alt Hacker NewsI thought this was going to be a longer rant about how python needs to... Go away. Which, as a long time python programmer and contributor, and at one time avid proponent of the language, I would entertain the suggestion. I think all of ML being in Python is a collosal mistake that we'll pay for for years.
The main reasons being it is slow, its type system is significantly harder to use than other languages, and it's hard to distribute. The only reason to use it is inertia. Obviously inertia can be sufficient for many reasons, but I would like to see the industry consider python last, and instead consider typescript, go, or rust (depending on use case) as a best practice. Python would be considered deprecated and only used for existing codebases like pytorch. Why would you write a web app in Python? Types are terrible, it's slow. There are way better alternatives.
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Typescript?
Why replace a nice language like python with anything coming out of javascript?
I'd love to replace Python with something simple, expressive, and strongly typed that compiles to native code. I have a habit of building little CLI tools as conveniences for working with internal APIs, and you wouldn't think you could tell a performance difference between Go and Python for something like that, but you can. After a year or so of writing these tools in Go, I went back to Python because the LOC difference is stark, but every time I run one of them I wish it was written in Go.
(OCaml is probably what I'm looking for, but I'm having a hard time getting motivated to tackle it, because I dread dealing with the tooling and dependency management of a 20th century language from academia.)
"> I think all of ML being in Python is a colossal mistake that we'll pay for for years.
Market pressure. Early ML frameworks were in Lisp, then eventually Lua with Torch, but demand dictated the choice of Python because "it's simple" even if the result is cobbled together.
Lisp is arguably still the most suitable language for neural networks for a lot of reasons beyond the scope of this post, but the tooling is missing. I’m developing such a framework right now, though I have no illusions that many will adopt it. Python may not be elegant or efficient, but it's simple, and that's what people want.
It’s especially frustrating that dependency hell seems to be embedded in the Python culture. The amount of “oh no this lib will only work with Python 3.10+ and a slew of other libs at random versions we won’t bother to tell you” while some other lib that it depends on will only work on “3.8.56z but not if you look at it funny and only if you say pretty please” is maddening. Semver is apparently not standard practice either.
I am probably biased against Python, so take this opinion with a grain of salt, but it feels to me like a whole ecosystem of amateur software devs (but professional ML-engineers, data scientists etc) cobbling together something that barely works.
I’m old enough at this point that I remember the whole old guard of software engineers falling over themselves to hate on JS and Node, call the ecosystem immature, and be quick to point out how that is not “real” software. But in the past 10-15 years it appears JS and Node got their shit together, while Python is still completely and utterly stuck in managing dependencies and environments like it is 2012. And if you ask professional Pythonistas about this, you always get an answer like “oh it’s actually really easy, you must not have taken the time to really look at it, because Python is easy, it’s just pseudocode look how amazing it all is”
I really wish ML hadn’t standarized on Python. As a user of ML tools ans frameworks but not a fulltime ML engineer it just constant pain.
I swear the only the people who care about Python types are on Hacker News comments. I've never actually worked with or met someone who cared so much about it, and the ones that care at all seem just fine with type hints.
I think all of ML being in Python is a colossal mistake that we'll pay for for years.
If ML fulfills its promise, it won't matter in the least what language the code is/was written in.
If it doesn't, it won't matter anyway.
How much does python really impact ml? All of the libraries are wrappers around C code that uses gpus any way, it's distributed and inference can be written in faster languages for serving anyway?
> I think all of ML being in Python is a collosal mistake that we'll pay for for years.
> The main reasons being it is slow, <snip>, and it's hard to distribute.
Don't forget that Python consumes approximately 70x more power when compared to C.
This is a needlessly dismissive and narrow-minded attitude. Have you ever tried to use FastAPI?
100%.
With that said... there is a reason why ML went with Python. GPU programming requires C-based libraries. NodeJS does not have a good FFI story, and neither does Rust or Go. Yes, there's support, but Python's FFI support is actually better here. Zig is too immature here.
The world deserves a Python-like language with a better type system, a better distribution system, and not nearly as much dynamism footguns / rope for people to hang themselves with.