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Run npx skillmds@latest add majiayu000/setting-up-astro-project in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Setting Up Astro Project free to use?

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Who published Setting Up Astro Project?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Setting Up Astro Project by majiayu000

Name: Setting Up Astro Project
Rating: 4.2 (5 reviews)
Author: majiayu000

Setting Up Astro Project

Initialize and configure Astro/Airflow projects. Use when the user wants to create a new project, set up dependencies, configure connections/variables, or understand project structure. For running the local environment, see managing-astro-local-env.

majiayu000 Updated Sep 21, 2026 567 repo stars

File contents

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

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)

---name: setting-up-astro-projectdescription: Initialize and configure Astro/Airflow projects. Use when the user wants to create a new project, set up dependencies, configure connections/variables, or understand project structure. For running the local environment, see managing-astro-local-env.---# Astro Project SetupThis 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```bashastro dev init```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==5.3.0pandas==2.1.0requests>=2.28.0```### OS Packages (packages.txt)```gcclibpq-dev```### Custom DockerfileFor complex setups (private PyPI, custom scripts):```dockerfileFROM quay.io/astronomer/astro-runtime:12.4.0RUN pip install --extra-index-url https://pypi.example.com/simple my-package```**After modifying dependencies:** Run `astro dev restart`---## Configuring Connections & Variables### airflow_settings.yamlLoaded automatically on environment start:```yamlairflow: 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```bash# Export from running environmentastro dev object export --connections --file connections.yaml# Import to environmentastro dev object import --connections --file connections.yaml```---## Validate Before RunningParse DAGs to catch errors without starting the full environment:```bashastro 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)

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