A Walk-Through of uv for Python

Faster installs. Zero config. Blazing speed. uv isn’t just another Python tool—it’s a game-changer for your workflow.

A Walk-Through of uv for Python

The Next-Gen Python Package Manager That Might Just Replace pip

But what if I told you there’s a new kid on the block that’s faster, smarter, and solves some of pip's biggest pain points?

Meet uv, a blazing-fast Python package manager and build backend from the minds behind Astral.

Think of it as the Rust-powered lovechild of pip, virtualenv, and poetry, built for modern development workflows.

In this article, we’ll walk through what uv is, how to get started with it, and why it might just become your new favorite tool in the Python ecosystem.

What is uv?

At its core, uv is a modern Python package manager designed to be:

Ridiculously fast (thanks to Rust)

Cross-platform (Linux, macOS, Windows)

Compatible with pip and virtualenv

Drop-in ready for existing projects

It aims to be a one-stop tool for Python environments: installing packages, resolving dependencies, creating virtual environments, and more — without the sluggishness of traditional tools.

It’s kind of like what bun is doing for JavaScript: unify and supercharge the workflow.

Installing uv

You can install uv with just one line:

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

Alternatively, you can use brew (on macOS and Linux):

brew install astral-sh/uv/uv

Or via pipx:

pipx install uv

Once installed, verify it:

uv --version

Boom. You’re ready to roll.

How Fast Is It Really?

Let’s put it this way: if pip feels like riding a bicycle uphill, uv is a Tesla on a straight highway.

Here’s a quick benchmark:

| Task                   | `pip` Time | `uv` Time | 
| ---------------------- | ---------- | --------- | 
| Installing `requests`  | \~2.5 sec  | \~0.3 sec | 
| Resolving complex deps | \~12 sec   | \~1.7 sec | 
| Creating virtualenv    | \~1.8 sec  | \~0.2 sec |

No caching tricks here. Just pure Rust speed and clever optimization.

Using uv: Common Commands

Let’s look at how you’d use uv in day-to-day work:

1. Install packages

uv pip install flask

Yes, uv pip install mimics pip install. It acts as a drop-in replacement while leveraging uv's ultra-fast backend.

2. Create a virtual environment

uv venv

It auto-creates a .venv directory in your current folder. No more needing python -m venv .venv or virtualenv.

3. Run inside virtualenv

uv run python app.py

Think of this like poetry run, but faster and simpler. It activates the .venv and runs your script.

4. Manage dependencies

uv also supports requirements.txt and pyproject.toml seamlessly:

uv pip install -r requirements.txt

Or with modern lock files:

uv pip compile pyproject.toml

This makes it easy to transition from existing workflows without rewriting your project setup.

Why uv Is More Than Just a Faster pip

Beyond performance, uv fixes many ecosystem annoyances:

Handles dependency resolution intelligently

Compatible with pyproject.toml-based workflows

Built-in support for isolated environments

Native Rust speed, without sacrificing Python ergonomics

And because it’s actively developed by the Astral team (also behind ruff, the fastest linter in Python), you can expect quality, stability, and rapid iteration.

Real-World Use Case: From pip to uv in Seconds

Let’s say you have a typical Flask project:

my-flask-app/ 
├── app.py 
├── requirements.txt 
└── .venv/

To migrate to uv, just run:

uv venv 
uv pip install -r requirements.txt 
uv run python app.py

No manual source .venv/bin/activate, no waiting for pip to do its thing. Everything just works—fast.

Should You Switch to uv?

Yes, if:

You’re tired of pip and venv slowing you down

You want a simpler setup without juggling five different tools

You’re using or migrating to pyproject.toml

Maybe not yet, if:

You need absolute backward compatibility for legacy CI pipelines

You’re locked into a poetry-only or conda-specific workflow

That said, uv is moving fast and already integrates well into most environments.

Bonus: uv is not just for installing packages

It’s worth noting that uv includes tools for:

Lockfile generation

Hash pinning (secure installs)

Script execution (uv run)

Managing pyproject.toml dependencies

All in one binary. One tool to rule them all.

Final Thoughts

Python has long needed a next-gen tool to manage environments and packages without the friction. uv might just be that solution—built with speed, simplicity, and modern development in mind.

It’s not trying to reinvent the Python wheel. It’s making it spin faster.

If you haven’t tried it yet, I highly recommend giving uv a test run in your next side project. You might never go back to pip again.

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Happy coding