Can I use Python Pro with an existing project?

Yes, Python Pro is designed to be used proactively on existing projects. It can help migrate your project to a src layout, configure pyproject.toml correctly, and introduce strict linting rules.

How does Python Pro handle type checking for older libraries?

The skill utilizes strict pyright configurations, employing strategies like explicit Any annotations for untyped stubs and TYPE_CHECKING blocks to prevent circular imports while maintaining code clarity.

What version of Python does Python Pro support?

Python Pro is specifically optimized for Python 3.12 and newer to take full advantage of the latest language features, performance improvements, and type-hinting capabilities.

Why does this skill prioritize uv over pip?

uv is 10-100x faster than pip and provides built-in lockfile support, ensuring that your development environment is fully reproducible across different machines and CI/CD pipelines.

Python Pro

Name: Python Pro
Author: rbergman

byrbergman

•

Desarrollo de API

Implements senior-level Python engineering standards using modern tooling, strict type safety, and production-grade design patterns.

Acerca de

Python Pro transforms Claude into a senior Python architect, ensuring every project adheres to modern industry standards. It proactively applies best practices for package management with uv, strict type checking with pyright, and high-performance linting with ruff. Whether you are initializing a new project with a src layout, implementing complex async patterns, or enforcing strict QA via just workflows, this skill ensures your codebase is maintainable, type-safe, and idiomatic for Python 3.12+ environments.

Características Principales

Modern package management and lockfile reproducibility using uv
Production-ready templates for structured logging, async patterns, and testing
Standardized developer workflows using just and mise for version control
1 GitHub stars
Strict type safety enforcement with pyright and PEP 484/585/604
High-performance linting and formatting via ruff integration

Casos de Uso

Automating complex build, test, and linting pipelines for professional dev teams
Bootstrapping new production-ready Python projects with idiomatic src layouts
Refactoring legacy code to meet modern standards for type safety and clean architecture

Acerca de

Características Principales

Modern package management and lockfile reproducibility using uv
Production-ready templates for structured logging, async patterns, and testing
Standardized developer workflows using just and mise for version control
1 GitHub stars
Strict type safety enforcement with pyright and PEP 484/585/604
High-performance linting and formatting via ruff integration

Casos de Uso

Automating complex build, test, and linting pipelines for professional dev teams
Bootstrapping new production-ready Python projects with idiomatic src layouts
Refactoring legacy code to meet modern standards for type safety and clean architecture