What is a DAG in Apache Airflow?

A DAG (Directed Acyclic Graph) is the core concept in Airflow. It is a collection of tasks organized with dependencies and relationships that define how they should run. The "directed" part means each edge has a direction (from one task to another). "Acyclic" means there are no loops - you cannot create a cycle where task A depends on task B which depends on task A.

A simple DAG example:

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

with DAG('my_dag', start_date=datetime(2024, 1, 1), schedule='@daily') as dag:
    t1 = PythonOperator(task_id='task_1', python_callable=lambda: print('Hello'))
    t2 = PythonOperator(task_id='task_2', python_callable=lambda: print('World'))
    t1 » t2 # t2 runs after t1

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