uv-package-manager
Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows
Install / Use
npx skills add wshobson/agents --skill uv-package-managerInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Our assessment of uv-package-manager
uv-package-manager scores 98/100 on our quality scale, 43rd of 1,111 Automation skills we index (top 4%).
Its SKILL.md is 6.9 KB long, well organised into 92 sections with 15 code examples: a thorough specification that gives an agent plenty to work with.
With 39,920 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 4 days ago, so uv-package-manager is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands (2 minor notes below).
- noteInstalls by piping a downloaded script into a shellline 58
curl -LsSf https://astral.sh/uv/install.sh | sh - noteInstalls by piping a downloaded script into a shellline 61
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
uv-package-manager compared with similar skills
All 4 of these similar skills score higher than uv-package-manager; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| uv-package-manager (this skill)by wshobson | 98 | 39.9k | 4d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.4k | 9d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 73.8k | today | CLAUDE.md |
| rufloby ruvnet | 100 | 73.2k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 83.5k | today | MCP Server |
Frequently asked questions
- How do I install uv-package-manager?
- Run
npx skills add wshobson/agents --skill uv-package-manager. The install tabs above show the steps for each supported agent. - Which AI agents does uv-package-manager work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is uv-package-manager safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands (2 minor notes below). It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is uv-package-manager still maintained?
- The repository was last updated 4 days ago, so uv-package-manager is actively maintained.
Skill content
View source on GitHubname: 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
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
