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