How to identify all broken dag from airflow

Question

Using airflow instance in Google cloud platform. on airflow page am getting broken DAG message which, want to clean after some time. want to write a script which will be run from airflow and identify all broken dags and delete those python files from DAG bucket. anyone can help me for this?

Answer 1

I have never personally tested all the scripts, but some time ago I came across this set of wonderful Airflow maintenance related scripts.

Among them, you can find this Python script related to broken DAGs cleanup:

"""
A maintenance workflow that you can deploy into Airflow to periodically delete broken DAG file(s).
airflow trigger_dag airflow-delete-broken-dags
"""
from airflow.models import DAG, ImportError
from airflow.operators.python_operator import PythonOperator
from airflow import settings
from datetime import timedelta
import os
import os.path
import socket
import logging
import airflow


# airflow-delete-broken-dags
DAG_ID = os.path.basename(__file__).replace(".pyc", "").replace(".py", "")
START_DATE = airflow.utils.dates.days_ago(1)
# How often to Run. @daily - Once a day at Midnight
SCHEDULE_INTERVAL = "@daily"
# Who is listed as the owner of this DAG in the Airflow Web Server
DAG_OWNER_NAME = "operations"
# List of email address to send email alerts to if this job fails
ALERT_EMAIL_ADDRESSES = []
# Whether the job should delete the logs or not. Included if you want to
# temporarily avoid deleting the logs
ENABLE_DELETE = True

default_args = {
    'owner': DAG_OWNER_NAME,
    'email': ALERT_EMAIL_ADDRESSES,
    'email_on_failure': True,
    'email_on_retry': False,
    'start_date': START_DATE,
    'retries': 1,
    'retry_delay': timedelta(minutes=1)
}

dag = DAG(
    DAG_ID,
    default_args=default_args,
    schedule_interval=SCHEDULE_INTERVAL,
    start_date=START_DATE,
    tags=['teamclairvoyant', 'airflow-maintenance-dags']
)
if hasattr(dag, 'doc_md'):
    dag.doc_md = __doc__
if hasattr(dag, 'catchup'):
    dag.catchup = False


def delete_broken_dag_files(**context):

    logging.info("Starting to run Clear Process")

    try:
        host_name = socket.gethostname()
        host_ip = socket.gethostbyname(host_name)
        logging.info("Running on Machine with Host Name: " + host_name)
        logging.info("Running on Machine with IP: " + host_ip)
    except Exception as e:
        print("Unable to get Host Name and IP: " + str(e))

    session = settings.Session()

    logging.info("Configurations:")
    logging.info("enable_delete:            " + str(ENABLE_DELETE))
    logging.info("session:                  " + str(session))
    logging.info("")

    errors = session.query(ImportError).all()

    logging.info(
        "Process will be removing broken DAG file(s) from the file system:"
    )
    for error in errors:
        logging.info("\tFile: " + str(error.filename))
    logging.info(
        "Process will be Deleting " + str(len(errors)) + " DAG file(s)"
    )

    if ENABLE_DELETE:
        logging.info("Performing Delete...")
        for error in errors:
            if os.path.exists(error.filename):
                os.remove(error.filename)
            session.delete(error)
        logging.info("Finished Performing Delete")
    else:
        logging.warn("You're opted to skip Deleting the DAG file(s)!!!")

    logging.info("Finished")


delete_broken_dag_files = PythonOperator(
    task_id='delete_broken_dag_files',
    python_callable=delete_broken_dag_files,
    provide_context=True,
    dag=dag)

All the credit is for the author, I am only reproducing the full source code here.