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It's the killer language in scientific computing I'd say, having used both Python and Matlab. The open source nature/libraries and being a more fully-powered programming language (expressive object system) make it better.

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As someone who does a lot of scientific computing in Python, I'd probably recommend learning Julia as the 'killer language' if scientific computing is the main reason you want to learn programming.

Pythons strength comes from being pretty good at scientific computing, and equally good at just about everything else.

I haven't tried Julia, it sounds like it could be better in the long run but I'd be shocked if the ecosystem is equivalent already.

Luckily, you can call many Python libraries directly from your Julia code: https://github.com/JuliaPy/PyCall.jl

Yea, PyCall makes it trivial to write a quick Julia wrapper around a python library. It's also really handy for porting python code to Julia. Start by wrapping all your existing functions with PyCall and then replace them one by one with Julia functions.

Was going to say that Julia might be the long term best open source replacement for closed source scientific computing (Matlab, Mathematica...etc). In some ways it is already just as good, but in others, it has a long way to go. From a speed perspective, it is top notch.

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