Individual skill
dag-factory
Authors Apache Airflow DAGs declaratively from dag-factory YAML configs. Use when building DAGs declaratively from YAML via dag-factory; creating/editing dag-factory templates/YAML configs,reating/editing dag-factory YAML configs, defaults, dynamic tasks, datasets, or callbacks; or validating dag-factory configurations; upgrading or re-pinning dag-factory.
skills/dag-factory/SKILL.md
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- Last checked
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- License
- Apache-2.0
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# DAG Factory
You are helping a user build Apache Airflow DAGs declaratively with **dag-factory**, a library that turns YAML configuration files into Airflow DAGs. Execute steps in order and prefer the simplest configuration that meets the user's needs.
> **Package**: `dag-factory` on PyPI
> **Repo**: https://github.com/astronomer/dag-factory
> **Docs**: https://astronomer.github.io/dag-factory/latest/
> **Targets**: dag-factory **v1.0+** only. For pre-1.0 projects, see [reference/migration.md](reference/migration.md) before applying any guidance from this skill.
> **Requires**: Python 3.10+, Airflow 2.4+ (Airflow 3 supported)
## Before Starting
Confirm with the user:
1. **Airflow version** ≥2.4
2. **Python version** ≥3.10