When it comes to Python package managers, the choice often comes down to uv vs pip. You may choose pip for out-of-the-box availability, broad compatibility, and reliable ecosystem support. In contrast, uv is worth considering if you prioritize fast installs, reproducible environments, and clean uninstall behavior, or if you want to streamline workflows for new projects.
In this tutorial, you’ll compare both tools. To keep this comparison meaningful, you’ll focus on the overlapping features, primarily package installation and dependency management. The decision table below can help you quickly choose between the two:
| Use Case | uv |
pip |
|---|---|---|
| You need a tool with reliable ecosystem support | — | ✅ |
| You need reproducible, locked environments | ✅ | — |
Choosing the right package installer can greatly affect your workflow as a Python developer. In this tutorial, you’ll compare uv and pip, explore their overlapping features, and learn how to pick the right tool for your project’s goals.
Get Your Cheat Sheet: Click here to download the uv vs pip cheat sheet that will help you decide which tool to use.
Take the Quiz: Test your knowledge with our interactive “uv vs pip: Managing Python Packages and Dependencies” quiz. You’ll receive a score upon completion to help you track your learning progress:
Interactive Quiz
uv vs pip: Managing Python Packages and DependenciesTest your knowledge of uv vs pip as Python package managers and learn how to pick the right tool for speed, reproducibility, and compatibility.
Metrics Comparison: uv vs pip
To help you quickly see where uv and pip differ, the table below summarizes their strengths and trade-offs in package installation and dependency management:
| Metric | uv |
pip |
|---|---|---|
| Out-of-the-Box Availability | No | Yes |
| Package installation speed | Installs JupyterLab in 2.618 seconds | Installs JupyterLab in 21.409 seconds |
| Reproducible installs | Supports reproducible installs based on native locking | Supports requirements.txt and needs pip-tools for reproducibility |
| Removal of transitive dependencies | Yes | No |
| Maturity and ecosystem support | New and growing, adoption increasing | Mature, standard tool in the Python ecosystem |
| Licensing | MIT license | MIT license |
| Supporting organization | Astral, a private company focused on high-performance developer tools for Python | Python Packaging Authority (PyPA), an official part of the Python Software Foundation (PSF) |
After this quick summary, you’ll run a more detailed analysis to learn more about the intricacies of each specific metric or feature.
Note: To learn more about pip and uv in general, you can check out these tutorials:
In the following sections, you’ll explore these metrics one by one and run a few benchmarks to help you compare both tools and decide which one better suits your specific needs.
Out-of-the-Box Availability
One big reason pip remains dominant is that it ships with Python. This means that if you install Python with the official CPython installer, then you’ll have pip available out of the box and can use it to install packages with no extra step:
$ python -m pip install requests
Once you’ve installed Python, you can use pip immediately without installing additional tools. This is convenient when you don’t have the appropriate permissions to install new software on your work computer.
Note: On Ubuntu and Debian, the default Python installation often includes the python3 package, but may not include pip. If it’s missing, then you can install it by running sudo apt install python3-pip in your terminal window.
On the other hand, uv requires an extra installation step. You can install it using the standalone installer by running the command below:
This additional setup might not be a problem for you, but it can be a blocker if you don’t have the appropriate permissions to install apps in your working environment. Fortunately, uv has other installation options that you can use to install it in your user space.
Package Installation Speed
Here’s where uv really shines compared to pip. Written in Rust and designed for speed, uv can install packages faster than pip. This is especially true when you’re working on projects with large dependency trees.
Coming up next, you’ll see how uv and pip compare for installing packages and managing dependencies.
