Guides and automates the migration of Apache Airflow 2.x DAGs and custom components to Airflow 3.x standards.
This skill facilitates the transition from Apache Airflow 2.x to 3.x by identifying breaking changes, refactoring legacy imports, and updating code to align with the new Airflow 3 architecture. It leverages Ruff migration rules for automated fixes and provides a comprehensive checklist for manual refactoring, such as replacing direct metadata database access with the Airflow Task Execution API and updating deprecated context variables. Ideal for data engineers looking to modernize their workflows while ensuring compatibility with Airflow 3’s decoupled scheduler and worker architecture.
Key Features
01Guidance on migrating Datasets to the new Asset-based system
02Identification and remediation of direct metadata database access issues
03Automated code refactoring using Ruff migration rules (AIR30/AIR31)
04Update mapping for legacy operators, hooks, and provider imports
05Verification of Airflow context keys and scheduling logic changes
0677 GitHub stars
Use Cases
01Upgrading legacy Airflow 2.x DAG repositories to the latest Airflow 3.x standard
02Refactoring codebase to eliminate deprecated imports and ensure future-proof data workflows
03Modernizing custom operators to use the new Task Execution API instead of ORM sessions
