Forget pip and Poetry - uv Is the Future of Python Development

Imagine installing dependencies for your Python project in less time than it takes to sip your coffee.

Now imagine you don’t have to juggle pip, venv, poetry, pipx, and half a dozen other tools just to get started.

That’s the promise of uv, a lightning-fast, all-in-one project manager built in Rust that’s turning the Python packaging world on its head.

Why uv Matters

I still remember the frustration of setting up a new Python project: waiting for pip to finish installing dependencies, juggling virtual environments with venv or virtualenv. It always felt slow, clunky, and unnecessarily complicated.

Then I discovered uv, and honestly, it changed the way I work with Python. uv isn’t just another package manager, it’s an all-in-one project manager that handles everything I used to rely on multiple tools for: installing dependencies, managing Python versions, creating virtual environments, building packages, and even running scripts like pipx.

What blew me away the most was the speed. Tasks that used to take sometimes even minutes now complete in seconds. I’ve personally seen uv install packages 10x faster than the tools I’ve been using for years.

For me, uv isn’t is a rethink of Python packaging that makes starting a project enjoyable again. It’s fast, seamless, and, frankly, addictive once you experience the difference.

Origins & Background

When I first heard about uv, I was curious who was behind it. It turns out it was developed by Astral, the team that created Ruff, the Python linter.

uv officially launched in early 2024, and from the beginning, it was positioned as an ambitious project: “Cargo for Python.” If you’re familiar with Rust, Cargo is the go-to tool for managing dependencies and builds. Astral’s vision was to bring the same level of speed, reliability, and simplicity to Python developers.

What really sets uv apart for me, and why I’ve become such a fan, is that it’s built in Rust. Rust is known for its performance and safety, and uv leverages that to give Python packaging a speed boost I hadn’t seen before. Installing packages, setting up environments, and syncing dependencies all feel nearly instantaneous. It’s a reminder that sometimes, the right language and architecture can make a massive difference in developer experience.

Core Features

When I started using uv, what immediately caught my attention was how everything felt consolidated. Instead of juggling pip, poetry, virtualenv, pipx, and more, uv lets me handle all of these from a single tool.

Unified Toolchain

Honestly, this is where uv shines for me. Everything I used to do with multiple tools, installing packages, managing virtual environments, running scripts, is now in one place. No context-switching, no hunting down conflicting tools. Just one command-line interface that feels cohesive and intuitive.

Speed & Efficiency

I wasn’t exaggerating when I said uv is fast. Benchmarks show it’s 8–10× faster than pip and, if you’re using cached packages, up to 80–115× faster. I noticed this immediately while setting up a new project, it literally cut my setup time from minutes to seconds. uv achieves this through clever tricks like global caching, hardlinks, and copy-on-write, which also keeps disk usage low.

Virtual Environments & Python Version Management

Creating virtual environments is insanely fast with uv. Compared to python -m venv, it’s about 80× faster, and even compared to virtualenv, it’s around 7× faster. Plus, I can manage multiple Python versions without needing separate tools like pyenv. Switching Python versions and isolating projects has never been smoother.

Scripts & Tool Management

One of my favorite features is uv run, which lets me execute single-file scripts with inline dependencies. I can also manage CLI tools like pipx using uvx, deciding whether to keep them permanently or run them ephemerally. It’s flexible and removes a lot of friction from running ad-hoc tools.

Packaging & Publishing

When it comes to packaging, uv doesn’t disappoint. I can build source and binary distributions with uv build and publish them effortlessly using uv publish. It fully integrates with modern Python workflows (pyproject.toml) so packaging feels natural, not like a chore.

Compatibility & Integration

Finally, uv plays well with everything I already use. Commands like uv pip install or uv pip sync work as expected, and it runs on macOS, Linux, and Windows without a hitch. This cross-platform reliability means I can adopt uv without worrying about breaking my existing workflow.

Installation & Getting Started

Getting started with uv is surprisingly easy. You can install it in multiple ways: via a standalone script, pip, or even pipx, depending on your preference. This flexibility makes it simple to adopt uv in any workflow without hassle.

The standalone script method is the fastest way to get up and running:

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

Alternatively, you can install via pip:

pip install uv

Or using pipx if you prefer isolating your CLI tools:

pipx install uv

Once installed, getting a new project up and running is straightforward. Here’s a quickstart example:

uv init myproject         # Initialize a new project
cd myproject
uv add requests           # Add a dependency
uv venv --python 3.12     # Create a virtual environment with a specific Python version
uv pip install flask      # Install additional packages inside the venv
uv build                  # Build the project into a package
uv publish                # Publish the package

Within a few commands, you have a fully set up Python project: dependencies installed, virtual environment ready, and even ready for packaging and publishing. uv makes the entire setup process seamless and efficient, which is why it’s quickly becoming a favorite for modern Python development.

Comparison with Other Tools

When I first started exploring uv, one of the things that immediately struck me was how it unifies workflows that are normally scattered across multiple tools. Traditionally, Python developers juggle pip, venv, poetry, and pipx depending on whether they’re managing dependencies, virtual environments, or CLI tools. Each has its strengths, but also friction points that slow down development.

With uv, I no longer feel like I’m switching hats between different tools. The speed gains are noticeable, especially when working on large projects or repeatedly installing dependencies. The unified toolchain means one command handles what previously required multiple tools (pip, virtualenv, pipx, and even twine).

The trade-off? Being a newer tool, uv still has a smaller ecosystem, and some IDEs don’t fully recognize its workflows yet. But for me, the efficiency and simplicity it brings to daily Python development outweigh those minor limitations.

Conclusion

Looking back at everything uv offers, what stands out most to me is how fast, unified, and modern it feels. From managing virtual environments to installing packages, running scripts, and publishing projects, it really streamlines workflows that used to feel fragmented and slow.

For anyone who spends time juggling pip, venv, poetry, or pipx, uv is worth a closer look. It’s cross-platform, handles multiple Python versions effortlessly, and generally reduces friction in daily development.

My advice: try it out on a small test project. Compare the experience against your current stack, you might be surprised at just how much time and hassle it can save. For me, switching even a few workflows to uv has already made Python development feel smoother and more enjoyable.

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