text: """
  This is a basic generated Great Expectations script that runs a checkpoint.
  
  Checkpoints are the primary method for validating batches of data in production and triggering any followup actions.
  
  A Checkpoint facilitates running a validation as well as configurable Actions such as updating Data Docs, sending a
  notification to team members about validation results, or storing a result in a shared cloud storage.
  
  See also <cyan>https://docs.greatexpectations.io/en/latest/guides/how_to_guides/validation/how_to_create_a_new_checkpoint_using_test_yaml_config.html</cyan> for more information about the Checkpoints and how to configure them in your Great Expectations environment.
  
  Checkpoints can be run directly without this script using the `great_expectations checkpoint run` command.  This script
  is provided for those who wish to run checkpoints in python.
  
  Usage:
  - Run this file: `python great_expectations/uncommitted/run_{0:s}.py`.
  - This can be run manually or via a scheduler such, as cron.
  - If your pipeline runner supports python snippets, then you can paste this into your pipeline.
  """
  import sys
  
  from great_expectations.checkpoint.types.checkpoint_result import CheckpointResult
  from great_expectations.data_context import DataContext
  
  data_context: DataContext = DataContext(context_root_dir="{1:s}")
  
  result: CheckpointResult = data_context.run_checkpoint(
      checkpoint_name="{0:s}",
      batch_request=None,
      run_name=None,
  )
  
  if not result["success"]:
      print("Validation failed!")
      sys.exit(1)
  
  print("Validation succeeded!")
  sys.exit(0)
  