StoreEvaluationParametersAction

class great_expectations.checkpoint.StoreEvaluationParametersAction(data_context: AbstractDataContext, target_store_name: Optional[str] = None)#

Store evaluation parameters from a validation result.

Evaluation parameters allow expectations to refer to statistics/metrics computed in the process of validating other prior expectations.

Typical usage example:

    - name: store_evaluation_params
  action:
    class_name: StoreEvaluationParametersAction
    target_store_name: evaluation_parameter_store

Parameters

• data_context – GX Data Context.

• target_store_name – The name of the store in the Data Context to store the evaluation parameters.

Raises

TypeError – validation_result_id must be of type ValidationResultIdentifier or GeCloudIdentifier, not .

run(validation_result_suite: ExpectationSuiteValidationResult, validation_result_suite_identifier: Union[ValidationResultIdentifier, GXCloudIdentifier], data_asset, expectation_suite_identifier: Optional[ExpectationSuiteIdentifier] = None, checkpoint_identifier=None, **kwargs)#

Public entrypoint GX uses to trigger a ValidationAction.

When a ValidationAction is configured in a Checkpoint, this method gets called after the Checkpoint produces an ExpectationSuiteValidationResult.

Parameters

• validation_result_suite – An instance of the ExpectationSuiteValidationResult class.

• validation_result_suite_identifier – an instance of either the ValidationResultIdentifier class (for open source Great Expectations) or the GXCloudIdentifier (from Great Expectations Cloud).

• data_asset – An instance of the Validator class.

• expectation_suite_identifier – Optionally, an instance of the ExpectationSuiteIdentifier class.

• checkpoint_identifier – Optionally, an Identifier for the Checkpoint.

• kwargs – named parameters that are specific to a given Action, and need to be assigned a value in the Action's configuration in a Checkpoint's action_list.

Returns

A Dict describing the result of the Action.