| name | python |
| description | Build maintainable Python backend and service code with strong typing, safe error handling, clean module boundaries, and testable workflows. Use for FastAPI services, data pipelines, and integration-heavy Python changes. |
Python Skill
Use this skill for Python backend, service, and pipeline work.
When to apply
- FastAPI endpoint design and request/response contracts
- Service-layer refactors and orchestration logic
- Error handling and reliability hardening
- Data processing and integration workflows
- Type-driven cleanup and maintainability improvements
Workflow
- Start from contracts.
- Define input/output schemas first.
- Keep transport models separate from business logic.
- Keep modules focused.
- API routes: auth + validation + response mapping.
- Service layer: orchestration and domain rules.
- Data layer: storage/query concerns only.
- Make failure modes explicit.
- Convert exceptions into actionable error responses.
- Add fallback behavior for external/model failures where needed.
- Type and document critical paths.
- Add precise type hints on function boundaries.
- Keep complex behavior in small named functions.
- Keep side effects controlled.
- Centralize environment/config access.
- Avoid hidden globals unless lifecycle is explicit.
- Validate before ship.
- Run target tests/build checks.
- Confirm no regressions in endpoint contracts.
Patterns to prefer
- Pydantic models for API boundaries
- Service wrappers for orchestration flows
- Idempotent startup/init routines
- Structured logging around integration boundaries
Anti-patterns
- Endpoint handlers with embedded business logic
- Catch-all exceptions that hide root causes
- Implicit type conversions at runtime boundaries
- Global mutable state without init discipline
Validation checklist
- Endpoint contracts match actual responses
- Error paths return stable HTTP semantics
- State/init code is deterministic on restart
- Core functions are typed and reviewable
