Hacker News Reader

Comment by mruts | Hacker News Reader

I whole heartedly agree. Python is garbage for data science. If an industrial grade NN library was written for it, plus some quant libraries, I think most people would switch.

I work in finance doing data science-y things and have yet to meet anyone who doesn’t think that Python is a pile of garbage.

People used to make the easy to learn argument, but Julia is even easier. And more elegant, extensible, and faster.

View on HN

> If an industrial grade NN library was written for it

Can you give tell us which language and industrial grade NN library you're using?

Because from where I'm sitting I see that Python is the only language that gets first grade support for both Tensorflow and Pytorch. It's so ahead for working with NN that it's not even close.

I was talking about Julia, not Python. Python obviously has industrial grade NN libraries.

Whenever I see the “I’ve never met x” argument, I’m always looking out for the catch. Because it’s a bad argument to begin with. But the catch is almost always in a situation where x is everywhere, and you would have to have your head willfully stuck in a hole in the ground to not see it.

And this is no exception.

You, uh, don't like PyTorch and TensorFlow? I can't tell if this is sarcastic.

They are written in C++.

Not sure how that's relevant. Everything is written in something else.

Python itself is written in C. The Julia github repo shows Julia 68.2%, C 16.3%, C++ 10.4%, Scheme 3.2%. R is a mix of C, C++, R and some Fortran I think...

It is relevant from the point of view of what a developer is able to achieve without being forced to drop down to a 2nd programming language, aka "2 language syndrome".

And how many Python libraries are just plain wrappers, not really written in Python.

I use TensorFlow from .NET ML and C++ API.

are you suggesting that data scientists use C++ for day to day work? those libraries have first-class wrappers in Python (there is R support, but not at the same level).

Having worked at CERN, many do in fact use C++ for day to day work, hence why CINT and ROOT exist.

However my point was that with Julia, those libraries would have been written in Julia.

All the Python libraries that one throws around for these use cases are C, C++ and Fortran libraries, that happen to have Python wrappers.

Any programming language can have wrappers for them, there is nothing written in Python per se.

I was talking about Julia, not Python. Python clearly has great NN libraries and great data science libraries.

I think he uses a calculator for that

Plus a good package manager, insanely good interop, one good ide, etc etc.

Reply on news.ycombinator.com