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Julia is definitely a fair counterpoint to my comment about C, but I don't think it really has comparable ubiquity to numpy + Python and C/C++ in the computatio

Julia is definitely a fair counterpoint to my comment about C, but I don't think it really has comparable ubiquity to numpy + Python and C/C++ in the computational science/numerical computing communities. What is nice about ubiquity is that if I need to use a rather esoteric numerical technique for research, odds are there are at least prototypes for it already made in numpy + Python or C/C++, if not a fully-fledged, well tested package for it. Julia might be catching up there. I hope so, because I do think my area of computational science would benefit from not only relying on 1 or 2 programming language ecosystems for 99% of all work.

dunefox 6y ago
> odds are there are at least prototypes for it already made in numpy + Python or C/C++, if not a fully-fledged, well tested package for it. Odds are that there is one in Julia as well - if not only in Julia. Also, with PyCall you can just seamlessly use any Python library. So, use Julia - the better language for scientific programming - and use Python libraries where needed. This is one of the reasons I'm investing time into Julia, especially for deep learning and natural language processing.