dict[str, JSONValues], List[JSONValues], str, int, float, bool]]], str, int, float, bool]]]#

Returns a JSON-serializable dict representation of this BatchDefinition.

Returns:

A JSON-serializable dict representation of this BatchDefinition.