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    wshobson

    uv-package-manager

    wshobson/uv-package-manager
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    About

    SKILL.md

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    About

    Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows...

    SKILL.md

    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

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