Which Python version does this skill prioritize?

The skill is optimized for Python 3.13, ensuring access to the latest language features and performance improvements.

What is the recommended package manager?

This skill defaults to uv, a high-performance Python package manager written in Rust, for faster installs and reliable lockfiles.

How does this skill handle code quality?

It integrates Ruff for lightning-fast linting and formatting, alongside Mypy for strict static type checking to prevent runtime errors.

Does it support Model Context Protocol (MCP) development?

Yes, it includes specific implementation guides and patterns for FastMCP (version 2.12+) to build extensible AI tools.

Modern Python Development

Name: Modern Python Development
Author: sumik5

bysumik5

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API Development

Standardizes Python project lifecycles using uv, FastAPI, and enterprise-grade testing and deployment patterns.

About

This skill provides a comprehensive framework for developing modern, production-ready Python applications. It enforces the use of high-performance tools like uv for dependency management, Ruff for linting, and Mypy for strict type safety. By integrating best practices for FastAPI and FastMCP, it helps developers build scalable web services and Model Context Protocol servers. The skill also guides users through achieving 80%+ test coverage with pytest and creating optimized, multi-stage Docker configurations for cloud-ready deployments.

Key Features

High-speed dependency management and environment setup using uv
Comprehensive testing strategies including async support and coverage targets
Optimized multi-stage Docker builds for minimal image size and security
1 GitHub stars
Production-grade FastAPI and FastMCP implementation patterns
Automated linting and formatting standards with Ruff and Mypy

Use Cases

Bootstrapping a new Python 3.13 project with a standardized directory layout
Implementing robust Model Context Protocol (MCP) servers using FastMCP
Containerizing Python applications for scalable deployment on Cloud Run or Kubernetes

About

Key Features

High-speed dependency management and environment setup using uv
Comprehensive testing strategies including async support and coverage targets
Optimized multi-stage Docker builds for minimal image size and security
1 GitHub stars
Production-grade FastAPI and FastMCP implementation patterns
Automated linting and formatting standards with Ruff and Mypy

Use Cases

Bootstrapping a new Python 3.13 project with a standardized directory layout
Implementing robust Model Context Protocol (MCP) servers using FastMCP
Containerizing Python applications for scalable deployment on Cloud Run or Kubernetes