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.

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)