Does uv handle Python version installation?

Yes, uv includes built-in Python management capabilities, allowing you to install and pin specific Python versions for your projects without external tools like pyenv.

Is uv suitable for production Docker builds?

Absolutely. This skill includes specific patterns for multi-stage Docker builds that use uv to create small, efficient production images with fast layer caching.

Can I use uv with existing Poetry or pip-tools projects?

Yes, uv is designed to be compatible with pyproject.toml and can seamlessly migrate or sync dependencies from legacy tools like Poetry and pip-tools.

How much faster is uv compared to pip?

uv is typically 10 to 100 times faster than pip, utilizing Rust-based performance for extremely efficient dependency resolution and parallel installation.

UV Python Package Manager

Name: UV Python Package Manager
Author: HermeticOrmus

byHermeticOrmus

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Developer Tools

Streamlines Python development using the ultra-fast uv tool for high-performance dependency management and environment orchestration.

About

This skill empowers Claude to master 'uv', a blazing-fast Python package installer and resolver written in Rust. It provides comprehensive guidance on managing Python versions, creating virtual environments, and resolving complex dependencies at speeds 10-100x faster than traditional tools like pip. By implementing modern project workflows, lockfile management, and optimized Docker patterns, this skill helps developers move away from slower legacy tools while ensuring reproducible and efficient builds across local development and CI/CD environments.

Key Features

Reproducible builds via robust lockfile (uv.lock) support
2 GitHub stars
Ultra-fast dependency resolution and installation (10-100x faster than pip)
Seamless migration paths from pip, pip-tools, and Poetry
Unified management of Python interpreters and virtual environments
Optimized integration patterns for CI/CD pipelines and Docker containers

Use Cases

Managing complex monorepos with shared Python workspaces
Accelerating local Python project setup and dependency installation
Reducing build times in automated deployment and testing pipelines

About

Key Features

Reproducible builds via robust lockfile (uv.lock) support
2 GitHub stars
Ultra-fast dependency resolution and installation (10-100x faster than pip)
Seamless migration paths from pip, pip-tools, and Poetry
Unified management of Python interpreters and virtual environments
Optimized integration patterns for CI/CD pipelines and Docker containers

Use Cases

Managing complex monorepos with shared Python workspaces
Accelerating local Python project setup and dependency installation
Reducing build times in automated deployment and testing pipelines