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 pr...

Security Scan

The skill is an instruction-only guide for the 'uv' Python package manager and its requested actions and artifacts are consistent with that purpose — no unrelated credentials, installs, or surprising behaviors are present.

Purpose & Capability

Name, description, and instructions align: the SKILL.md explains installing and using the uv package manager, venv and Python version management, dependency operations, lockfiles, and related workflows. It doesn't request unrelated access or credentials.

Instruction Scope

Instructions are focused on installing and using uv and managing Python projects. They reference project files like pyproject.toml, .python-version, and virtualenvs — all expected for this purpose. The guide does not direct the agent to read arbitrary system files, harvest credentials, or transmit data to unexpected endpoints.

Install Mechanism

There is no formal install spec in the skill bundle (it's instruction-only). The SKILL.md recommends several install methods, including 'curl -LsSf https://astral.sh/uv/install.sh | sh' and PowerShell 'irm ... | iex', which are common for CLI installers but carry the usual risk of piping remote scripts to a shell. Alternatives (pip, brew, cargo) are also provided.

Credentials

The skill declares no required environment variables, credentials, or config paths. The instructions do not reference hidden env vars or ask for unrelated secrets.

Persistence & Privilege

The skill is not marked always:true and is user-invocable only. It does not request persistent presence or attempt to modify other skills or global agent settings.

Assessment

This skill is a coherent, instruction-only guide for the uv package manager. Before running any installer commands it recommends, verify the source (e.g., confirm astral.sh is the project's official site), prefer package-manager installs (pip/brew/cargo) if possible, and avoid piping remote scripts directly to a shell without inspecting them. In CI or production, pin uv versions and prefer reproducible install methods (package manager or verified release artifacts). If you need stronger assurance, fetch the installer script first, inspect it, and verify checksums or use a release hosted on a well-known registry.

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

Advanced Workflows

Pattern 12: Monorepo Support

# Project structure
# monorepo/
#   packages/
#     package-a/
#       pyproject.toml
#     package-b/
#       pyproject.toml
#   pyproject.toml (root)

# Root pyproject.toml
[tool.uv.workspace]
members = ["packages/*"]

# Install all workspace packages
uv sync

# Add workspace dependency
uv add --path ./packages/package-a

Pattern 13: CI/CD Integration

# .github/workflows/test.yml
name: Tests

on: [push, pull_request]

jobs:
  test:
    runs-on: ubuntu-latest

    steps:
      - uses: actions/checkout@v4

      - name: Install uv
        uses: astral-sh/setup-uv@v2
        with:
          enable-cache: true

      - name: Set up Python
        run: uv python install 3.12

      - name: Install dependencies
        run: uv sync --all-extras --dev

      - name: Run tests
        run: uv run pytest

      - name: Run linting
        run: |
          uv run ruff check .
          uv run black --check .

Pattern 14: Docker Integration

# Dockerfile
FROM python:3.12-slim

# Install uv
COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv

# Set working directory
WORKDIR /app

# Copy dependency files
COPY pyproject.toml uv.lock ./

# Install dependencies
RUN uv sync --frozen --no-dev

# Copy application code
COPY . .

# Run application
CMD ["uv", "run", "python", "app.py"]

Optimized multi-stage build:

# Multi-stage Dockerfile
FROM python:3.12-slim AS builder

# Install uv
COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv

WORKDIR /app

# Install dependencies to venv
COPY pyproject.toml uv.lock ./
RUN uv sync --frozen --no-dev --no-editable

# Runtime stage
FROM python:3.12-slim

WORKDIR /app

# Copy venv from builder
COPY --from=builder /app/.venv .venv
COPY . .

# Use venv
ENV PATH="/app/.venv/bin:$PATH"

CMD ["python", "app.py"]

Pattern 15: Lockfile Workflows

# Create lockfile (uv.lock)
uv lock

# Install from lockfile (exact versions)
uv sync --frozen

# Update lockfile without installing
uv lock --no-install

# Upgrade specific package in lock
uv lock --upgrade-package requests

# Check if lockfile is up to date
uv lock --check

# Export lockfile to requirements.txt
uv export --format requirements-txt > requirements.txt

# Export with hashes for security
uv export --format requirements-txt --hash > requirements.txt

Performance Optimization

Pattern 16: Using Global Cache

# UV automatically uses global cache at:
# Linux: ~/.cache/uv
# macOS: ~/Library/Caches/uv
# Windows: %LOCALAPPDATA%\uv\cache

# Clear cache
uv cache clean

# Check cache size
uv cache dir

Pattern 17: Parallel Installation

# UV installs packages in parallel by default

# Control parallelism
uv pip install --jobs 4 package1 package2

# No parallel (sequential)
uv pip install --jobs 1 package

Pattern 18: Offline Mode

# Install from cache only (no network)
uv pip install --offline package

# Sync from lockfile offline
uv sync --frozen --offline

Comparison with Other Tools

uv vs pip

# pip
python -m venv .venv
source .venv/bin/activate
pip install requests pandas numpy
# ~30 seconds

# uv
uv venv
uv add requests pandas numpy
# ~2 seconds (10-15x faster)

uv vs poetry

# poetry
poetry init
poetry add requests pandas
poetry install
# ~20 seconds

# uv
uv init
uv add requests pandas
uv sync
# ~3 seconds (6-7x faster)

uv vs pip-tools

# pip-tools
pip-compile requirements.in
pip-sync requirements.txt
# ~15 seconds

# uv
uv lock
uv sync --frozen
# ~2 seconds (7-8x faster)

Common Workflows

Pattern 19: Starting a New Project

# Complete workflow
uv init my-project
cd my-project

# Set Python version
uv python pin 3.12

# Add dependencies
uv add fastapi uvicorn pydantic

# Add dev dependencies
uv add --dev pytest black ruff mypy

# Create structure
mkdir -p src/my_project tests

# Run tests
uv run pytest

# Format code
uv run black .
uv run ruff check .

Pattern 20: Maintaining Existing Project

# Clone repository
git clone https://github.com/user/project.git
cd project

# Install dependencies (creates venv automatically)
uv sync

# Install with dev dependencies
uv sync --all-extras

# Update dependencies
uv lock --upgrade

# Run application
uv run python app.py

# Run tests
uv run pytest

# Add new dependency
uv add new-package

# Commit updated files
git add pyproject.toml uv.lock
git commit -m "Add new-package dependency"

Tool Integration

Pattern 21: Pre-commit Hooks

# .pre-commit-config.yaml
repos:
  - repo: local
    hooks:
      - id: uv-lock
        name: uv lock
        entry: uv lock
        language: system
        pass_filenames: false

      - id: ruff
        name: ruff
        entry: uv run ruff check --fix
        language: system
        types: [python]

      - id: black
        name: black
        entry: uv run black
        language: system
        types: [python]

Pattern 22: VS Code Integration

// .vscode/settings.json
{
  "python.defaultInterpreterPath": "${workspaceFolder}/.venv/bin/python",
  "python.terminal.activateEnvironment": true,
  "python.testing.pytestEnabled": true,
  "python.testing.pytestArgs": ["-v"],
  "python.linting.enabled": true,
  "python.formatting.provider": "black",
  "[python]": {
    "editor.defaultFormatter": "ms-python.black-formatter",
    "editor.formatOnSave": true
  }
}

Troubleshooting

Common Issues

# Issue: uv not found
# Solution: Add to PATH or reinstall
echo 'export PATH="$HOME/.cargo/bin:$PATH"' >> ~/.bashrc

# Issue: Wrong Python version
# Solution: Pin version explicitly
uv python pin 3.12
uv venv --python 3.12

# Issue: Dependency conflict
# Solution: Check resolution
uv lock --verbose

# Issue: Cache issues
# Solution: Clear cache
uv cache clean

# Issue: Lockfile out of sync
# Solution: Regenerate
uv lock --upgrade

Best Practices

Project Setup

1. Always use lockfiles for reproducibility
2. Pin Python version with .python-version
3. Separate dev dependencies from production
4. Use uv run instead of activating venv
5. Commit uv.lock to version control
6. Use --frozen in CI for consistent builds
7. Leverage global cache for speed
8. Use workspace for monorepos
9. Export requirements.txt for compatibility
10. Keep uv updated for latest features

Performance Tips

# Use frozen installs in CI
uv sync --frozen

# Use offline mode when possible
uv sync --offline

# Parallel operations (automatic)
# uv does this by default

# Reuse cache across environments
# uv shares cache globally

# Use lockfiles to skip resolution
uv sync --frozen  # skips resolution

Migration Guide

From pip + requirements.txt

# Before
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

# After
uv venv
uv pip install -r requirements.txt
# Or better:
uv init
uv add -r requirements.txt

From Poetry

# Before
poetry install
poetry add requests

# After
uv sync
uv add requests

# Keep existing pyproject.toml
# uv reads [project] and [tool.poetry] sections

From pip-tools

# Before
pip-compile requirements.in
pip-sync requirements.txt

# After
uv lock
uv sync --frozen

Command Reference

Essential Commands

# Project management
uv init [PATH]              # Initialize project
uv add PACKAGE              # Add dependency
uv remove PACKAGE           # Remove dependency
uv sync                     # Install dependencies
uv lock                     # Create/update lockfile

# Virtual environments
uv venv [PATH]              # Create venv
uv run COMMAND              # Run in venv

# Python management
uv python install VERSION   # Install Python
uv python list              # List installed Pythons
uv python pin VERSION       # Pin Python version

# Package installation (pip-compatible)
uv pip install PACKAGE      # Install package
uv pip uninstall PACKAGE    # Uninstall package
uv pip freeze               # List installed
uv pip list                 # List packages

# Utility
uv cache clean              # Clear cache
uv cache dir                # Show cache location
uv --version                # Show version

Resources

• Official documentation: https://docs.astral.sh/uv/
• GitHub repository: https://github.com/astral-sh/uv
• Astral blog: https://astral.sh/blog
• Migration guides: https://docs.astral.sh/uv/guides/
• Comparison with other tools: https://docs.astral.sh/uv/pip/compatibility/

Best Practices Summary

1. Use uv for all new projects - Start with uv init
2. Commit lockfiles - Ensure reproducible builds
3. Pin Python versions - Use .python-version
4. Use uv run - Avoid manual venv activation
5. Leverage caching - Let uv manage global cache
6. Use --frozen in CI - Exact reproduction
7. Keep uv updated - Fast-moving project
8. Use workspaces - For monorepo projects
9. Export for compatibility - Generate requirements.txt when needed
10. Read the docs - uv is feature-rich and evolving