Skip to main content
Version: 0.17.19

Create a new Checkpoint

This guide will help you create a new CheckpointThe primary means for validating data in a production deployment of Great Expectations., which allows you to couple an Expectation SuiteA collection of verifiable assertions about data. with a data set to ValidateThe act of applying an Expectation Suite to a Batch..

Prerequisites​

Create a Checkpoint​

To modify the following code for your use case, replace batch_request and expectation_suite_name with your own paremeters.

checkpoint = context.add_or_update_checkpoint(
    name="my_checkpoint",
    validations=[
        {
            "batch_request": batch_request,
            "expectation_suite_name": "my_expectation_suite",
        },
    ],
)

For other Checkpoint configuration options, see Manage Checkpoints.

Run your Checkpoint (Optional)​

checkpoint_result = checkpoint.run()

The returned checkpoint_result contains information about the checkpoint run.

Build Data Docs (Optional)​

Run the following Python code to build Data DocsHuman readable documentation generated from Great Expectations metadata detailing Expectations, Validation Results, etc. with the latest checkpoint run results:

context.build_data_docs()

Retrieve your Checkpoint (Optional)​

Run the following Python code to retrieve the Checkpoint:

retrieved_checkpoint = context.get_checkpoint(name="my_checkpoint")