stepfunctions

import os from stepfunctions.workflow import Workflow from stepfunctions.steps import Pass, Chain # Dummy AWS credentials for local testing/placeholder - replace with actual credentials/roles in production # Ensure your environment has AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_SESSION_TOKEN (optional) and AWS_REGION set # or your ~/.aws/credentials and ~/.aws/config are configured. # For actual deployment, you'd typically use an IAM role. # Define a simple Pass state pass_step = Pass( state_id='MyPassState', parameters={ 'input_data.$': '$' } ) # Create a workflow workflow = Workflow( name='MySimpleWorkflow', definition=pass_step, role=os.environ.get('STEPFUNCTIONS_EXECUTION_ROLE_ARN', 'arn:aws:iam::123456789012:role/FakeStepFunctionsExecutionRole') # Replace with your IAM Role ARN ) try: # Create the workflow on AWS Step Functions workflow.create() print(f"Workflow '{workflow.name}' created successfully.") # Execute the workflow with sample input execution = workflow.execute(inputs={'message': 'Hello from Step Functions SDK!'}) print(f"Workflow execution started with ARN: {execution.execution_arn}") # Wait for execution to complete and print output execution.wait_for_completion() print(f"Execution finished. Output: {execution.get_output()}") # Clean up (optional, for real workflows, you might not delete immediately) # workflow.delete() # print(f"Workflow '{workflow.name}' deleted.") except Exception as e: print(f"An error occurred: {e}") print("Please ensure your AWS credentials are configured and the IAM role ARN is valid and has necessary permissions.") print("You can define the IAM role ARN as an environment variable STEPFUNCTIONS_EXECUTION_ROLE_ARN.")