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Version: 1.0 prerelease

RuntimeDataConnector

class great_expectations.datasource.data_connector.RuntimeDataConnector(name: str, datasource_name: str, execution_engine: ExecutionEngine, batch_identifiers: Optional[list] = None, batch_spec_passthrough: Optional[dict] = None, assets: Optional[dict] = None, id: Optional[str] = None)#

A Data Connector that allows users to specify a Batch’s data directly using a Runtime Batch Request.

A Runtime Batch Request contains either an in-memory Pandas or Spark DataFrame, a filesystem or S3 path, or an arbitrary SQL query.

Parameters:

  • name – The name of the Data Connector.

  • datasource_name – The name of this Data Connector’s Datasource.

  • execution_engine – The Execution Engine object to used by this Data Connector to read the data.

  • batch_identifiers – A list of keys that must be defined in the batch identifiers dict of the Runtime Batch Request.

  • batch_spec_passthrough – Dictionary with keys that will be added directly to the batch spec.

  • id – The unique identifier for this Data Connector used when running in cloud mode.

get_available_data_asset_names()→ List[str]#

Returns a list of data_assets that are both defined at runtime, and defined in DataConnector configuration