Checkpoint

class great_expectations.checkpoint.Checkpoint(name: str, data_context: AbstractDataContext | None = None, expectation_suite_name: str | None = None, batch_request: BatchRequestBase | FluentBatchRequest | dict | None = None, validator: Validator | None = None, action_list: Sequence[ActionDict] | None = None, suite_parameters: dict | None = None, runtime_configuration: dict | None = None, validations: list[dict] | list[CheckpointValidationDefinition] | None = None, id: str | None = None, expectation_suite_id: str | None = None, default_validation_id: str | None = None)#

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

Checkpoints provide a convenient abstraction for bundling the Validation of a Batch (or Batches) of data against an Expectation Suite (or several), as well as the Actions that should be taken after the validation.

A Checkpoint uses a Validator to run one or more Expectation Suites against one or more Batches provided by one or more Batch Requests. Running a Checkpoint produces Validation Results and will result in optional Actions being performed if they are configured to do so.

Parameters:

• name – User-selected checkpoint name (e.g. “staging_tables”).

• data_context – Data context that is associated with the current checkpoint.

• expectation_suite_name – Expectation suite associated with checkpoint.

• batch_request – Batch request describing the batch of data to validate.

• action_list – A list of actions to perform after each batch is validated.

• suite_parameters – Suite parameters to use in generating this checkpoint.

• runtime_configuration – Runtime configuration to pass into the validator’s runtime configuration (e.g. result_format).

• validations – Validations to be executed as part of checkpoint.

• id – Great Expectations Cloud id for this Checkpoint.

• expectation_suite_id – Great Expectations Cloud id associated with Expectation Suite.

• default_validation_id – Default value used by Checkpoint if no Validations are configured.

Raises:

• ValueError – If BatchRequest contains batch_data, since only primitive types are allowed in the constructor.

• ValueError – If Validations contains batch_data, since only primitive types are allowed in the constructor.

run(expectation_suite_name: str | None = None, batch_request: BatchRequestBase | FluentBatchRequest | dict | None = None, validator: Validator | None = None, action_list: Sequence[ActionDict] | None = None, suite_parameters: dict | None = None, runtime_configuration: dict | None = None, validations: list[dict] | list[CheckpointValidationDefinition] | None = None, run_id: str | RunIdentifier | None = None, run_name: str | None = None, run_time: datetime.datetime | None = None, result_format: str | dict | None = None, expectation_suite_id: str | None = None) → CheckpointResult#

Validate against current Checkpoint.

Arguments allow for override of the current Checkpoint configuration.

Parameters:

• expectation_suite_name – Expectation suite associated with checkpoint.

• batch_request – Batch request describing the batch of data to validate.

• validator – Validator objects, loaded with Batch data samples, can be supplied (in lieu of “batch_request”)

• action_list – A list of actions to perform after each batch is validated.

• suite_parameters – Suite parameters to use in generating this checkpoint.

• runtime_configuration – Runtime configuration to pass into the validator’s runtime configuration (e.g. result_format).

• validations – Validations to be executed as part of checkpoint.

• run_id – The run_id for the validation; if None, a default value will be used.

• run_name – The run_name for the validation; if None, a default value will be used.

• run_time – The date/time of the run.

• result_format – One of several supported formatting directives for expectation validation results

• expectation_suite_id – Great Expectations Cloud id for the expectation suite

Raises:

• InvalidCheckpointConfigError – If run_id is provided with run_name or run_time.

• InvalidCheckpointConfigError – If result_format is not an expected type.

• CheckpointError – If Checkpoint does not contain a batch_request or validations.

Returns:

CheckpointResult