Comparing uv and pip

00:00 You’ll start by taking a look at a high-level comparison between uv and pip, so that you get the sense for their similarities and differences.

00:08 And then in the upcoming lessons, you’ll dive deep into each of these differences or similarities to really understand what they mean and the practical implications of them.

00:19 So first and foremost, this is going to explain a lot of the upcoming features and differences. pip is backed by PyPA, which stands for the Python Packaging Authority, and uv is backed by Astral. While the first is a working group from the Python Software Foundation, the second is a private company.

00:39 So this is a key difference between these two tools. Because of that, pip is available out of the box. Typically, if you install Python from an official installer, you will have pip automatically available, whereas uv always needs to be installed.

00:55 You always need to go through an extra installation step to get uv in your computer.

01:02 Now, uv is focused on providing fast installation speeds. Whatever fast means, it’s going to be dependent on your machine and the packages you’re installing.

01:11 But typically, it’s faster than installing the same packages on the same machine with pip. So that’s why you see “Fast” with asterisks and “Slow” with asterisk in the table.

01:23 Now, related to installing and uninstalling dependencies, uv will remove your transitive dependencies, and you’ll see what this means exactly in one of the upcoming lessons, whereas pip does not.

01:36 And at the same time, uv has out-of-the-box support for reproducible installs, whereas pip does not. You can get some third-party tools to complement pip in this regard, but by default, out of the box, pip does not do that.

01:50 As far as the ecosystem and the maturity of the tool goes, uv is a fairly recent tool. uv is growing in adoption, and the Python community is showing interest in uv.

02:01 It is still a very new tool, whereas pip has been around for what feels like essentially forever. So it is a very mature tool, and the ecosystem is very used to pip and knows how to integrate and work with pip.

02:14 As far as the license goes, both tools are open source, both have the MIT License. But one key difference that might come into play is that whereas pip is written in Python, uv is written in Rust.

02:28 And typically, Python developers know how to write Python. That is why they are Python developers, but they do not necessarily know how to write Rust. So this might be something to take into account when you consider these two tools as your two options.

02:43 So this is a very high-level comparison of these tools. And in the next lesson, you’re going to understand the impacts of uv and pip having two very different supporting organizations.