airflowlisted

# Apache Airflow with Astronomer CLI Use `astro` for local Apache Airflow development, DAG authoring, task testing, and debugging. [python-stack](../python-stack/SKILL.md) owns Python package conventions and [docker](../docker/SKILL.md) manages container runtimes. Local runs need an existing Docker-compatible engine and 20 GiB disk headroom; workstation tools disable anonymous telemetry (`ASTRO_TELEMETRY_DISABLED=1`). Inspect the project's Airflow version before choosing service flags (`--api-server` for Airflow 3; `--webserver` for Airflow 2). ## Workflow 1. **Inspect project layout**: confirm existing `dags/`, `Dockerfile`, `requirements.txt`, and `airflow_settings.yaml`. ```bash ls -la dags/ ``` 1. **Start local environment**: spin up local scheduler, webserver, triggerer, and PostgreSQL database. ```bash astro dev start ``` 1. **Validate DAG syntax and integrity**: parse DAG files to catch import and configuration errors without waiting for the scheduler. ```bash astro dev parse ``` 1. **Test tasks and runs**: execute unit tests or run individual tasks directly inside the local environment. ```bash astro dev pytest astro dev run tasks test <dag_id> <task_id> ``` 1. **Inspect service and task logs**: follow logs to diagnose scheduling delays or task failures. ```bash astro dev logs --scheduler astro dev logs --api-server ``` 1. **Stop or rebuild environment**: stop containers when done or rebuild when changin