python-coder

Configure Python 3.12+ projects with pyproject.toml and modern tooling.

47|11|Updated Nov 26, 2025
One-click install
npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill python-coder
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python-coder
Source: https://github.com/majesticlabs-dev/majestic-marketplace/tree/main/plugins/majestic-python/skills/python-coder
Command: npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill python-coder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill guides modern Python development using Python 3.12+ features, tooling, and production-ready patterns.

Core Features & Use Cases

  • Modern language features, typing, async patterns, packaging, and testing.
  • Tools like uv, ruff, mypy, pyright, pre-commit, and CI workflows.
  • Guidance on FastAPI, Django, SQLAlchemy, and deployment patterns.

Quick Start

Initialize a Python project with pyproject.toml and start coding with modern tooling support.

Frequently Asked Questions about python-coder

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

FAQPage Schema
How do I set up a modern Python project with type checking and async support?

Modern Python development starts with pyproject.toml configuration and tools like uv for dependency management, mypy or pyright for static type checking, and ruff for linting. Python 3.12+ enables advanced typing and async patterns, supported by this Skill's guidance on project initialization and tooling setup.

Can I use FastAPI with async SQLAlchemy and Pydantic for production APIs?

Yes. FastAPI with async SQLAlchemy and Pydantic validation is a production-grade pattern covered here. This Skill provides guidance on building high-performance web APIs, including async request handling, data validation, and robust testing workflows.

What's the best way to test Python code with pytest in a modern workflow?

Pytest integrates into modern Python workflows through pre-commit hooks and CI automation. This Skill covers testing strategies, static type checking, and code quality enforcement to ensure maintainable, production-ready code alongside FastAPI and async patterns.

How do I package and deploy a Python application securely?

Secure deployment requires packaging standards via pyproject.toml, dependency management with uv, code quality checks via ruff and mypy, and CI workflows. This Skill guides production deployment patterns, performance profiling, and maintenance practices for Python 3.12+ applications.

Does Python 3.12 support the async patterns I need for data processing pipelines?

Python 3.12+ supports advanced async patterns essential for data processing pipelines and asynchronous services. This Skill provides guidance on async/await syntax, typing for concurrent code, and tools like pyright to validate async safety in production workflows.

What tooling do I need for code quality in a Python project?

Code quality requires ruff for linting, mypy or pyright for type checking, and pre-commit hooks for automated checks. This Skill covers integrating these tools into modern Python 3.12+ projects alongside testing and CI workflows for maintainable production code.