you say "I'm against it creeping into an existing eco-system for no reason.", while you ignore that there is at least one good reason: A lot better performance.
The 10x performance wasn't mentioned in the article at all except the title.
I watched the video and he does mention it going from 30s to 3s when switching from a requirements.txt approach to a uv based approach. No comparison was done against poetry.
I am unable to reproduce these results.
I just copied his dependencies from the pyproject.toml file into a new poetry project. I ran `poetry install` from within Docker (to avoid using my local cache) `docker run --rm -it -v `pwd`:/work python:3.13 /bin/bash` and it took 3.7s
I did the same with an empty repo and a requirements.txt file and it took 8.1s.
I also did through `uv` and it took 2.1s.
Better performance?, sure.
A lot better performence?, I can't say that with the numbers I got.
10x performance?... absolutely not.
Also, this isn't a major part of anybody's workflow. Docker builds happen typically on release. Maybe when running tests during CI/CD after the majority of work has been done locally.
I agree it would be better if it was in Python but pypa did not step up, for decades! On the other hand, it is not powershell or ruby, it is a single deployed executable that works. I find that acceptable if not perfect.
There are cases where single-threaded Rust and C are faster than each other, though usually only by single-digit percentages. But Rust is so much easier to parallelize than C that it isn't even funny.
