python

khalido's avatarfrom khalido

Python development preferences. Use when writing Python code, CLI tools, APIs, or scripts.

⭐0stars🔀0forks📁View on GitHub🕐Updated Jan 9, 2026
[Code Generation]

When & Why to Use This Skill

This Claude skill streamlines Python development by enforcing modern best practices and a curated high-performance toolset. It focuses on writing readable, concise, and type-hinted code using industry-leading libraries like FastAPI, Polars, and SQLModel, while leveraging the `uv` package manager for lightning-fast dependency management and project initialization.

Use Cases

  • Rapidly bootstrapping new Python projects with standardized configurations using `uv` and `ruff` for linting and formatting.
  • Developing robust and interactive CLI tools using `typer` and `rich` for professional terminal outputs.
  • Building scalable, production-ready Web APIs and backend services with FastAPI, Pydantic, and SQLModel.
  • Implementing clean and maintainable data processing pipelines using Polars and explicit Python type hints.
  • Integrating directly with Google Workspace APIs (Sheets, etc.) using official SDKs and modern authentication patterns.
  • Setting up local development environments with automated testing via `pytest` and secure tunneling via Cloudflare.
namepython
descriptionPython development preferences. Use when writing Python code, CLI tools, APIs, or scripts.

Python Development

Philosophy

Readable, concise code. Function names and type hints should make purpose clear without verbose docstrings.

Tooling

  • Package manager: uv - new projects: uv init --python 3.14
  • Linting/formatting: ruff
  • Testing: pytest
  • Logging: loguru

Preferred Libraries

Purpose Library
CLI tools typer
CLI output rich (when needed)
HTTP clients httpx
Web APIs fastapi + uvicorn
DataFrames polars
ORM sqlmodel (Pydantic + SQLAlchemy)

Code Style

  • Type hints on function signatures
  • Small, focused functions
  • pathlib for paths
  • dataclasses or Pydantic for structured data
  • SQLite for prototyping, Postgres for prod

Docstrings

Minimal but useful. Skip verbose Google/NumPy style. Answer: "what does this return in practice?"

def fetch_weather(city: str) -> dict[str, float]:
    """Get current weather from OpenWeatherMap API.

    Returns {"temp": 24.5, "humidity": 65.0, "wind_speed": 12.3}
    """

Include: what it does (if name isn't obvious), what's actually returned (not just the type), optional example for complex functions.

Google APIs

Use Google SDKs directly (gspread and similar wrappers are outdated/unmaintained).

uv add google-api-python-client google-auth-httplib2 google-auth-oauthlib

Refs: Sheets quickstart, reading values

Local Testing

Expose local servers via Cloudflare tunnel:

cloudflared tunnel --url http://localhost:8000

Deployment

Railway for FastAPI projects. Volumes required for persistent files (SQLite db, credentials.json).

Ref: Railway LLM docs