I'm done pretending this is a "right tools for the right job" kind of thing, there's wrong people in the right job, and they only know python. If no one self-writes code anymore anyway, at least use a language that isn't a clusterfuck of bad design decisions, and has 1 trillion lines of code in the collective memory of people who don't know what a stack is.
I can get behind the idea that LLM's probably don't need a language designed for humans if humans arent writing it, but the rest of this is just daft. Pythons popularity isn't just pure luck, in fact its only been in recent years that the tooling has caught up to the point where its as easy to setup as it is to write, which should really tell you something if people persevered with it anyway.
I'm sorry your favourite language doesnt have the recognition it so rightfully deserves, but reducing python to just "stupid language for stupid people" is, well, stupid
Speaking as a grey beard myself, I think its safe to say that the grey beards among us will always deride those who didn't have to work as hard as they did.
I used to do backend development in superior languages, and sometimes do hobby frontend in superior languages, but my work is Python now. And it kind of has to be Python: we do machine learning, and I work with GDAL and PDAL and all these other weird libraries and everything has Python bindings! I search for "coherent point drift" and of course there's a Python library.
The superior languages I mentioned... perhaps they have like a library for JSON encoding and decoding. You need anything else? Great, now you're a library author and maintainer!
To make it good, you need to review and interate.
https://peps.python.org/pep-0723/
* disclosure: We are a commercial client of astral.sh
Circa 2017 I was working on systems that were complex enough that pip couldn't build them and after I got to the bottom of it I knew it not my fault but it was the fault of pip.
I built a system which could build usable environments out of pre-built wheels and sketched out the design of a system that was roughly 'uv but written in Python' but saw two problems: (1) a Python dependent system can be destroyed by people messing with Python environments, like my experience is that my poetry gets trashed every six months or so and (2) there was just no awareness by the 'one tiny project on your machine that pips in four packages' people that there was a correctness problem at all and everybody else was blaming themselves for a problem and didn't have a clear understanding of what was wrong with pip or what a correct model for managing python dependencies is (short answer: see maven) or that a 100% correct model was even possible and that we'd have to always settle for a 97% model. The politics looked intractable so I gave up.
Now written in rust, uv evaded the bootstrap problem and it dealt with the adoption problem by targeting 'speed' as people would see the value in that even if they didn't see the value in 'correctness'. My system would have been faster than pip because it would have kept a cache, but uv is faster still.
I have used them all and UV is the only one that actually solves the problem.
It’s insane that people would suggest that Python can go back.
I always looked down on the Java ecosystem but if it turns out Maven had a better story all along and we all overlooked it, that's wild.
> The politics looked intractable so I gave up.
So yeah, this is your actual problem. (Don’t worry, I’m in the same camp here.)
Having a static binary makes distribution way simplier. There are a bunch of ways you could try to achive something like in python but it would be significantly larger.
Performance-wise writing it in python would have heavy startup overhead and wouldn't be able to get close to the same level of performance.
Obviously you could achive the same thing in many other languages, but rust ends up being a really good fit for making a small static binary for this workload of network heavy, IO-bound, async/threading friendly with the occasional bit of CPU heavy work.
you mean pdm?
Poetry having users isn’t the metric for success. pip having way less users is.
Poetry's CLI would often, for me, just fall over and crash. Crashing a lot is not a fundamental problem in the sense you can fix the bugs, but hey I'm not hitting uv crashes.
pipenv was even worse in terms of just hanging during package resolution. Tools that hang are not tools you want in a CI pipeline!
The end result: `uv run` I expect to work. `pipenv` or `poetry` calls I have to assume don't work, have to put retries into CI pipelines and things like that.
But yes, in terms of user interface they are pretty similar. UV performance really does make the difference.
`uv run` a .py with inline script metadata has all the deps installed and your script running in a venv while poetry is still deciding to resolve...
(I'm not doing this to be a dick, I genuinely want to know what the use case is)
Things got bearable with virtualenv/virtualenv wrappers, but it was never what I would call great. Pip was always painful, and slow. I never looked forward to using them - and every time I worked on a new system - the amount of finaggling I had to do to avoid problems, and the amount of time I spent supporting other people who had problems was significant.
The day I first used uv (about is as memorable to me as the the day I first started using python (roughly 2004) - everything changed.
I've used uv pretty much every single day since then and the joy has never left. Every operation is twitch fast. There has never once been any issues. Combined with direnv - I can create projects/venvs on the fly so quickly I don't even bother using it's various affordances to run projects without a venv.
To put it succinctly - uv gives me two things.
One - zero messing around with virtualenvwrappers and friends. For whatever reason, I've never once run into an error like "virtualenvwrapper.sh: There was a problem running the initialization hooks."
Two - fast. It may be the fastest software I've ever used. Everything is instant - so you never experience any type of cognitive distraction when creating a python project and diving into anything - you think it - and it's done. I genuinely look forward to uv pip install - even when it's not already in cache - the parallel download is epically fast - always a joy.
But - neither the speed nor constant issues with pip/virtualenvwrappers are really a function of the OS/File System.
A frequent theme in this thread (probably most clearly described in https://news.ycombinator.com/item?id=47444936) is that relying on your Python Environment to manager your Python Environment - always ends up in pain. Poetry had this issue as well.
One of the key architectural decisions of Astral was to write the Python Environment Management tooling in rust - so that it could never footgun itself.
It also benefited from very enlightened engineering decisions described here: https://nesbitt.io/2025/12/26/how-uv-got-so-fast.html
You can run a script with a one liner and it will automatically get you the same python and venv and everything as whoever distributed the python code, in milliseconds if the packages are already cached on your local computer.
Very easy to get going without even knowing what a venv or pypi or anything is.
If you are already an expert you get “faster simpler tooling” and if you are a complete beginner it’s “easy peasy lemon squeezy”.
it just works. i'm not sure how else to describe it other than less faffing about. it just does the right thing, every time. there's a tiny learning curve (mostly unlearning bad or redundant habits), but once you know how to wield it, it's a one stop shop.
and as mentioned, it's crazy fast.
You should really qualify that statement, it implies that the Python ecosystem is bearable.
See the point ?
...and then I’ve read the rest of your comment. Please do go read the HN guidelines.
