Uv Package Manager

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.

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,=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](references/advanced-patterns.md)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Jartan-LLC
• Source: Jartan-LLC/grimoire
• License: MIT

Install and usage instructions live in the source repository linked above.