Python Package & Project Manager

uv

Overview

uv is an ultra-fast Python package and project manager written in Rust. As of 2025, it integrates the functionality of multiple Python tools including pip, pip-tools, pipx, poetry, pyenv, virtualenv, and twine into a single tool, achieving 10-100x speed improvements over pip. Developed by Astral, like Ruff, it's revolutionizing Python development workflows as a high-performance developer tool.

Details

Key Features

• Ultra-Fast Performance: Written in Rust with parallelization and optimization for outstanding speed
• All-in-One Tool: Replaces pip, poetry, pyenv, virtualenv, and more
• Python Management: Integrated Python installation and version management
• Project Management: Lockfiles, workspaces, and dependency management
• Tool Management: Isolated environment execution for command-line tools
• Standards Compliant: Fully compatible with PyPI, requirements.txt, pyproject.toml

Package Management Features

• Fast Installation: 20-100x faster package installation than pip
• Dependency Resolution: Efficient and accurate dependency resolution
• Lockfiles: Cross-platform reproducibility with uv.lock
• Caching: Deduplication through global cache
• Multiple Sources: Supports PyPI, Git, HTTP, and local packages

Project Management Features

• Project Initialization: Create new projects with uv init
• Dependency Management: Intuitive management with uv add, uv remove
• Sync Function: Environment reproduction from lockfile with uv sync
• Script Execution: Automatic virtual environment management with uv run
• Workspaces: Native monorepo support

Python Management Features

• Python Installation: Manage multiple versions with uv python install
• Version Pinning: Specify project Python version with uv python pin
• Auto-detection: Automatically selects optimal Python version for project
• CPython/PyPy Support: Supports multiple Python implementations

Tool Management Features

• Tool Installation: Install in isolated environments with uv tool install
• One-off Execution: Temporary execution with uvx (alias for uv tool run)
• Environment Isolation: Manage each tool in independent virtual environment
• PEP 723 Support: Execute scripts with inline dependency metadata

Pros and Cons

Pros

• Outstanding Speed: Fast installation, resolution, and builds
• Unified Interface: Reduced learning and management costs for multiple tools
• Excellent Error Messages: Clear errors with suggested solutions
• Reproducibility Guarantee: Complete environment reproduction with lockfiles
• Existing Project Support: Easy migration from pip and poetry projects
• Active Development: Frequent updates and responsive support

Cons

• Relatively New: Released in 2024, ecosystem still developing
• Rust Dependency: May require Rust toolchain for building
• Configuration Files: Uses uv.toml instead of pip.conf
• Partial Incompatibility: Some advanced pip features not implemented
• Enterprise Adoption: Limited track record in large-scale projects

References

• uv Documentation
• Astral Official Site
• uv GitHub Repository
• uv Discord Community
• uv Migration Guide

Code Examples

Project Management

# Create new project
uv init my-project
cd my-project

# Specify Python version
uv python pin 3.12

# Add dependencies
uv add fastapi uvicorn
uv add --dev pytest black ruff

# Generate lockfile
uv lock

# Sync environment (from lockfile)
uv sync

# Run scripts (auto-manages virtual environment)
uv run python main.py
uv run pytest

Package Installation (pip-compatible)

# Using pip interface
uv pip install requests numpy pandas

# Install from requirements.txt
uv pip install -r requirements.txt

# Install development dependencies
uv pip install -e ".[dev]"

# Install specific version
uv pip install "django>=4.0,<5.0"

# Upgrade
uv pip install --upgrade requests

Python Management

# List available Python versions
uv python list

# Install Python 3.12
uv python install 3.12

# Install multiple versions
uv python install 3.11 3.12 pypy3.10

# Pin project Python version
uv python pin 3.12

# Run with specific Python
uv run --python 3.11 python script.py

Virtual Environment Management

# Create virtual environment
uv venv

# Create with specific Python version
uv venv --python 3.12

# Create with custom name
uv venv myenv

# Activate virtual environment (usually unnecessary due to auto-management)
source .venv/bin/activate  # Linux/Mac
.venv\Scripts\activate     # Windows

Tool Management

# Install global tools
uv tool install ruff
uv tool install black
uv tool install mypy

# Run tools
uv tool run ruff check .
uv tool run black --check .

# Use uvx (alias) for temporary execution
uvx ruff check .
uvx --from jupyter-core jupyter --version

# Run specific tool version
uvx --with "ruff==0.1.0" ruff check

Project Configuration (pyproject.toml)

[project]
name = "my-project"
version = "0.1.0"
description = "My awesome Python project"
requires-python = ">=3.11"
dependencies = [
    "fastapi>=0.100.0",
    "uvicorn[standard]>=0.23.0",
    "pydantic>=2.0.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.0.0",
    "black>=23.0.0",
    "ruff>=0.1.0",
]

[tool.uv]
dev-dependencies = [
    "pytest-cov>=4.0.0",
    "mypy>=1.0.0",
]

Workspace Management

# Root pyproject.toml
[tool.uv.workspace]
members = ["packages/*", "apps/*"]

[tool.uv]
constraint-dependencies = [
    "django>=4.2",
    "numpy<2.0",
]

# Sync workspace
uv sync --all-packages

# Run command in specific package
uv run --package my-app python -m my_app

# Test entire workspace
uv run --all-packages pytest

Script Execution (PEP 723)

# script.py - with inline metadata
# /// script
# requires-python = ">=3.11"
# dependencies = [
#   "requests",
#   "rich",
# ]
# ///

import requests
from rich import print

response = requests.get("https://api.github.com")
print(response.json())

# Run command
# uv run script.py

Fast Build and Publishing

# Build package
uv build

# Upload to PyPI
uv publish

# Upload to Test PyPI
uv publish --repository testpypi