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BatchRequest

class great_expectations.core.batch.BatchRequest(datasource_name: str, data_connector_name: str, data_asset_name: str, data_connector_query: Optional[dict] = None, limit: Optional[int] = None, batch_spec_passthrough: Optional[dict] = None)#

A BatchRequest is the way to specify which data Great Expectations will validate.

A Batch Request is provided to a Datasource in order to create a Batch.

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The data_connector_query parameter can include an index slice:

{
    "index": "-3:"
}

or it can include a filter:

{
    "batch_filter_parameters": {"year": "2020"}
}

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

  • data_connector_query – a dictionary of query parameters the DataConnector should use to filter the batches returned from a BatchRequest

  • limit – if specified, the maximum number of batches to be returned (limit does not affect the number of records in each batch)

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

Returns:

BatchRequest

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 BatchRequestBase.

Returns:

A JSON-serializable dict representation of this BatchRequestBase.