Did anyone thought of implementing Octave on top of Julia?

Apparently, a lot of the Octave/MATLAB features are already available in Julia, and implementing Octave language interpreter would allow to save a lot of time for both worlds. So basically, it will boil down to implement the Octave language parser, e.g. with Tokenize.jl, and some glue where functions are missing in Julia. The Octave syntax is defined in libinterp/parse-tree/oct-parse.yy in bison/flex format. It will allow seamlessly run the existing Octave and Matlab code, will simplify embedding the Julia functions, and reusing the reach infrastructure related to machine learning (at least compared to Octave one).

There was some project called MatlabCompat.jl, but it didn’t took off

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It requires someone who needs that badly enough to implement it. Do you need it badly enough?

I invented a torch. Now I just shine to another solar torch then I can see… Why not just the torch…

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This is a FAQ: https://docs.julialang.org/en/v1.4-dev/manual/faq/#Why-don’t-you-compile-Matlab/Python/R/…-code-to-Julia?-1

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