BatchRequest

class great_expectations.core.batch.BatchRequest(datasource_name: str, data_connector_name: str, data_asset_name: str, data_connector_query: dict | None = None, limit: int | None = None, batch_spec_passthrough: dict | None = 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.

Relevant Documentation Links

• How To Get One Or More Batches Of Data From A Configured Datasource

• Batch Request

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, JSONValues]#

Returns a JSON-serializable dict representation of this BatchRequestBase.

Returns:

A JSON-serializable dict representation of this BatchRequestBase.