| name | python |
| description | Build, review, and refactor Python backend services. Use for tasks like FastAPI/Flask service setup, API design, request/response schemas, database access (PostgreSQL), migrations, background jobs, observability (logging/metrics/tracing), authentication, configuration, testing, and production hardening. |
python
Use this skill for Python 后端服务开发与评审。
Defaults (unless repo dictates otherwise)
- Framework: FastAPI (preferred) or follow existing
- Python: follow repo’s version; prefer modern typing
- API: JSON over HTTP, explicit schemas
- DB: PostgreSQL; prefer explicit migrations
Service structure (recommended)
app/
main.py (app factory, routers)api/ (routers, request/response models)core/ (config, logging, security)db/ (session/engine, repositories)models/ (ORM models if used)schemas/ (Pydantic models)services/ (business logic)integrations/ (3rd party clients)tests/
Workflow
- Clarify contract
- Endpoints, auth requirements, error model, SLAs.
- Data ownership and persistence requirements.
- API design
- Version paths (
/v1/...) and consistent naming.
- Pydantic schemas: validate on input, shape output explicitly.
- Error responses: stable
code + message + optional details.
- Persistence
- Define schema and migrations (Alembic if used).
- Avoid leaking DB models into API; map to schemas.
- Use indexes for query paths; ensure safe defaults and constraints.
- Security
- Keep secrets in env vars; never in code.
- AuthN/AuthZ: token validation, scopes/roles.
- Input validation, rate limiting (if relevant), safe logging (no PII).
- Observability
- Structured logs with request IDs.
- Metrics for latency, error rate, DB timings; tracing if available.
- Testing
- Unit tests for business logic.
- API tests for endpoints (happy path + errors).
- Deterministic fixtures; avoid flaky time/network dependencies.
Output expectations when making changes
- Prefer small, incremental diffs.
- Update schemas/migrations/tests together.
- Document new env vars and run steps.
