Manage Checkpoints

A Checkpoint validates Expectation Suite data. After you create a Checkpoint to validate data, you can save and reuse the Checkpoint.

To learn more about Checkpoints, see Checkpoint.

Prerequisites

• You have set up your environment and the GX Agent is running.

• You have a Data Asset.

• You have created an Expectation.

Add a Checkpoint

1. In Jupyter Notebook, run the following code to import the great_expectations module and the existing Data Context:

   Jupyter Notebook

   import great_expectations as gx
   context = gx.get_context()

2. Run the following code to retrieve the Expectation Suite:

   Jupyter Notebook

   expectation_suite = context.get_expectation_suite(expectation_suite_name=<expectation_name>)

3. Run the following code to assign a name to the Checkpoint:

   Jupyter Notebook

   checkpoint_name = <checkpoint_name> 

4. Run the following code to define the Checkpoint configuration including the Data Source and Data Asset names:

   Jupyter Notebook

   checkpoint_config = {
       "name": checkpoint_name,
       "validations": [{
           "expectation_suite_name": expectation_suite.expectation_suite_name,
            "expectation_suite_ge_cloud_id": expectation_suite.ge_cloud_id,
            "batch_request": {
               "datasource_name": "<data_source_name>",
               "data_asset_name": "<data_asset_name>",
     },
   }],
   } 

5. Run the following code to add the Checkpoint:

   Jupyter Notebook

   checkpoint = context.add_or_update_checkpoint(**checkpoint_config) 

6. Optional. Run the following code to confirm the Checkpoint name:

   Jupyter Notebook

   print(checkpoint) 

7. Optional. Run the following code to run the Checkpoint:

   Jupyter Notebook

   result = checkpoint.run() 

Run a Checkpoint

1. In GX Cloud, click Checkpoints.

2. Optional. To run a Checkpoint on a failing Checkpoint, click Failures Only.

3. Optional. To run a specific Checkpoint, select it in the Checkpoints pane.

4. Click Run Checkpoint for the Checkpoint you want to run.

Edit a Checkpoint configuration

1. In Jupyter Notebook, run the following code to import the great_expectations module and the existing Data Context:

   Jupyter Notebook

   import great_expectations as gx
   context = gx.get_context()

2. Run the following Python code to retrieve the Checkpoint:

   Jupyter Notebook

   retrieved_checkpoint = context.get_checkpoint(name="<checkpoint_name>") 

3. Edit the Checkpoint configuration.

4. Run the following code to update the Checkpoint configuration:

   Jupyter Notebook

   checkpoint = context.add_or_update_checkpoint(**checkpoint_config) 

Delete a Checkpoint

1. In GX Cloud, click Checkpoints.

2. Click Delete Checkpoint for the Checkpoint you want to delete.

3. Click Delete.