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I learned C because of classes in MPI and I tried to go back to it after years of Python and MATLAB but the amount of boilerplate code and the workflow slowed m
by ChrisRackauckas 9y ago
I learned C because of classes in MPI and I tried to go back to it after years of Python and MATLAB but the amount of boilerplate code and the workflow slowed me down too much. C++ is definitely a fine choice if you are a great programmer but I don't find it easy at all to prototype or maintain codebases in languages like that. YMMV
- ChrisRackauckas 9y agoI would say though that if I didn't go the Julia route I would probably be using C++. Again, in the article I wrote that for package development, I see Julia as a more productive C++ as opposed to a faster Python. I'm using it in a way that is all based around generic algorithms that can statically compile well, so it's essentially C++ template magic but with a lot less code (no headers) and I can prototype separate implementations in the REPL as I go (in Juno, highlight and do Ctrl+enter and it replaces the function in the package with the new definition). I think the other clear choice in this space is actually D. But between Julia, C++, and D, I like Julia because I found it really easy to program things and have it work the first time.