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by Alexander-Barth 186 days ago
I wish you all the best luck with your product!

Unfortunately, mathworks is a quite litigious company. I guess you are aware of mathworks versus AccelerEyes (now makers of ArrayFire) or Comsol.

For our department, we mostly stop to use MATLAB about 7 years ago, migrating to python, R or Julia. Julia fits the "executable math" quite well for me.
1 comments
fluidcruft 186 days ago
All anyone really needs is seamless integration of Julia with python. Instead everyone seems to be rewriting python into rust.
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FacelessJim 185 days ago
Checkout PythonCall.jl and juliacall (on the python side). Not to mention that now you can literally write python wrappers of Julia compiled libraries like you would c++ ones.
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fluidcruft 185 days ago
I will, thanks.

> you can literally write python wrappers of Julia compiled libraries like you would c++ ones

Yes, please. What do I google? Why can't julia compile down to a module easily?

No offense but once you learn to mentally translate between whiteboard math and numpy... it's really not that hard. And if you were used to Matlab before Mathworks added a jit you were doing the same translation to vectored operations because loops are dog slow in Matlab (coincidentally Octave is so much better than Matlab syntax wise).

And again python has numba and maybe mojo, etc. Because julia refused to fill the gap. I don't understand why there's so much friction between julia and python. You should be able to trivially throw a numpy array at julia and get a result back. I don't think the python side of this is holding things back. At least back in the day there was a very anti-python vibe from julia and the insistence that all the things should be re-implemented in julia (webservers etc) because julia was out to prove it was more than a numerical language. I don't know if that's changed but I doubt it. Holy wars don't build communities well.

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markkitti 182 days ago
>> you can literally write python wrappers of Julia compiled libraries like you would c++ ones. > Yes, please. What do I google? Why can't julia compile down to a module easily?

Try JuliaC for compiling shared libraries if that is what you mean by a "module": https://github.com/JuliaLang/JuliaC.jl

That said Julia's original design focused on just-in-time compilation rather than ahead-of-time compilation, so the AOT process is still rough.

> I don't understand why there's so much friction between julia and python. You should be able to trivially throw a numpy array at julia and get a result back.

You can throw a numpy array at Julia and get a result back. See https://juliapy.github.io/PythonCall.jl/stable/juliacall/

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