Apache Airflow

Common errors

Warnings

Install

Install compatibility reviewed last tested: 2026-05-12

Imports

• DAG

  from airflow.models.dag import DAG

• BashOperator

  from airflow.operators.bash import BashOperator

• PythonOperator

  from airflow.operators.python import PythonOperator

• TaskGroup

  from airflow.utils.task_group import TaskGroup

• Provider specific operators (e.g., S3Operator)
  wrong

  from airflow.operators.s3_operator import S3Operator

  correct

  from airflow.providers.amazon.operators.s3 import S3Operator

  Operators specific to external systems are now in provider packages (e.g., airflow.providers.<provider_name>.operators). The old top-level `airflow.operators` path is deprecated for these.

• XComArg
  wrong

  from airflow.utils.task_group import XComArg

  correct

  from airflow.models.xcom_arg import XComArg

  XComArg moved to airflow.models.xcom_arg in Airflow 3.0.

Quickstart last tested: 2026-04-24

This quickstart defines a simple DAG with Bash and Python operators. To run this locally after installing Airflow, save the code as a `.py` file (e.g., `dags/quickstart_dag.py`) in your `AIRFLOW_HOME/dags` directory. Then, initialize the database and start the Airflow standalone environment. **To set up and run Airflow locally (assuming `apache-airflow` is installed with `sqlite` support via `pip install "apache-airflow[sqlite]"`):** ```bash # (Optional) Set AIRFLOW_HOME, e.g., to a temporary directory export AIRFLOW_HOME=$(pwd)/airflow_home # Initialize the database and create an admin user (first time only) airflow standalone # Follow prompts to set admin password. This command also starts webserver, scheduler, and triggerer. # You can also start components separately: # airflow db migrate # airflow users create --username admin --firstname Airflow --lastname Admin --role Admin --email admin@example.com -p mypassword # airflow webserver --port 8080 # airflow scheduler # airflow triggerer # After starting, visit http://localhost:8080 to enable the DAG. ``` Remember to define `AIRFLOW_HOME` before running `airflow standalone` or `airflow db init`.

import os
from datetime import datetime

from airflow.models.dag import DAG
from airflow.operators.bash import BashOperator
from airflow.operators.python import PythonOperator


# Set AIRFLOW_HOME if not already set (e.g., in a local dev setup)
# os.environ['AIRFLOW_HOME'] = os.environ.get('AIRFLOW_HOME', '~/airflow')


def _greet(name):
    print(f"Hello, {name} from a Python task!")


with DAG(
    dag_id='simple_airflow_quickstart',
    start_date=datetime(2023, 1, 1),
    schedule_interval='@daily',
    catchup=False,
    tags=['quickstart'],
) as dag:
    start_task = BashOperator(
        task_id='start_workflow',
        bash_command='echo "Starting the workflow!"',
    )

    greet_task = PythonOperator(
        task_id='greet_with_python',
        python_callable=_greet,
        op_kwargs={'name': 'Airflow User'},
    )

    end_task = BashOperator(
        task_id='end_workflow',
        bash_command='echo "Workflow finished!"',
    )

    start_task >> greet_task >> end_task