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uv-package-manager

wshobson/agents

Ultra-fast Python package manager and virtual environment tool—10-100x faster than pip with built-in dependency resolution and Python version management.

What is uv-package-manager?

uv is a Rust-based package installer and project manager that replaces pip, pip-tools, and poetry for modern Python workflows. Use it to set up projects, manage dependencies, create virtual environments, and speed up CI/CD pipelines with minimal configuration.

  • Install packages 10-100x faster than pip with advanced dependency resolution
  • Create and manage Python virtual environments without requiring Python pre-installed
  • Download and manage multiple Python versions across projects
  • Generate and maintain lockfiles for reproducible builds
  • Drop-in replacement for pip with compatible commands and workflows
  • Manage dev dependencies, optional dependency groups, and git-based packages

How to install uv-package-manager

npx skills add https://github.com/wshobson/agents --skill uv-package-manager
Prerequisites
  • No Python installation required (uv installs itself)
  • curl or PowerShell for initial installation
  • For git-based packages: git installed and configured
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How to use uv-package-manager

  1. 1.Install uv using curl, PowerShell, Homebrew, or pip
  2. 2.Run `uv init my-project` to create a new project with pyproject.toml and virtual environment
  3. 3.Use `uv add package-name` to add dependencies (automatically creates venv if needed)
  4. 4.Run scripts with `uv run python script.py` to auto-activate the virtual environment
  5. 5.Use `uv lock` to generate a lockfile for reproducible installations across environments
  6. 6.Pin Python versions with `uv python pin 3.12` to ensure team consistency

Use cases

Good for
  • Setting up new Python projects with automatic venv creation and dependency installation
  • Migrating existing pip/poetry/pip-tools projects to faster dependency management
  • Optimizing Docker builds by caching dependencies more efficiently
  • Managing monorepo Python projects with shared and isolated dependencies
  • Resolving complex dependency conflicts faster than traditional tools
Who it's for
  • Python developers optimizing local development speed
  • DevOps engineers reducing CI/CD pipeline duration
  • Teams migrating from pip, poetry, or pip-tools
  • Data scientists managing complex dependency environments
  • Open-source maintainers seeking faster contributor onboarding

uv-package-manager FAQ

How is uv different from pip?

uv is 10-100x faster, written in Rust, includes built-in virtual environment and Python version management, and has a better dependency resolver. It's a drop-in replacement that works with existing pip workflows.

Do I need Python installed to use uv?

No. uv is self-contained and can install Python versions for you. You can install uv via curl, PowerShell, Homebrew, or pip if you already have Python.

Can I use uv with existing projects?

Yes. Run `uv sync` on projects with pyproject.toml, or `uv add -r requirements.txt` to migrate from requirements files. uv is compatible with pip, poetry, and pip-tools workflows.

What does `uv run` do?

It automatically activates the project's virtual environment and runs a command without requiring manual activation. Useful for scripts, tools, and CI/CD where you want to avoid shell-specific activation steps.

How do I lock dependencies for reproducible builds?

Run `uv lock` to generate a uv.lock file that pins all transitive dependencies. Commit this file to version control and use `uv sync` to install exact versions across environments.

Full instructions (SKILL.md)

Source of truth, from wshobson/agents.


name: uv-package-manager description: Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows. Use when setting up Python projects, managing dependencies, or optimizing Python development workflows with uv.

UV Package Manager

Comprehensive guide to using uv, an extremely fast Python package installer and resolver written in Rust, for modern Python project management and dependency workflows.

When to Use This Skill

  • Setting up new Python projects quickly
  • Managing Python dependencies faster than pip
  • Creating and managing virtual environments
  • Installing Python interpreters
  • Resolving dependency conflicts efficiently
  • Migrating from pip/pip-tools/poetry
  • Speeding up CI/CD pipelines
  • Managing monorepo Python projects
  • Working with lockfiles for reproducible builds
  • Optimizing Docker builds with Python dependencies

Core Concepts

1. What is uv?

  • Ultra-fast package installer: 10-100x faster than pip
  • Written in Rust: Leverages Rust's performance
  • Drop-in pip replacement: Compatible with pip workflows
  • Virtual environment manager: Create and manage venvs
  • Python installer: Download and manage Python versions
  • Resolver: Advanced dependency resolution
  • Lockfile support: Reproducible installations

2. Key Features

  • Blazing fast installation speeds
  • Disk space efficient with global cache
  • Compatible with pip, pip-tools, poetry
  • Comprehensive dependency resolution
  • Cross-platform support (Linux, macOS, Windows)
  • No Python required for installation
  • Built-in virtual environment support

3. UV vs Traditional Tools

  • vs pip: 10-100x faster, better resolver
  • vs pip-tools: Faster, simpler, better UX
  • vs poetry: Faster, less opinionated, lighter
  • vs conda: Faster, Python-focused

Installation

Quick Install

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

# Using pip (if you already have Python)
pip install uv

# Using Homebrew (macOS)
brew install uv

# Using cargo (if you have Rust)
cargo install --git https://github.com/astral-sh/uv uv

Verify Installation

uv --version
# uv 0.x.x

Quick Start

Create a New Project

# Create new project with virtual environment
uv init my-project
cd my-project

# Or create in current directory
uv init .

# Initialize creates:
# - .python-version (Python version)
# - pyproject.toml (project config)
# - README.md
# - .gitignore

Install Dependencies

# Install packages (creates venv if needed)
uv add requests pandas

# Install dev dependencies
uv add --dev pytest black ruff

# Install from requirements.txt
uv pip install -r requirements.txt

# Install from pyproject.toml
uv sync

Virtual Environment Management

Pattern 1: Creating Virtual Environments

# Create virtual environment with uv
uv venv

# Create with specific Python version
uv venv --python 3.12

# Create with custom name
uv venv my-env

# Create with system site packages
uv venv --system-site-packages

# Specify location
uv venv /path/to/venv

Pattern 2: Activating Virtual Environments

# Linux/macOS
source .venv/bin/activate

# Windows (Command Prompt)
.venv\Scripts\activate.bat

# Windows (PowerShell)
.venv\Scripts\Activate.ps1

# Or use uv run (no activation needed)
uv run python script.py
uv run pytest

Pattern 3: Using uv run

# Run Python script (auto-activates venv)
uv run python app.py

# Run installed CLI tool
uv run black .
uv run pytest

# Run with specific Python version
uv run --python 3.11 python script.py

# Pass arguments
uv run python script.py --arg value

Package Management

Pattern 4: Adding Dependencies

# Add package (adds to pyproject.toml)
uv add requests

# Add with version constraint
uv add "django>=4.0,<5.0"

# Add multiple packages
uv add numpy pandas matplotlib

# Add dev dependency
uv add --dev pytest pytest-cov

# Add optional dependency group
uv add --optional docs sphinx

# Add from git
uv add git+https://github.com/user/repo.git

# Add from git with specific ref
uv add git+https://github.com/user/repo.git@v1.0.0

# Add from local path
uv add ./local-package

# Add editable local package
uv add -e ./local-package

Pattern 5: Removing Dependencies

# Remove package
uv remove requests

# Remove dev dependency
uv remove --dev pytest

# Remove multiple packages
uv remove numpy pandas matplotlib

Pattern 6: Upgrading Dependencies

# Upgrade specific package
uv add --upgrade requests

# Upgrade all packages
uv sync --upgrade

# Upgrade package to latest
uv add --upgrade requests

# Show what would be upgraded
uv tree --outdated

Pattern 7: Locking Dependencies

# Generate uv.lock file
uv lock

# Update lock file
uv lock --upgrade

# Lock without installing
uv lock --no-install

# Lock specific package
uv lock --upgrade-package requests

Python Version Management

Pattern 8: Installing Python Versions

# Install Python version
uv python install 3.12

# Install multiple versions
uv python install 3.11 3.12 3.13

# Install latest version
uv python install

# List installed versions
uv python list

# Find available versions
uv python list --all-versions

Pattern 9: Setting Python Version

# Set Python version for project
uv python pin 3.12

# This creates/updates .python-version file

# Use specific Python version for command
uv --python 3.11 run python script.py

# Create venv with specific version
uv venv --python 3.12

Project Configuration

Pattern 10: pyproject.toml with uv

[project]
name = "my-project"
version = "0.1.0"
description = "My awesome project"
readme = "README.md"
requires-python = ">=3.8"
dependencies = [
    "requests>=2.31.0",
    "pydantic>=2.0.0",
    "click>=8.1.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.4.0",
    "pytest-cov>=4.1.0",
    "black>=23.0.0",
    "ruff>=0.1.0",
    "mypy>=1.5.0",
]
docs = [
    "sphinx>=7.0.0",
    "sphinx-rtd-theme>=1.3.0",
]

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[tool.uv]
dev-dependencies = [
    # Additional dev dependencies managed by uv
]

[tool.uv.sources]
# Custom package sources
my-package = { git = "https://github.com/user/repo.git" }

Pattern 11: Using uv with Existing Projects

# Migrate from requirements.txt
uv add -r requirements.txt

# Migrate from poetry
# Already have pyproject.toml, just use:
uv sync

# Export to requirements.txt
uv pip freeze > requirements.txt

# Export with hashes
uv pip freeze --require-hashes > requirements.txt

For advanced workflows including Docker integration, lockfile management, performance optimization, tool comparison, common workflows, tool integration, troubleshooting, best practices, migration guides, and command reference, see references/advanced-patterns.md