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Uv Package Manager

Seth HobsonCommunityCreated by Seth Hobson

  • Skill
  • Tool integration
  • Software development
  • MIT
  • Low risk

From the author

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.
— the description by Seth Hobson

From the skill’s files

Taken from the skill’s own files (its description, section headings and stated usage). Not an AutoGineer summary, and not written by the author as one.

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. Comprehensive guide to using uv, an extremely fast Python package installer and resolver written in Rust, for modern Python project management and dependency workflows.

What it does

  • When to Use This Skill
  • Core Concepts
  • Installation
  • Quick Start
  • Virtual Environment Management
  • Package Management

When to use it

  • Use when setting up Python projects, managing dependencies, or optimizing Python development workflows with uv.
  • Setting up new Python projects quickly
  • Managing Python dependencies faster than pip
  • Creating and managing virtual environments
  • Installing Python interpreters
  • Resolving dependency conflicts efficiently

Advantages

The skill’s files do not state this.

Usage examples

The skill’s files do not state this.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/wshobson/uv-package-manager/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip uv-package-manager.zip -d .agents/skills

Documentation by Seth Hobson

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
# Using Homebrew (macOS or Linux)
brew install uv

# Using Cargo (if you have Rust)
cargo install --locked uv

On Windows, use WinGet:

winget install --id=astral-sh.uv -e

Use the official installation guide for other supported installation methods.

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/[email protected]

# 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

Files

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
# Using Homebrew (macOS or Linux)
brew install uv

# Using Cargo (if you have Rust)
cargo install --locked uv

On Windows, use WinGet:

winget install --id=astral-sh.uv -e

Use the official installation guide for other supported installation methods.

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/[email protected]

# 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

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs a command-line tool, Needs Python

Security

What our scanner noticed· Low risk

  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Seth Hobson
Publisher
Seth Hobson (Community)
Source
wshobson/agents · plugins/python-development/skills/uv-package-manager · commit 4bde316
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Seth Hobson or Seth Hobson.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download uv-package-manager.zip