Checkpoint

class great_expectations.Checkpoint(*, name: str, validation_definitions: List[great_expectations.core.validation_definition.ValidationDefinition], actions: List[Union[great_expectations.checkpoint.actions.EmailAction, great_expectations.checkpoint.actions.MicrosoftTeamsNotificationAction, great_expectations.checkpoint.actions.SlackNotificationAction, great_expectations.checkpoint.actions.UpdateDataDocsAction]] = None, result_format: Union[great_expectations.core.result_format.ResultFormat, dict, Literal['BOOLEAN_ONLY', 'BASIC', 'SUMMARY', 'COMPLETE']] = ResultFormat.SUMMARY, id: Optional[str] = None)#

A Checkpoint is the primary means for validating data in a production deployment of Great Expectations.

Checkpoints provide a convenient abstraction for running a number of validation definitions and triggering a set of actions to be taken after the validation step.

Parameters

• name – The name of the checkpoint.

• validation_definitions – List of validation definitions to be run.

• actions – List of actions to be taken after the validation definitions are run.

• result_format – The format in which to return the results of the validation definitions. Default is ResultFormat.SUMMARY.

• id – An optional unique identifier for the checkpoint.

run(batch_parameters: Dict[str, Any] | None = None, expectation_parameters: SuiteParameterDict | None = None, run_id: RunIdentifier | None = None) → CheckpointResult#

save()→ None#