How‑To Guides

This section provides practical step‑by‑step instructions to accomplish common tasks in Apache Airflow. Choose a topic from the sidebar or explore the highlights below.

Creating your first DAG

Learn how to define a simple DAG that prints “Hello World”.

from airflow import DAG
from airflow.operators.bash import BashOperator
from datetime import datetime

with DAG(
    dag_id="hello_world",
    start_date=datetime(2024, 1, 1),
    schedule_interval="@daily",
    catchup=False,
) as dag:
    BashOperator(
        task_id="print_hello",
        bash_command="echo 'Hello World!'"
    )

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Using PythonOperator

Execute Python callables directly inside your tasks.

from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime

def greet():
    print("Greetings from Airflow!")

with DAG(
    "python_operator_example",
    start_date=datetime(2024, 1, 1),
    schedule_interval=None,
    catchup=False,
) as dag:
    PythonOperator(
        task_id="greet_task",
        python_callable=greet
    )

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Setting up Connections

Configure external services (e.g., Postgres, S3) via the UI or CLI.

# CLI example
airflow connections add 'my_postgres' \
    --conn-uri 'postgresql://user:password@host:5432/dbname'

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Deploying Airflow with Docker Compose

Quickly spin up a local development environment.

# Clone the official repo
git clone https://github.com/apache/airflow.git
cd airflow

# Export version
export AIRFLOW_VERSION=2.9.0
export PYTHON_VERSION=3.11

# Generate compose file
docker compose up airflow-webserver

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