uv is one of the best things that happened to Python
Discover why uv is revolutionizing Python development. With blazing speed, unified tooling, and deterministic dependency resolution, uv replaces pip, venv, and pip-tools with a single, Rust-powered solution that’s faster, simpler, and more reliable.
Python's ecosystem has evolved significantly over the years, but package management and virtual environments have been one of the biggest pain points of python. While tools like pip
, virtualenv
, and venv
have improved the experience, they often feel slow or clunky, especially for large-scale projects.
And this is when uv comes to rescue; a lightning-fast Python package manager and virtual environment tool that redefines how we handle dependencies. Built for speed and efficiency, uv is the best thing that has happened to Python in recent years, surpassing previous tools by integrating package management, virtual environments, and dependency resolution into a single, high-performance solution.
Why uv is a Game Changer
It's blazing Fast
uv is written in Rust, making it significantly faster than traditional tools like pip and virtualenv. Installing, resolving dependencies, and setting up virtual environments take a fraction of the time.
Ok this is kind of absurd. I just switched over @ArchiveBoxApp to uv, and it ran our typically ~1 min build+publish in under 2 seconds.
— Nick Sweeting (@thesquashSH) October 5, 2024
It's singlehandedly making me want to stay on python compared to JS.
👏 👏@charliermarsh @astral_sh amazing job pic.twitter.com/2dyVZAuwTW
Some happy user on X praising love for uv.
Unified Tooling
With uv, there's no need for multiple tools. It combines the functionalities of pip, venv, and pip-tools in a single package. This means:
- No more juggling between
pip install
,python -m venv
, andpip-compile
. You justuv sync
and it automatically creates a.venv
Python virtual environment and installs all the dependencies defined in yourpyproject.toml
. - You want to package it?
uv build
. - You want to publish it?
uv publish
.
Deterministic Dependency Resolution
Unlike pip
, which sometimes struggles with dependency conflicts, uv
provides deterministic dependency resolution similar to poetry
. This ensures that the same environment can be reproduced reliably across different machines. Similar to poetry.lock
, you will find uv.lock
.
Seamless Package Management
Installing and managing dependencies is smoother than ever:
uv add pandas
No need for pip install
—uv
integrates this seamlessly while being much faster.
Python as a tool (for real)
You can also run python tools without caring environments or setting up projects. Similar to npx
or pipx
, you have uv tool
or uvx
.
For example. If you want to launch a REST Client on the terminal:
uvx posting
And voilà:

This opens up the posibilty to remove lots of tooling for your projects. For example, no need to add ruff
as a dev dependency anymore, so you can just:
uvx ruff check
Do you want to always execute the latest version? no problem:
uvx ruff@latest check
This will always run the latest ruff version.
Cargo-like packaging with uv workspaces
uv uses a packaging approach similar to Rust cargo packages, which makes Python projects easier to manage, using workspaces—a way to group multiple packages (like microservices or libs) in one repo—without needing editable installs, symlinks, or complex tooling.
albatross
├── packages
│ ├── bird-feeder
│ │ ├── pyproject.toml
│ │ └── src
│ │ └── bird_feeder
│ │ ├── __init__.py
│ │ └── foo.py
│ └── seeds
│ ├── pyproject.toml
│ └── src
│ └── seeds
│ ├── __init__.py
│ └── bar.py
├── pyproject.toml
├── README.md
├── uv.lock
└── src
└── albatross
└── main.py
From uv docs: an example of a workspace, albatross which has 2 dependencies: bird-feeder library and seeds library.
Works with Existing Workflows
uv
doesn’t force you to change everything. It supports existing Python environments and integrates well with pip
, requirements.txt
, and other standard Python tooling. You can still compile your requirements.txt if your workflows need that:
uv export --format requirements-txt
Final Thoughts
I don't find any reasons to not to start using uv on your Python projects. It's fast, it's reliable and it's intuitive.
Python’s ecosystem has needed a tool like uv for a long time. It simplifies workflows, reduces overhead, and makes package management a joy rather than a chore. If you haven’t tried uv yet, now is the time.
Kudos to the Astral team for giving such a top notch standard on python tooling. First ruff, then uv. And they just announced a mypy alternative. And it looks promising:
Our type checker can solve Diophantine equations via the Python type system (this isn't a joke, it actually works) pic.twitter.com/XX327qs9EW
— Charlie Marsh (@charliermarsh) April 3, 2025
Just 🤯
If you want to learn more on how to use uv, you can go there: