DAG Factory documentation

Everything you need to know about how to build Apache Airflow® workflows using YAML files.

Getting started

Are you new to DAG Factory? This is the place to start!

• DAG Factory at a glance

  • Quickstart with Airflow standalone
  • Quickstart with Astro CLI

• Using YAML instead of Python

  • Traditional Airflow Operators
  • TaskFlow API

Command Line

• Using DAG Factory CLI features

Configuration

• Configuring your workflows
• load_yml_dags Function
• Define Python Object
• Defaults
• Environment variables
• Schedule

Features

• Dynamic tasks
• Callbacks
• Custom operators
• Multiple configuration files
• Datasets scheduling
• Assets Scheduling
• KubernetesPodOperator
• HttpSensor

📢 Dag-Factory 1.0 Released

Version 1.0 introduces important improvements and breaking changes to support modern Airflow usage.

👉 See the Migration Guide to upgrade from earlier versions.

🚀 Dag-Factory Supports Airflow 3

DAG-Factory is compatible with Apache Airflow 3 and supports modern scheduling, and updated import paths.

Getting help

Having trouble? We'd like to help!

• Report bugs, questions and feature requests in our ticket tracker.

Contributing

DAG Factory is an Open-Source project. Learn about its development process and about how you can contribute:

• Contributing to DAG Factory
• Github repository

License

To learn more about the terms and conditions for use, reproduction and distribution, read the Apache License 2.0.

Privacy Notice

This project follows Astronomer's Privacy Policy.

For further information, read this

Security Policy

Check the project's Security Policy to learn how to report security vulnerabilities in DAG Factory and how security issues reported to the DAG Factory security team are handled.