MarGib – The World Behind the Keyboard: UV – an ultra-fast Python package manager in Rust. How it works, why it outperforms the competition, and how to use it?

UV – an ultra-fast Python package manager in Rust. How it works, why it outperforms the competition, and how to use it?

MarGib July 05, 2026

🌐 🇵🇱 Polski · 🇬🇧 EN

UV is a revolutionary tool for managing Python dependencies and environments, written in Rust. Thanks to optimizations and a modern architecture, it outperforms traditional solutions like pip or Poetry. Check out how it works, why it is so fast, and how to get started with it.

Ilustracja interfejsu wiersza poleceń z komendami UV, symbolizująca szybkość i nowoczesność narzędzia. — UV – an ultra-fast Python package manager in Rust. Illustration: Marginał Blog.

What is UV and why should you be interested in it?

UV is a modern package manager and project management tool for Python, created by Astral – the developers of the popular linter ruff. Its main goal is to replace several tools at once: pip, venv, pip-tools, and even partially poetry or pdm. Thanks to its architecture written in Rust, UV offers performance unattainable for traditional Python-based solutions.

Key features of UV include:

Ultra-fast package installation and updates.
Built-in virtual environment management.
Dependency locking (generating the uv.lock file).
Compatibility with pyproject.toml and requirements.txt.
Ability to run scripts without global package installation (similar to pipx).

UV is not just another experiment – it is a project developed by an experienced team that has already proven its effectiveness with tools like ruff. It is worth paying attention to if you are looking for a more efficient alternative to pip or poetry.

Who is behind the UV project and how has it evolved?

UV was created by Astral, founded by Charlie Marsh and Greg Price. Astral had already made a name for itself with tools such as:

ruff – a lightning-fast Python linter that gained massive popularity.
rye – an experimental package manager that pioneered the idea of unifying Python tools.

The first public version of UV (0.1.0) was released on February 14, 2024. Since then, the project has been developing dynamically, with regular updates every 1-2 weeks. Rapid development and community engagement have led to UV gaining over 15,000 stars on GitHub in just a few months.

The main motivation for creating UV was the frustration associated with the slow performance of traditional tools. pip or poetry are written in Python, which comes with performance limitations, especially when resolving dependencies or performing I/O operations. UV solves these problems by leveraging the capabilities of the Rust language.

Why is UV so fast? Architecture and optimizations

UV outperforms the competition in terms of performance, and the key to its speed lies in several crucial aspects:

1. The Rust language and low-level control

UV is written in Rust, which gives it several significant advantages over Python-based tools:

No interpreter overhead: Python, despite its flexibility, is slower than compiled languages like Rust. UV avoids this problem by running as a native binary.
Multithreading: Rust allows for the effective use of multiple CPU cores, which speeds up operations like dependency resolution or package installation.
Memory control: Rust eliminates garbage collection issues, which translates into more stable and faster operation.

For example, installing the numpy package with UV takes about 0.5 seconds, while in pip it takes 5-10 seconds. That is a 10-20x difference!

2. Modern dependency solver

UV uses the pubgrub algorithm, which is also used in poetry. However, unlike poetry, UV has optimized this algorithm for performance. As a result, dependency resolution is not only accurate but also lightning-fast.

3. I/O optimizations and caching

UV minimizes disk read/write operations, which are one of the main bottlenecks in Python tools. It achieves this through:

Global cache: Downloaded packages are stored in a central location, which speeds up subsequent installations.
Avoiding redundant file reads: UV reads configuration files (e.g., pyproject.toml) only once, whereas tools like pip might do so multiple times.
Built-in package index server: UV uses a local proxy to PyPI, which reduces network latency.

4. Benchmarks – UV vs. the competition

The table below presents a comparison of execution times for key operations in UV and other tools (based on Astral benchmarks from March 2024):

Tool	Install `numpy`	Install 100 packages	Create virtual environment
UV	0.5s	~5s	~0.1s
pip	5-10s	60-120s	2-5s
poetry	8-15s	90-180s	3-8s
pdm	6-12s	70-150s	2-6s

It is worth noting that results may vary depending on the system and configuration, but the trend is clear: UV is significantly faster than the competition.

Advantages of UV – why should you use it?

UV not only beats the competition in performance but also offers a range of other benefits:

1. One tool for everything

UV combines the functions of several tools into one:

pip – package installation.
venv/virtualenv – virtual environment management.
pip-tools – generating requirements.txt files.
pipx – running scripts without global installation.

Thanks to this, you no longer need to remember multiple commands or tools – UV does it for you.

2. Compatibility with existing projects

UV is compatible with:

pyproject.toml files (the standard in modern Python projects).
requirements.txt files (legacy, but still widely used).
uv.lock files (equivalent to poetry.lock or pdm.lock).

This means you can seamlessly integrate UV into existing projects, regardless of which tool you used previously.

3. Minimal requirements and easy installation

UV is provided as a statically compiled binary, which means that:

It does not require Python to be installed to run (though the Python project itself obviously does).
It has no dependencies on other packages.
It runs on Linux, macOS, and Windows (including WSL2).

Installing UV takes literally a few seconds – just run one command.

4. Active community and regular updates

UV is being developed very actively. On average, a new version appears every 1-2 weeks, and the Astral team responds quickly to bug reports and user suggestions. The project already has over 15,000 stars on GitHub, which proves the high level of community interest.

5. Support for multiple Python versions

UV works with Python version 3.7 and newer. This means you can use it in both new and older projects.

How to install UV?

Installing UV is simple and does not require special preparations. Below you will find instructions for various operating systems.

System requirements

Operating systems: Linux, macOS, Windows (WSL2 recommended for Windows).
Python: Version 3.7 or newer (required for running Python projects, but not for installing UV itself).
Dependencies: None – UV is a self-contained binary.

Installation methods

The simplest way to install UV is to use the installation script:

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

Alternatively, you can install UV via pip (though this is not recommended, as UV does not require Python):

pip install uv

If you prefer manual installation, you can download the binary from the GitHub releases page and place it in a directory included in your PATH.

Installation verification

After installation, check if UV is working correctly:

uv --version

You should see the version number, e.g.: uv 0.1.15 (2024-04-05).

How to use UV? Basic commands

UV offers many useful commands that replace the functions of traditional tools. Below are the most important ones.

1. Creating a new project

To create a new project, use the uv init command:

uv init my_project
cd my_project

UV will create a project structure with a pyproject.toml file, which will contain the basic configuration.

2. Installing packages

UV allows you to install packages in several ways:

Installing a single package:

uv add requests

Installing a package in a specific version:

uv add numpy@1.24.0

Installing packages from a requirements.txt file:

uv pip install -r requirements.txt

3. Managing virtual environments

UV has built-in support for virtual environments:

Creating a virtual environment:

uv venv

By default, the environment will be created in the .venv directory.

Activating the environment:

# Linux/macOS
source .venv/bin/activate

# Windows
.venv\Scripts\activate

4. Running scripts

UV allows you to run Python scripts without needing to install packages globally:

uv run python my_script.py

You can also launch a REPL with installed packages:

uv run python

5. Locking dependencies

To generate a uv.lock file with exact package versions, use:

uv lock

The uv.lock file works similarly to poetry.lock or pdm.lock and ensures installation reproducibility.

6. Updating packages

To update a package to the latest version, use:

uv update requests

UV development roadmap – what's next?

UV is a project that is developing dynamically, and the Astral team has ambitious plans for the future. Here is what we can expect in the coming months:

1. Support for alternative package indexes

In the second half of 2024, UV is expected to gain support for private package repositories, which will facilitate work in corporate environments.

2. Integration with build tools

UV is set to be integrated with popular Python project build tools, such as setuptools or hatch. This will make it an even more universal solution.

3. Experimental support for Python 3.13

The Astral team plans to add support for the latest Python version, allowing UV to be used in cutting-edge projects.

4. Expanding locking features

The uv.lock file is to be expanded with additional metadata, which will further increase installation reproducibility.

Will UV replace pip and Poetry?

UV has the potential to become the primary tool for managing Python projects, but this does not mean it will immediately replace pip or poetry. Here are a few reasons why UV might gain popularity:

Performance: UV is simply significantly faster than the competition, which is crucial in large projects.
One tool for everything: UV combines the functions of several tools, simplifying the workflow.
Active community: The project is being developed very dynamically, which ensures it will continue to evolve in the future.

However, pip and poetry still have their advantages:

pip is the standard and is pre-installed in most Python distributions.
poetry offers more extensive project management features, such as publishing packages to PyPI.

UV is a great alternative, but will it replace pip or poetry? That depends on user needs. If you value performance and simplicity, UV might be the ideal choice.

Summary – is it worth trying UV?

UV is one of the most promising tools for managing Python projects to appear in recent years. Its main advantages are:

Ultra-fast installation and package management thanks to its Rust-based architecture.
One tool for everything – replaces pip, venv, pip-tools, and partially poetry.
Easy installation and minimal requirements – runs on Linux, macOS, and Windows.
Active community and regular updates – the project is developing dynamically.

If you are looking for a more efficient alternative to pip or poetry, UV is definitely worth trying. Its speed and simplicity can significantly improve your workflow, especially in larger projects.

It is also worth following the project's development, as the Astral team has ambitious plans for the future. UV could become the standard for Python project management, just as ruff became the standard for linting.

If you want to learn more about performance optimization in development tools, check out our post on limiting CPU and RAM usage by processes on Linux. And if you are interested in how Rust is revolutionizing system tools, read about Rust Coreutils on Windows.