| name | python-development |
| description | Build and review Python services, scripts, data tools, and automation. Use for FastAPI, data processing, packaging, typing, tests, notebooks, and production scripts. |
Python Development
Purpose
Support Python work with clear environment management, typed boundaries, reliable tests, and maintainable data handling.
Workflow
- Identify Python version, package manager, lockfile, framework, and execution target.
- Keep IO, parsing, validation, and business logic separated.
- Use type hints and runtime validation where data crosses trust boundaries.
- Make scripts idempotent and safe to rerun.
- Verify with tests, type checks, linting, or targeted sample data.
Checklist
- Virtual environments, lockfiles, and dependency pinning.
- FastAPI/Pydantic request and response models.
- Pandas memory use, dtype handling, timezone handling, and missing values.
- Async vs sync IO, connection pooling, and cancellation.
- Logging, error handling, CLI ergonomics, and configuration.
Output
Return:
- Behavior summary.
- Data/schema assumptions.
- Verification commands.
- Operational notes.
