uv-package-manager

Manage Python dependencies and virtual environments with uv.

6|Updated Feb 25, 2026
One-click install
npx skills add https://github.com/archibate/archibate-skills --skill uv-package-manager-archibate
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: uv-package-manager
Source: https://github.com/archibate/archibate-skills/tree/main/old-skills/trash-skills/uv-package-manager
Command: npx skills add https://github.com/archibate/archibate-skills --skill uv-package-manager-archibate

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Eliminates slow, inconsistent Python package installation and fragile virtual environment workflows by providing a fast installer, reliable resolver, and reproducible lockfile-driven installs to reduce developer friction and CI runtime.

Core Features & Use Cases

  • Ultra-fast installs and resolution: Rust-based installer that dramatically reduces install time compared to pip and poetry.
  • Environment and Python version management: Create and pin virtual environments and Python interpreters per-project for reproducibility.
  • Lockfile and CI-friendly workflows: Generate uv.lock, perform frozen installs in CI, and optimize Docker builds for minimal layers and cache reuse.
  • Migration and monorepo support: Migrate from requirements.txt, pip-tools, or poetry and manage workspace members in monorepos.
  • Use Case: Speed up a test suite in CI by installing exact versions from uv.lock and reusing the global cache to cut build time significantly.

Quick Start

Initialize a new project with uv by running uv init my-project then pin the Python version with uv python pin 3.12 add your dependencies with uv add requests numpy and create the virtual environment with uv venv.

Frequently Asked Questions about uv-package-manager

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

FAQPage Schema
How do I speed up Python dependency installation in CI pipelines?

Speed up Python dependency installation in CI pipelines by using a Rust-based resolver to generate lockfiles and perform frozen installs. This enables reproducible, deterministic builds while reusing the global cache to significantly cut runtime.

What is the best way to migrate from pip or poetry to a faster Python package manager?

Migrate from pip or poetry to a faster Python package manager by transitioning your existing requirements.txt or lockfiles. The tool provides high-performance resolution and environment management to reduce developer friction and speed up local workflows.

Can I manage multiple package workspaces in a Python monorepo with uv?

Yes, you can manage multiple package workspaces in a Python monorepo. The tool supports managing workspace members and pinning specific Python interpreters per project to ensure reproducible virtual environments across different packages.

How do I create a reproducible virtual environment and pin a specific Python version?

Create a reproducible virtual environment and pin a Python version by initializing the project and specifying the interpreter. This manages virtual environments and Python versions per-project, ensuring consistent setups for local development and Dockerized builds.

Does uv support offline installations and cache reuse for Docker builds?

Yes, uv supports offline installations and cache reuse for Docker builds. It optimizes build layers and leverages a global cache to provide frozen, deterministic installs even without a continuous network connection.