
Reddit AMA: We are the creators of the Julia programming language - yarapavan
https://www.reddit.com/r/IAmA/comments/hyva5n/we_are_the_creators_of_the_julia_programming/
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smabie
I've recently been using Julia to analyze around 180gb of CSV's and it's been
really nice. The problem with Python (besides the sucky language) is that it's
so slow you have to work pretty hard to make sure all your operations are
calling into some C lib.

Trying to call a python function over 5m pandas rows? Forget about it, never
going to happen. Anything that requires an if statement, never going to
happen. Often you can express what you're trying to do in terms of vectorized
numpy/pandas operations, but it takes some work.

Julia simply doesn't have this problem and it's a game changer. By and large,
everything is reasonably fast and the compiler does a good job. Julia has made
scientific computing so much more accessible than Python ever could. Anyone
can publish a library and even if the code is rough, it'll usually be fast
enough to be useful. With Python, unless you're a professional software
engineer and willing to write in C, forget about sharing a new model or
numerical technique with anyone else.

I think the lack of classes and strong support for function polymorphism has
made Julia code pretty easy to write, easy to read, and very powerful. In
Python each library is its own little world and you can't really mix and match
them in a meaningful way. In Julia you can leverage multiple libraries in new
and unexpected ways.

Perhaps the best part of Julia is the broadcasting operator (.) that allows
any function to be easily mapped onto a collection. It's almost like using an
array language like k or j! Also, macros.

And with the seamless Python interop, Julia should be your goto pick for any
scientific computing project. It's even starting to replace C and Fortran,
which I think is pretty exciting. The future couldn't be brighter for Julia!

