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

安装

macOS/Linux

Windows (PowerShell)

Using pip (if you already have Python)

Using Homebrew (macOS)

Using cargo (if you have Rust)

uv 0.x.x

Create new project with virtual environment

Or create in current directory

Initialize creates:

- .python-version (Python version)

- pyproject.toml (project config)

- README.md

- .gitignore

Install packages (creates venv if needed)

Install dev dependencies

Install from requirements.txt

Install from pyproject.toml

Create virtual environment with uv

Create with specific Python version

Create with custom name

Create with system site packages

Specify location

Linux/macOS

Windows (Command Prompt)

Windows (PowerShell)

Or use uv run (no activation needed)

Run Python script (auto-activates venv)

Run installed CLI tool

Run with specific Python version

Pass arguments

Add package (adds to pyproject.toml)

Add with version constraint

Add multiple packages

Add dev dependency

Add optional dependency group

Add from git

Add from git with specific ref

Add from local path

Add editable local package

Remove package

Remove dev dependency

Remove multiple packages

Upgrade specific package

Upgrade all packages

Upgrade package to latest

Show what would be upgraded

Generate uv.lock file

Update lock file

Lock without installing

Lock specific package

Install Python version

Install multiple versions

Install latest version

List installed versions

Find available versions

Set Python version for project

This creates/updates .python-version file

Use specific Python version for command

Create venv with specific version

Additional dev dependencies managed by uv

Custom package sources

my-package

Migrate from requirements.txt

Migrate from poetry

Already have pyproject.toml, just use:

Export to requirements.txt

Export with hashes