python-development

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

1. Identify Python version, package manager, lockfile, framework, and execution target.
2. Keep IO, parsing, validation, and business logic separated.
3. Use type hints and runtime validation where data crosses trust boundaries.
4. Make scripts idempotent and safe to rerun.
5. 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.