What is the recommended testing strategy?

The skill advocates for a minimum of 80% test coverage using pytest, utilizing fixtures, markers, and coverage reports to maintain high code quality.

What makes this Python skill 'modern'?

It utilizes the latest high-performance tools like uv (a Rust-based package manager) and ruff (the fastest linter available), alongside Python 3.13 and the Model Context Protocol (MCP).

Can I use this for non-web projects?

Yes. While it includes specific guides for FastAPI, the core toolset (uv, ruff, mypy) and project structures are suitable for any modern Python application or library.

How does it handle dependency management?

It leverages uv for lightning-fast installs and locked dependencies via pyproject.toml, ensuring reproducible environments across development, CI, and production.

Is it compatible with containerized environments?

Absolutely. It provides specific patterns for multi-stage Docker builds that optimize image size and security by effectively managing virtual environments.

Modern Python Development

Name: Modern Python Development
Author: sumik5

bysumik5

Desarrollo de API

Standardizes Python projects using a high-performance toolchain including uv, ruff, and FastAPI for type-safe and scalable applications.

Acerca de

This skill provides a comprehensive blueprint for modern Python 3.13+ development, integrating a high-performance Rust-based toolchain with industry-standard practices. It guides users through project structuring, FastAPI and FastMCP implementation, rigorous static type checking with mypy, and optimized Docker containerization. Designed for developers who prioritize speed and reliability, it ensures a consistent and maintainable codebase through automated linting, formatting, and a strict testing strategy targeting 80% coverage.

Características Principales

Standardized project layouts for src-based packages and FastAPI apps
High-speed dependency management and project initialization using uv
Advanced testing workflows with pytest aiming for 80%+ code coverage
Automated linting and formatting with ruff and static type analysis with mypy
Optimized multi-stage Docker configurations for cloud-native deployment
0 GitHub stars

Casos de Uso

Bootstrapping new production-grade Python projects with modern 3.13+ standards
Developing high-performance MCP servers using FastMCP and FastAPI
Modernizing existing Python workflows with faster CI/CD and stricter type safety

Acerca de

Características Principales

Standardized project layouts for src-based packages and FastAPI apps
High-speed dependency management and project initialization using uv
Advanced testing workflows with pytest aiming for 80%+ code coverage
Automated linting and formatting with ruff and static type analysis with mypy
Optimized multi-stage Docker configurations for cloud-native deployment
0 GitHub stars

Casos de Uso

Bootstrapping new production-grade Python projects with modern 3.13+ standards
Developing high-performance MCP servers using FastMCP and FastAPI
Modernizing existing Python workflows with faster CI/CD and stricter type safety