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Uv Package Manager

  • 11.8k installs
  • 38.3k repo stars
  • Updated July 22, 2026
  • wshobson/agents

uv is a Rust-based Python package manager and virtual environment tool that installs dependencies, manages Python versions, and creates reproducible builds 10-100x faster than pip.

About

uv is an ultra-fast Python package installer and resolver written in Rust that replaces pip, pip-tools, and poetry for dependency management. Developers use it to set up projects, manage dependencies, create virtual environments, and install Python interpreters with significantly faster performance. Key workflows include initializing projects with `uv init`, adding/removing packages with `uv add`/`uv remove`, managing virtual environments via `uv venv` and `uv run`, pinning Python versions, and generating lockfiles for reproducible builds. Works cross-platform (Linux, macOS, Windows) and requires no Python installation.

  • 10-100x faster package installation than pip; drop-in replacement for pip workflows
  • Create venvs and install Python versions with `uv venv` and `uv python install`; no system Python required
  • Auto-generates `pyproject.toml`, `uv.lock`, and `.python-version`; supports git, local, and editable installs
  • `uv run` activates venv implicitly; run scripts and CLI tools without manual activation
  • Migrates from pip, pip-tools, poetry, and conda; exports to requirements.txt with optional hashes

Uv Package Manager by the numbers

  • 11,791 all-time installs (skills.sh)
  • +279 installs in the week ending Jul 28, 2026 (Skillselion tracking)
  • Ranked #5 of 311 Python skills by installs in the Skillselion catalog
  • Security screen: HIGH risk (skills.sh audit)
  • Data as of Jul 28, 2026 (Skillselion catalog sync)
At a glance

uv-package-manager capabilities & compatibility

Capabilities
fast package installation and dependency resolut · virtual environment creation and management · python version installation and pinning · lockfile generation for reproducible builds · git, local, and editable package installation · project initialization with templating · requirements.txt import/export
Works with
github · docker
Use cases
devops · ci cd
Platforms
macOS · Windows · Linux · WSL
Runs
Runs locally
Pricing
Free
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Listed on Skillselion
Installs11.8k
repo stars38.3k
Security audit1 / 3 scanners passed
Last updatedJuly 22, 2026
Repositorywshobson/agents

What it does

Install Python packages and manage virtual environments 10-100x faster than pip using a Rust-based package manager.

Who is it for?

Python backend projects, monorepos, CI/CD optimization, Docker builds, dependency migration, teams using pip/poetry/conda, reproducible dependency management

Skip if: Non-Python projects, conda-specific workflows, PyPI private repositories without pip compatibility, legacy Python 2 projects

When should I use this skill?

Setting up new Python projects, managing dependencies faster, creating virtual environments, resolving dependency conflicts, optimizing CI/CD, migrating from pip/poetry

What you get

Developers initialize Python projects, manage dependencies, and set up CI/CD environments in seconds; lockfiles ensure reproducible builds; no Python pre-installation required.

  • pyproject.toml with dependencies and metadata
  • uv.lock reproducible lockfile
  • .python-version pinned Python version

By the numbers

  • 10-100x faster than pip for installation
  • Cross-platform support: Linux, macOS, Windows
  • Compatible with pip, pip-tools, poetry workflows

Files

SKILL.mdMarkdownGitHub ↗

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

Related skills

How it compares

Pick uv-package-manager for agent-guided uv adoption and monorepo setup; use poetry documentation when remaining on poetry-specific plugin ecosystems.

FAQ

What is uv and why is it faster than pip?

uv is a Python package manager written in Rust that performs dependency resolution and installation 10-100x faster than pip. Rust's performance and uv's optimized algorithms enable speed without sacrificing correctness.

Do I need Python installed to use uv?

No. uv can install and manage Python versions itself via `uv python install`. You can use uv to bootstrap Python environments without a pre-existing Python installation.

Can I use uv with existing pip or poetry projects?

Yes. uv reads `pyproject.toml` with `uv sync`, imports `requirements.txt` with `uv add -r requirements.txt`, and exports to `requirements.txt` with `uv pip freeze`. Full migration support from pip, pip-tools, and poetry.

Is Uv Package Manager safe to install?

skills.sh reports 1 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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