setting-up-astro-project

par astronomer

Initialiser et configurer des projets Astro/Airflow avec dépendances, connexions et mise en place de l'environnement. Génère la structure complète du projet avec astro dev init , incluant les répertoires pour les DAGs, plugins, tests et fichiers de configuration. Gère les dépendances Python et système via requirements.txt et packages.txt , avec prise en charge de Dockerfile personnalisé pour les configurations complexes. Configure les connexions, variables et pools de manière déclarative dans airflow_settings.yaml , avec des commandes d'exportation/importation pour l'environnement...

npx skills add https://github.com/astronomer/agents --skill setting-up-astro-project

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Astro Project Setup

This skill helps you initialize and configure Airflow projects using the Astro CLI.

To run the local environment, see the managing-astro-local-env skill. To write DAGs, see the authoring-dags skill. Open-source alternative: If the user isn't on Astro, guide them to Apache Airflow's Docker Compose quickstart for local dev and the Helm chart for production. For deployment strategies, use the deploying-airflow skill.

Initialize a New Project

astro dev init

Don't pass --airflow-version or --runtime-version unless the user explicitly asks for a specific pin. Plain astro dev init resolves to the latest Astro Runtime — that's the right default. Specifying a version risks pinning to a stale value from training data. If the user wants to know what was installed, read the generated Dockerfile afterward instead of guessing.

Creates this structure:

project/
├── dags/                # DAG files
├── include/             # SQL, configs, supporting files
├── plugins/             # Custom Airflow plugins
├── tests/               # Unit tests
├── Dockerfile           # Image customization
├── packages.txt         # OS-level packages
├── requirements.txt     # Python packages
└── airflow_settings.yaml # Connections, variables, pools

Adding Dependencies

Python Packages (requirements.txt)

apache-airflow-providers-snowflake==5.3.0
pandas==2.1.0
requests>=2.28.0

OS Packages (packages.txt)

gcc
libpq-dev

Custom Dockerfile

For complex setups (private PyPI, custom scripts):

FROM quay.io/astronomer/astro-runtime:12.4.0

RUN pip install --extra-index-url https://pypi.example.com/simple my-package

After modifying dependencies: Run astro dev restart

Configuring Connections & Variables

airflow_settings.yaml

Loaded automatically on environment start:

airflow:
  connections:
    - conn_id: my_postgres
      conn_type: postgres
      host: host.docker.internal
      port: 5432
      login: user
      password: pass
      schema: mydb

  variables:
    - variable_name: env
      variable_value: dev

  pools:
    - pool_name: limited_pool
      pool_slot: 5

Export/Import

# Export from running environment
astro dev object export --connections --file connections.yaml

# Import to environment
astro dev object import --connections --file connections.yaml

Validate Before Running

Parse DAGs to catch errors without starting the full environment:

astro dev parse

Related Skills

managing-astro-local-env: Start, stop, and troubleshoot the local environment
authoring-dags: Write and validate DAGs (uses MCP tools)
testing-dags: Test DAGs (uses MCP tools)
deploying-airflow: Deploy DAGs to production (Astro, Docker Compose, Kubernetes)