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Apply asyncio patterns for concurrent IO, background work, and coordinated refresh flows in Python analytics services.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Apply layer-specific quality checklists for Python ETL, Airflow DAGs, dbt models, SQL, FastAPI, Vue.js, and Docker Compose changes in the HH data platform.
Inspect git history and diffs to identify what changed, which platform layers are affected, and what risk signals to prioritise before applying review checklists.
Design small, maintainable Airflow DAGs with clear task boundaries, retry policy, and runtime assumptions.
Design dbt source, staging, and mart models with explicit schemas and clear layer responsibilities.
Break down a data-platform request into sequenced work items, dependencies, risks, and definition of done.
Design a reproducible local Docker Compose setup for Airflow, PostgreSQL, and related developer workflows.
| name | asyncio-pipeline-patterns |
| description | Apply asyncio patterns for concurrent IO, background work, and coordinated refresh flows in Python analytics services. |
| license | MIT |
| compatibility | opencode |
| metadata | {"audience":"backend-engineers","domain":"asyncio"} |
