I would say, as someone who works on performance of pip, no one else was able to reproduce OPs severe performance issue, not saying it didn't happen, just it was an edge case on specific hardware (I am assuming it was this issue https://github.com/pypa/pip/issues/12314).
Since it was posted a lot of work was done on areas which likely caused performance problems, and I would expect in the latest version of pip to see at least a doubling in performance, e.g. I created a scenario similar to OPs that dropped from 266 seconds to 48 seconds on my machine, and more improvements have been made since then. However OP has never followed up to let us know if it improved.
Now, that's not to say you shouldn't use uv, it's performance is great. But just a lot of volunteer work has been put in over the last year (well before uv was announced) to improve the default Python package install performance. And one last thing:
> for a non-compiler language?
Installing packages from PyPI can involve compiling C, C++, Rust, etc. Python's packaging is very very flexible, and in lots of cases it can take a lot of time.
Since it was posted a lot of work was done on areas which likely caused performance problems, and I would expect in the latest version of pip to see at least a doubling in performance, e.g. I created a scenario similar to OPs that dropped from 266 seconds to 48 seconds on my machine, and more improvements have been made since then. However OP has never followed up to let us know if it improved.
Now, that's not to say you shouldn't use uv, it's performance is great. But just a lot of volunteer work has been put in over the last year (well before uv was announced) to improve the default Python package install performance. And one last thing:
> for a non-compiler language?
Installing packages from PyPI can involve compiling C, C++, Rust, etc. Python's packaging is very very flexible, and in lots of cases it can take a lot of time.