Verwenden der Apache Airflow REST API

def get_token_info(region, env_name):
  logging.basicConfig(level=logging.INFO)
						
  try:
    # Initialize MWAA client and request a web login token
    mwaa = boto3.client('mwaa', region_name=region)
    response = mwaa.create_web_login_token(Name=env_name)
						
    # Extract the web server hostname and login token
    web_server_host_name = response["WebServerHostname"]
    web_token = response["WebToken"]
						
    # Construct the URL needed for authentication 
    login_url = f"https://{web_server_host_name}/pluginsv2/aws_mwaa/login"
    login_payload = {"token": web_token}
						
    # Make a POST request to the MWAA login url using the login payload
    response = requests.post(
      login_url,
      data=login_payload,
      timeout=10
    )
						
    # Check if login was successful
    if response.status_code == 200:
						
    # Return the hostname and the session cookie 
    return (
      web_server_host_name,
      response.cookies['_token']
    )
    else:
      # Log an error
      logging.error("Failed to log in: HTTP %d", response.status_code)
      return None
      except requests.RequestException as e:
      
      # Log any exceptions raised during the request to the MWAA login endpoint
      logging.error("Request failed: %s", str(e))
      return None
      except Exception as e:
      
      # Log any other unexpected exceptions
      logging.error("An unexpected error occurred: %s", str(e))
      return None

def get_session_info(region, env_name):
  logging.basicConfig(level=logging.INFO)

  try:
      # Initialize MWAA client and request a web login token
      mwaa = boto3.client('mwaa', region_name=region)
      response = mwaa.create_web_login_token(Name=env_name)
      
      # Extract the web server hostname and login token
      web_server_host_name = response["WebServerHostname"]
      web_token = response["WebToken"]
      
      # Construct the URL needed for authentication 
      login_url = f"https://{web_server_host_name}/aws_mwaa/login"
      login_payload = {"token": web_token}

      # Make a POST request to the MWAA login url using the login payload
      response = requests.post(
          login_url,
          data=login_payload,
          timeout=10
      )

      # Check if login was succesfull 
      if response.status_code == 200:
      
          # Return the hostname and the session cookie 
          return (
              web_server_host_name,
              response.cookies["session"]
          )
      else:
          # Log an error
          logging.error("Failed to log in: HTTP %d", response.status_code)
          return None
  except requests.RequestException as e:
       # Log any exceptions raised during the request to the MWAA login endpoint
      logging.error("Request failed: %s", str(e))
      return None
  except Exception as e:
      # Log any other unexpected exceptions
      logging.error("An unexpected error occurred: %s", str(e))
      return None

def trigger_dag(region, env_name, dag_id):
						"""
						Triggers a DAG in a specified MWAA environment using the Airflow REST API.
						
						Args:
						region (str): AWS region where the MWAA environment is hosted.
						env_name (str): Name of the MWAA environment.
						dag_id (str): ID of the DAG to trigger.
						"""
						
						logging.info(f"Attempting to trigger DAG {dag_id} in environment {env_name} at region {region}")
						
						# Retrieve the web server hostname and token for authentication
						try:
						web_server_host_name, jwt_token = get_token_info(region, env_name)
						if not jwt_token:
						logging.error("Authentication failed, no jwt token retrieved.")
						return
						except Exception as e:
						logging.error(f"Error retrieving token info: {str(e)}")
						return
						
						# Prepare headers and payload for the request
						request_headers = {
						"Authorization": f"Bearer {jwt_token}",
						"Content-Type": "application/json" # Good practice to include, even for GET
						}
						
						# sample request body input
						json_body = {"logical_date": "2025-09-17T14:15:00Z"}
						
						# Construct the URL for triggering the DAG
						url = f"https://{web_server_host_name}/api/v2/dags/{dag_id}/dagRuns"
						
						# Send the POST request to trigger the DAG
						try:
						response = requests.post(url, headers=request_headers, json=json_body)
						# Check the response status code to determine if the DAG was triggered successfully
						if response.status_code == 200:
						logging.info("DAG triggered successfully.")
						else:
						logging.error(f"Failed to trigger DAG: HTTP {response.status_code} - {response.text}")
						except requests.RequestException as e:
						logging.error(f"Request to trigger DAG failed: {str(e)}")
						
						if __name__ == "__main__":
						logging.basicConfig(level=logging.INFO)
						
						# Check if the correct number of arguments is provided
						if len(sys.argv) != 4:
						logging.error("Incorrect usage. Proper format: python script_name.py {region} {env_name} {dag_id}")
						sys.exit(1)
						
						region = sys.argv[1]
						env_name = sys.argv[2]
						dag_id = sys.argv[3]
						
						# Trigger the DAG with the provided arguments
						trigger_dag(region, env_name, dag_id)

def trigger_dag(region, env_name, dag_name):
						"""
						Triggers a DAG in a specified MWAA environment using the Airflow REST API.
						
						Args:
						region (str): AWS region where the MWAA environment is hosted.
						env_name (str): Name of the MWAA environment.
						dag_name (str): Name of the DAG to trigger.
						"""
						
						logging.info(f"Attempting to trigger DAG {dag_name} in environment {env_name} at region {region}")
						
						# Retrieve the web server hostname and session cookie for authentication
						try:
						web_server_host_name, session_cookie = get_session_info(region, env_name)
						if not session_cookie:
						logging.error("Authentication failed, no session cookie retrieved.")
						return
						except Exception as e:
						logging.error(f"Error retrieving session info: {str(e)}")
						return
						
						# Prepare headers and payload for the request
						cookies = {"session": session_cookie}
						json_body = {"conf": {}}
						
						# Construct the URL for triggering the DAG
						url = f"https://{web_server_host_name}/api/v1/dags/{dag_id}/dagRuns"
						
						# Send the POST request to trigger the DAG
						try:
						response = requests.post(url, cookies=cookies, json=json_body)
						# Check the response status code to determine if the DAG was triggered successfully
						if response.status_code == 200:
						logging.info("DAG triggered successfully.")
						else:
						logging.error(f"Failed to trigger DAG: HTTP {response.status_code} - {response.text}")
						except requests.RequestException as e:
						logging.error(f"Request to trigger DAG failed: {str(e)}")
						
						if __name__ == "__main__":
						logging.basicConfig(level=logging.INFO)
						
						# Check if the correct number of arguments is provided
						if len(sys.argv) != 4:
						logging.error("Incorrect usage. Proper format: python script_name.py {region} {env_name} {dag_name}")
						sys.exit(1)
						
						region = sys.argv[1]
						env_name = sys.argv[2]
						dag_name = sys.argv[3]
						
						# Trigger the DAG with the provided arguments
						trigger_dag(region, env_name, dag_name)