██FR█████ █INTELL███████████

uv: Cargo-like Python Tool That Replaces pipx, pyenv, and more


This content originally appeared on DEV Community and was authored by Andrey Krisanov

Overview

uv is an end-to-end solution for managing Python projects,
command-line tools,
single-file scripts, and even
Python itself.

Think of it as Python’s Cargo: a unified, cross‑platform tool that’s fast, reliable, and easy to use.

This post is not a deep introduction to uv — many excellent articles already exist; instead,
it’s a concise cheat sheet for everyday use.

Installation & Updates 

# Install
curl -LsSf https://astral.sh/uv/install.sh | sh

# Update
uv self update

Managing Python Versions

Instead of juggling tools like pyenv, mise, asdf, or OS‑specific hacks, you can simply use uv:

# List available versions
uv python list

# Install Python 3.13
uv python install 3.13
  • Works the same across all OSes
  • No admin rights required
  • Independent of system Python

You can also use mise alongside uv if you prefer a global version manager.

Projects & Dependencies

Initialize a new project (creates a pyproject.toml automatically):

uv init myproject or # uv init -p 3.13 --name myproject
cd myproject

Sync dependencies (similar to pip install -r requirements.txt, but faster and more reliable):

uv sync

Add dependencies:

uv add litestar
uv add pytest --dev

Lock dependencies (generates a cross‑platform lockfile, like Pipfile.lock or poetry.lock):

uv lock

💡 The lock file is cross platform, so you can develop on Windows and deploy on Linux.

Fast Virtual Environments 

# Create & activate venv automatically
uv venv
source .venv/bin/activate

# Or skip activation and run directly with uv:
uv run python app.py

Scripts 

# Create a new script
uv init --script

# /// script
# requires-python = ">=3.13"
# dependencies = [
#     "requests",
# ]
# ///
import requests

print(requests.get("https://akrisanov.com"))

Run single‑file scripts with automatic dependency installation:

uv run script.py

💡 On *nix, add #!/usr/bin/env -S uv run (then chmod +x) to automatically call uv run for a script.

Tools

Install CLI tools globally, isolated from system Python:

uv tool install ruff # replaces pipx
uv tool install httpie

uvx httpie # a shortcut

# --with [temp dependency] runs jupyter in the current project
# without adding it and its dependencies to the project
uv run --with jupyter jupyter notebook

💡 uv run is fast enough that it implicitly re‑locks and re‑syncs the project each time, keeping your environment
up to date automatically.

If you’re developing a CLI tool, uv can help minimize the friction:

uv init --package your_tool
uv tool install . -e

See the tools documentation

Replacing pip-tools 

uv pip compile # replaces pip-tools compile
uv pip sync    # replaces pip-tools sync

Building and publishing packages 

# Build a `.whl` package for PyPI
uv build
# Upload your Python package to PyPI
uv publish

Pre-commit hooks 

uv run --with pre-commit-uv pre-commit run --all-files
pre-commit-uv

GitHub Actions 

astral-sh/setup-uv # brings UV to GitHub Actions

Docker

Official Docker images provide uv and Python preinstalled:

ghcr.io/astral-sh/uv:latest

Also, check Production-ready Python Docker Containers with uv by Hynek Schlawack.

Workspaces

uv supports organizing one or more packages into a workspace
to manage them together.

Example: you might have a FastAPI web application alongside several libraries, all versioned and maintained as separate
Python packages in the same Git repository.

In a workspace, each package has its own pyproject.toml, but the workspace shares a single lockfile, ensuring that
the workspace operates with a consistent set of dependencies.

Things to Keep in Mind

  • uv sync respects .python-version, but the UV_PYTHON environment variable takes precedence
  • Uses python‑build‑standalone, which can be slightly slower than system builds (~1–3%) and lacks CPU‑specific optimizations
  • Cache size can grow large (a trade‑off for speed and reliability)
  • Legacy projects may fail if they depended on pip’s older, looser dependency resolution rules

Why uv Matters

Python has always had a fragmented ecosystem of tools: pip, pip-tools, virtualenv, venv, pipx, pyenv, poetry, tox…

With uv, we finally get something closer to Rust’s Cargo or JavaScript’s npm/pnpm:
a single, consistent, cross‑platform tool for environments, dependencies, scripts, and tools — and it’s fast.

References & Further Reading

Additional Notes

  • While some people don’t care about uv being fast, it’s shaved minutes off CI builds and container rebuilds — saving money and energy.
  • Astral capitalized on a very promising project called python-build-standalone and now maintains it. These are Python builds that work without installers.

I’d love to hear if you’ve tried uv yet — what’s your setup?


This content originally appeared on DEV Community and was authored by Andrey Krisanov