Uv Package Manager

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.

FluxonLab 0aae372 2 files · 15.4 KB Updated Sep 17, 2026

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UV Package Manager

Vendor skill (source: wshobson-agents). Imported 2026-05-31.

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

---name: uv-package-managerdescription: 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> _Vendor skill (source: wshobson-agents). Imported 2026-05-31._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```bash# macOS/Linuxcurl -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```bashuv --version# uv 0.x.x```## Quick Start### Create a New Project```bash# Create new project with virtual environmentuv init my-projectcd my-project# Or create in current directoryuv init .# Initialize creates:# - .python-version (Python version)# - pyproject.toml (project config)# - README.md# - .gitignore```### Install Dependencies```bash# Install packages (creates venv if needed)uv add requests pandas# Install dev dependenciesuv add --dev pytest black ruff# Install from requirements.txtuv pip install -r requirements.txt# Install from pyproject.tomluv sync```## Virtual Environment Management### Pattern 1: Creating Virtual Environments```bash# Create virtual environment with uvuv venv# Create with specific Python versionuv venv --python 3.12# Create with custom nameuv venv my-env# Create with system site packagesuv venv --system-site-packages# Specify locationuv venv /path/to/venv```### Pattern 2: Activating Virtual Environments```bash# Linux/macOSsource .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.pyuv run pytest```### Pattern 3: Using uv run```bash# Run Python script (auto-activates venv)uv run python app.py# Run installed CLI tooluv run black .uv run pytest# Run with specific Python versionuv run --python 3.11 python script.py# Pass argumentsuv run python script.py --arg value```## Package Management### Pattern 4: Adding Dependencies```bash# Add package (adds to pyproject.toml)uv add requests# Add with version constraintuv add "django>=4.0,<5.0"# Add multiple packagesuv add numpy pandas matplotlib# Add dev dependencyuv add --dev pytest pytest-cov# Add optional dependency groupuv add --optional docs sphinx# Add from gituv add git+https://github.com/user/repo.git# Add from git with specific refuv add git+https://github.com/user/repo.git@v1.0.0# Add from local pathuv add ./local-package# Add editable local packageuv add -e ./local-package```### Pattern 5: Removing Dependencies```bash# Remove packageuv remove requests# Remove dev dependencyuv remove --dev pytest# Remove multiple packagesuv remove numpy pandas matplotlib```### Pattern 6: Upgrading Dependencies```bash# Upgrade specific packageuv add --upgrade requests# Upgrade all packagesuv sync --upgrade# Upgrade package to latestuv add --upgrade requests# Show what would be upgradeduv tree --outdated```### Pattern 7: Locking Dependencies```bash# Generate uv.lock fileuv lock# Update lock fileuv lock --upgrade# Lock without installinguv lock --no-install# Lock specific packageuv lock --upgrade-package requests```## Python Version Management### Pattern 8: Installing Python Versions```bash# Install Python versionuv python install 3.12# Install multiple versionsuv python install 3.11 3.12 3.13# Install latest versionuv python install# List installed versionsuv python list# Find available versionsuv python list --all-versions```### Pattern 9: Setting Python Version```bash# Set Python version for projectuv python pin 3.12# This creates/updates .python-version file# Use specific Python version for commanduv --python 3.11 run python script.py# Create venv with specific versionuv venv --python 3.12```## Project Configuration### Pattern 10: pyproject.toml with uv```toml[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 sourcesmy-package = { git = "https://github.com/user/repo.git" }```### Pattern 11: Using uv with Existing Projects```bash# Migrate from requirements.txtuv add -r requirements.txt# Migrate from poetry# Already have pyproject.toml, just use:uv sync# Export to requirements.txtuv pip freeze > requirements.txt# Export with hashesuv 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)

FluxonLab/Skillry/tree/main/community/wshobson-agents/skills/uv-package-manager commit 0aae372a57

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npx skillmds@latest add fluxonlab/uv-package-manager