Airflow
A comprehensive skill catalog for AI agents
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Apache Airflow workflow orchestration. Use for data pipelines.
SKILL.md
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Airflow
Apache Airflow is the standard for data engineering pipelines. v3.0 (2025) introduces Event-driven Triggers and a modern React UI.
When to Use
- ETL/ELT: Scheduling nightly data warehouse loads.
- ML Ops: Retraining models when new data arrives.
- Dependency Management: "Run Task B only if Task A succeeds".
Core Concepts
DAGs (Directed Acyclic Graphs)
Defined in Python.
Task SDK
New in v3.0. Allows writing tasks in any language, not just Python.
Edge Executor
Run tasks on remote edge devices.
Best Practices (2025)
Do:
- Use the TaskFlow API:
@taskdecorators are cleaner thanPythonOperator. - Use Datasets: Define data-aware scheduling (
schedule=[Dataset("s3://bucket/file")]).
Don't:
- Don't put top-level code in DAG files: It runs every scheduler heartbeat.