Comment by untrimmed 19 hours ago
As someone who has spent days wrestling with Python dependency hell just to get a model running, a simple cargo run feels like a dream. But I'm wondering, what was the most painful part of NOT having a framework? I'm betting my coffee money it was debugging the backpropagation logic.
I'm sure it's true and all. But I've been hearing the same claim about all those tools uv is intended to replace, for years now. And every time I try to run any of those, as someone who's not really a python coder, but can shit out scripts in it if needed and sometimes tries to run python software from github, it's been a complete clusterfuck.
So I guess what I'm wondering is, are you a python guy, or are you more like me? because for basically any of these tools, python people tell me "tool X solved all my problems" and people from my own cohort tell me "it doesn't really solve anything, it's still a mess".
If you are one of us, then I'm really listening.
I'm one of you.
I'm about the highest tier of package manager nerd you'll find out there, but despite all that, I've been struggling to create/run/manage venvs out there for ages. Always afraid of installing a pip package or some piece of python-based software (that might muck up Python versions).
I've been semi-friendly with Poetry already, but mostly because it was the best thing around at the time, and a step in the right direction.
uv has truely been a game changer. Try it out!
Don’t forget to schedule your colonoscopy as a Ruby guy
I'm (reluctantly) a python guy, and uv really is a much different experience for me than all the other tools. I've otherwise had much the same experience as you describe here. Maybe it's because `uv` is built in rust? ¯\_ (ツ)_/¯
But I'd also hesitate to say it "solves all my problems". There's plenty of python problems outside of the core focus of `uv`. For example, I think building a python package for distribution is still awkward and docs are not straightforward (for example, pointing to non-python files which I want to include was fairly annoying to figure out).
I’m a “Python guy” in that I write Python professionally, but also am like you in that I’ve been extremely underwhelmed by Portry/Pipenv/etc.
Python dependencies are still janky, but uv is a significant improvement over existing tools in both performance and ergonomics.
uv is great, but I think the real fix is just abandoning Python.
The culture that language maintains is rather hostile to maintainable development, easier to just switch to Rust and just write better code by default.
Every tool for the right job. If you are doing tons of scripting (for e.g. tests on platforms different than Rust), Python can be a solid valid alternative.
Also, tons of CAE platforms have Python bindings, so you are "forced" to work on Python. Sometimes the solution is not just "abandoning a language".
If it fits your purpose, knock yourself out, for others that may be reading: uv is great for Python dependency management on development, I still have to test it for deployment :)
>Every tool for the right job. If you are doing tons of scripting (for e.g. tests on platforms different than Rust), Python can be a solid valid alternative.
I'd say Go is a better alternative if you want to replace python scripting. Less friction and much faster compilation times than Rust.
There's not really another game in town if you want to do fast ML development :/
Dunno, almost all of the people I know anywhere in the ML space are on the C and Rust end of the spectrum.
Lack of types, lack of static analysis, lack of ... well, lack of everything Python doesn't provide and fights users on costs too much developer time. It is a net negative to continue pouring time and money into anything Python-based.
The sole exclusion I've seen to my social circle is those working at companies that don't directly do ML, but provide drivers/hardware/supporting software to ML people in academia, and have to try to fix their cursed shit for them.
Also, fwiw, there is no reason why Triton is Python. I dislike Triton for a lot of reasons, but its just a matmul kernel DSL, there is nothing inherent in it that has to be, or benefits from, being Python.... it takes DSL in, outputs shader text out, then has the vendor's API run it (ie, CUDA, ROCm, etc). It, too, would benefit from becoming Rust.
I know Python since version 1.6.
It is great for learning on how to program (BASIC replacement), OS scripting tasks as Perl replacement, and embedded scripting in GUI applications.
Additionally understand PYTHONPATH, and don't mess with anything else.
All the other stuff that is supposed to fix Python issues, I never bothered with them.
Thankfully, other languages are starting to also have bindings to the same C and C++ compute libraries.
abandoning Python for Rust in AI would cripple the field, not rescue it
the disease is the cargo cult addiction (which Rust is full of) to micro libraries, not the language that carries 90% of all peer reviewed papers, datasets, and models published in the last decade
every major breakthrough, from AlphaFold to Stable Diffusion, ships with a Python reference implementation because that is the language researchers can read, reproduce, and extend, remove Python and you erase the accumulated, executable knowledge of an entire discipline overnight, enforcing Rust would sabotage the field more than anything
on the topic of uv, it will do more harm than good by enabling and empowering cargo cults on a systemic level
the solution has always been education, teaching juniors to value simplicity, portability and maintainability
Nah, it would be like going from chemistry to chemical engineering. Doing chemical reactions in the lab by hand is great for learning but you aren't going to run a fleet of cars on hand made gas. Getting ML out of the lab and into production needs that same mental conversion from CS to SE.
Switching to uv made my python experience drastically better.
If something doesn't work or I'm still encountering any kind of error with uv, LLMs have gotten good enough that I can just copy / paste the error and I'm very likely to zero-in on a working solution after a few iterations.
Sometimes it's a bit confusing figuring out how to run open source AI-related python projects, but the combination of uv and iterating on any errors with an LLM has so far been able to resolve all the issues I've experienced.
uv has been amazing for me. It just works, and it works fast.
So in 2025, in Python, if I depend on two packages. A and B, and they both depend on different, API-incompatible or behavior-incompatible (or both) versions of C, that won't be an issue?
That's not my experience and e.g. uv hasn't helped me with that. I believe this is an issue with Python itself?
If parent was saying something "grossly ridiculous" I must be doing something wrong too. And I'm happy to hear what as that would lower the pain of using Python.
I.e. this was assumably true three years ago:
https://stackoverflow.com/questions/70828570/what-if-two-pyt...
Well, first, this a purposefully contrived example, that pretty much does not happen in real life scenarios. So you're pretty much acknowledging that there is no real problem by having to resort to such length.
Second, what exactly would you like to happen in that instance? You want to have, in a single project, the same library but at different and conflicting versions. The only way to solve that is to disambiguate, per call site, each use of said library. And guess what, that problem exist and was solved 30 years ago by simply providing different package names for different major version. You want to use both gtk 1 and gtk 2 ? Well you have the "gtk" and "gtk2" package, done, disambiguated. I don't think there is any package manager out there providing "gtk" and having version 1 and 2, it's just "gtk" and "gtk2".
Now we could design a solution around that I guess, nothing is impossible in this brave new world of programing, but that seems like a wasted effort for not-a-problem.
Maybe this doesn’t happen in Python, but I find that hard to believe. This is a common thing in Rust, where cargo does support compiling with multiple versions of the same crate. If I have dependency X that depends on version 1.x of crate Z, and dependency Y which depends on version 2.x, cargo will compile BOTH versions of crate Y, and handle the magic of linking dependencies X and Y to their own, different copies of this common dependency.
Yes, Rust can do this. I know Ruby cannot, and I believe Python may not either, but I am less sure about it because I’m less good with Python’s semantics here, but I’d believe your parent.
I am not even thinking of `uv`, but rather of pyproject.toml, and the various improvements as to how dependencies are declared and resolved. You don't get much simpler than a toml file listing your dependencies and constraints, along with a lock file.
Also let's keep middle school taunts at home.
lowkey ppl who praise cargo seem to have no idea of the tradeoffs involved in dependency management
the difficulty of including a dependency should be proportional to the risk you're taking on, meaning it shouldn't be as difficult as it in, say, C where every other library is continually reinventing the same 5 utilities, but also not as easy as it is with npm or cargo, because you get insane dependency clutter, and all the related issues like security, build times, etc
how good a build system isn't equivalent of how easy it is include a dependency, while modern languages should have a consistent build system, but having a centralised package repository that anyone freely pull to/from, and having those dependencies freely take on any number of other dependencies is a bad way to handle dependencies
> lowkey ppl who praise cargo seem to have no idea
Way to go on insulting people on HN. Cargo is literally the reason why people coming to Rust from languages like C++ where the lack of standardized tooling is giant glaring bomb crater that poses burden on people every single time they need to do some basic things (like for example version upgrades).
Example:
i'm saying that ease of dependency inclusion should not be a main criterion for evaluating how good a build system is, not that it isn't the main criterion for many people...
like the entire point of my comment is that people have misguided criteria for evaluating build systems, and your comment seems to just affirm this?
Dependency management should most definitely be one of the main criteria for evaluating how good a build system is. What's misguided is intentionally opting for worse dependency management in an attempt to solve a people problem, i.e. being careless about adding dependencies to your project in circumstances when you should be careful.
> like the entire point of my comment is that people have misguided criteria for evaluating build systems, and your comment seems to just affirm this?
I think dev_l1x_be's comment is meant to imply that your believe about people having misguided criteria [for evaluation build systems] is itself misguided, and that your favored approach [that the difficulty of including a dependency should be proportional to the risk you're taking on] is also misguided.
my thesis is that negative externalities of build systems are important and i don't know how to convince of importance of externalities someone whose value system is built specifically on ignoring externalities and only factoring in immediate convenience...
Security is another problem, and should be tackled systematically. Artificially making dependency inclusion hard is not it and is detrimental to the more casual use cases.
> but having a centralised package repository that anyone freely pull to/from, and having those dependencies freely take on any number of other dependencies is a bad way to handle dependencies
So put a slim layer of enforcement to enact those policies on top? Who's stopping you from doing that?
any language that has a standardised build system (virtually every language nowadays?), but doesn't have a centralised package repository, such that including a dependency is seamless, but takes a bit of time and intent
i like how zig does this, and the creator of odin has a whole talk where he basically uses the same arguments as my original comment to reason why odin doesn't have a package manager
i just realised that my comment sounds like it's praising python's package management since it's often so inconvenient to use, i want to mention that that wasn't my intended point, python's package management contains the worst aspects from both words: being centralised AND horrible to use lol
my mistake :)
> the difficulty of including a dependency should be proportional to the risk you're taking on
Why? Dependency hell is an unsolvable problem. Might as well make it easier to evaluate the tradeoff between dependencies and productivity. You can always arbitrarily ban dependencies.
Is your argument that python's package management & ecosystem is bad by design - to increase security?
In my experience it's just bugs and poor decision making on the maintainers (eg. pytorch dropping support for intel mac, leftpad in node) or on the language and package manager developers side (py2->3, commonjs, esm, go not having a package manager, etc).
Cargo has less friction than pypi and npm. npm has less friction than pypi.
And yet, you just need to compromise one lone, unpaid maintainer to wreck the security of the ecosystem.
Have you tried uv [1]? It has removed 90% of the pain of running python projects for me.
[1] https://github.com/astral-sh/uv