Airflow DAG Examples
Explore various Airflow DAG examples, including dynamic DAGs and example DAGs in Apache Airflow. Learn how to create efficient workflows with our comprehensive examples.
Airflow Script Generator
Examples
Daily DAG with Basic Tasks
Weekly DAG with Dependencies
DAG with Task Groups
DAG with Decorators
Examples
Daily DAG with Basic Tasks
Weekly DAG with Dependencies
DAG with Task Groups
DAG with Decorators
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How to get started
Step 1
Enter the name of your DAG, schedule interval, and tasks in the provided form.
Step 2
Customize your DAG with additional information such as dependencies, retries, and owner.
Step 3
Generate your Python script and integrate it into your Apache Airflow environment.
Main Features
DAGs in Python
Learn how to create and manage DAGs using Python. Our tool helps you generate Python DAG scripts effortlessly, ensuring smooth integration with your Airflow setup.
Advanced Airflow Concepts
Master advanced Airflow concepts such as task groups and DAG decorators. Enhance your workflow automation with our expert guidance and examples.
FAQ
What is an Airflow DAG?
A Directed Acyclic Graph (DAG) in Apache Airflow is a collection of all the tasks you want to run, organized in a way that reflects their relationships and dependencies.
How do I create a dynamic DAG in Airflow?
Dynamic DAGs in Airflow can be created by using Python code to generate tasks and dependencies programmatically. Our tool simplifies this process by generating the necessary code for you.
What are task groups in Airflow?
Task groups in Airflow allow you to group related tasks together, making it easier to manage complex workflows. Our generator supports task groups to help you organize your DAGs efficiently.