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Comment by kanox | Hacker News Reader

Somewhat offtopic but it is strange that special-purpose languages for scientific computing even exist. It seems far saner to just have these tools available as a set of libraries for a general purpose programming language and indeed the world seems to be heading that way with python as the chosen language.

Maybe when matlab and mathematica were first created the existing dynamic languages were not very good?

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It is rare for general purpose languages to make matrices as easy to manipulate as MATLAB does. Maybe Julia will fill this need, once it becomes more popular. Right now, for fast coding involving matrices (not necessarily fast running time, mind you), MATLAB takes the cake.

Fortran was released in 1957 as the first compiled language. Guess what it was for ... scientific computing.

I don't think that Fortran was the first compiled language. Wikipedia says the first language to be compiled was Autocode for the Mark 1.

https://en.wikipedia.org/wiki/Autocode

> Maybe when matlab and mathematica were first created the existing dynamic languages were not very good?

It had less to do with the languages and more to do with the libraries. Would you use Python over Matlab if numpy and scikit learn did not exist?

And even today if you have to do a lot of heavy duty or specialized statistics, does Python match R, Matlab or SPSS libraries?

Why does it seem more sane to have libraries instead of specialized languages?

Even with Python and R's mathematical ecosystem, they don't replicate the sheer breadth and depth of specialized tools like Mathematica and MATLAB.

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