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.
- -Relevant Documentation Links -
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, JSONValues], List[JSONValues], str, int, float, bool]]]#
-
Returns a JSON-serializable dict representation of this BatchRequestBase.
- Returns
-
A JSON-serializable dict representation of this BatchRequestBase.