python-expert

Guide modern Python development with typing, uv, ruff, and pytest.

Updated Aug 23, 2026

Search Tags:#development #linting #best practices #debugging #python #tooling #coding

Ready to run

npx skills add https://github.com/brunoldqueiroz/marvin --skill python-expert-brunoldqueiroz

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: python-expert
Source: https://github.com/brunoldqueiroz/marvin/tree/main/.claude/skills/python-expert
Command: npx skills add https://github.com/brunoldqueiroz/marvin --skill python-expert-brunoldqueiroz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides expert advice and best practices for writing, reviewing, and debugging Python code, ensuring high-quality, maintainable, and efficient software.

Core Features & Use Cases

Code Quality: Enforces modern Python standards using tools like ruff and mypy.
Toolchain Management: Guides on using uv for dependency management and pytest for testing.
Best Practices: Offers clear guidance on typing, Pydantic, pathlib, and more.
Use Case: Refactor a legacy Python script to adopt modern type hints and use ruff for linting and formatting, significantly improving readability and reducing bugs.

Quick Start

Use the python-expert skill to refactor the provided Python code to use modern type hints and ruff formatting.

Frequently Asked Questions about python-expert

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is the best way to refactor legacy Python code for modern type hints?▼

The best way to refactor legacy Python code involves adopting modern type hints, using `ruff` for automated linting and formatting, and applying `mypy` for strict type checking to improve readability and reduce bugs.

How do I manage Python dependencies and toolchains with uv?▼

You manage Python dependencies and toolchains with `uv` by utilizing its high-speed environment resolution and package installation capabilities, replacing traditional managers to ensure reproducible and efficient project setups.

Does this Python development approach support Python 3.11 features?▼

Yes, this Python development approach supports Python 3.11+ features, focusing on idiomatic code, modern typing standards, and anti-pattern avoidance to ensure high-quality and maintainable software.

How does ruff compare to other Python linting tools?▼

Ruff replaces multiple category-level Python linting tools by combining lightning-fast execution with comprehensive rule coverage, enabling rapid code formatting and linting within a single unified toolchain.

What are common Python anti-patterns to avoid during code reviews?▼

Common Python anti-patterns to avoid during code reviews include outdated string formatting, manual path manipulation instead of using `pathlib`, and ignoring type annotations, which degrade code maintainability.

Why use Pydantic and pytest for Python application testing?▼

You use Pydantic for robust data validation and `pytest` for scalable test execution, ensuring data integrity and comprehensive coverage when validating Python application logic and structural typing.