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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.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Map downstream lineage and blast radius for Airflow data assets. Use when the user needs to know which DAGs, tables, dashboards, or models depend on a dataset and what could break after a change.
Use when the user needs human-in-the-loop workflows in Airflow (approval/reject, form input, or human-driven branching). Covers ApprovalOperator, HITLOperator, HITLBranchOperator, HITLEntryOperator. Requires Airflow 3.1+.
Manages Apache Airflow operations including listing, running, and debugging DAGs, viewing logs, and checking server status using the VS Code extension tools.
Annotate Airflow tasks with data lineage using inlets and outlets. Use when the user wants to add lineage metadata to tasks, specify input/output datasets, or enable lineage tracking for operators without built-in OpenLineage extraction.
Workflow and best practices for writing Apache Airflow DAGs. Use when the user wants to create a new DAG, write pipeline code, or asks about DAG patterns and conventions. For testing and debugging DAGs, see the testing-dags skill.
Create custom OpenLineage extractors for Airflow operators. Use when the user needs lineage from unsupported or third-party operators, wants column-level lineage, or needs complex extraction logic beyond what inlets/outlets provide.
| name | setting-up-astro-project |
| description | 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. |
This skill helps initialize and configure Airflow projects using the Astro CLI.
Note: These are external CLI actions. For runtime inspection inside the VS Code extension, use the extension tools.
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
apache-airflow-providers-snowflake==5.3.0
pandas==2.1.0
requests>=2.28.0
gcc
libpq-dev
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.
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 from running environment
astro dev object export --connections --file connections.yaml
# Import to environment
astro dev object import --connections --file connections.yaml
Parse DAGs to catch errors without starting the full environment:
astro dev parse