Checkpoint
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 Description 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.
Runs the Checkpoint's underlying Validation Definitions and Actions.
Parameters
Name Description batch_parameters
Parameters to be used when loading the Batch.
expectation_parameters
Parameters to be used when validating the Batch.
run_id
An optional unique identifier for the run.
Returns
Type Description CheckpointResult
A CheckpointResult object containing the results of the run.
Raises
Type Description CheckpointRunWithoutValidationDefinitionError
If the Checkpoint is run without any Validation Definitions.
CheckpointNotAddedError
If the Checkpoint has not been added to the Store.
CheckpointNotFreshError
If the Checkpoint has been modified since it was last added to the Store.
Save the current state of this Checkpoint.
class great_expectations.Checkpoint(
*,
name: str,
validation_definitions: List[great_expectations.core.validation_definition.ValidationDefinition],
actions: List[great_expectations.checkpoint.actions.ValidationAction] = None,
result_format: Union[great_expectations.core.result_format.ResultFormat,
dict,
Literal['BOOLEAN_ONLY',
'BASIC',
'SUMMARY',
'COMPLETE']] = ResultFormat.SUMMARY,
id: Optional[str] = None
)
Methods
run
run(
batch_parameters: Dict[str,
Any] | None = None,
expectation_parameters: SuiteParameterDict | None = None,
run_id: RunIdentifier | None = None
) → CheckpointResult
save
save() → None