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)#
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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
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datasource_name – name of the Datasource used to connect to the data
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data_connector_name – name of the DataConnector used to connect to the data
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data_asset_name – name of the DataAsset used to connect to the data
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data_connector_query – a dictionary of query parameters the DataConnector should use to filter the batches returned from a BatchRequest
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limit – if specified, the maximum number of batches to be returned (limit does not affect the number of records in each batch)
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batch_spec_passthrough – a dictionary of additional parameters that the ExecutionEngine will use to obtain a specific set of data
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- Returns
BatchRequest
- to_json_dict() dict[str, JSONValues]#
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Returns a JSON-serializable dict representation of this BatchRequestBase.
- Returns
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A JSON-serializable dict representation of this BatchRequestBase.