uv-package-manager

name uv-package-manager description 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 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