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I don’t find that to be true with Julia. Keep in mind that Julia is intended to not only replace python and R but also C++ in a science setting. The academic pr

I don’t find that to be true with Julia. Keep in mind that Julia is intended to not only replace python and R but also C++ in a science setting. The academic programmers who write the high performance code parts usually do this in C/C++ and Fortran and thus tend to be quite familiar with a lot of low level computer science stuff. Looking at generated assembly code for a Julia function is a pretty normal thing to do. I am an old C/C++ developer and find myself very much at home with Julia. Sure I have used Python and Ruby before but those always make decisions around memory layout and code generation inaccessible. Thinking about Julia as yet another Python, R, Ruby or a JavaScript is just wrong. It doesn’t really fit existing categories well.

krapht 5y ago
I mean, the best way to think about it is as a replacement for MATLAB, except with better support for general purpose computing. MATLAB the language syntax is optimized for double precision matrix math - but MATLAB is interpreted with a JIT and extremely productive IDE, so actually really easy to use, except for the part where it costs $2000 per toolbox per year. It also interops fairly seamlessly with Java since it runs on the JVM. Mathworks: the company that I wouldn't pay paying money to, if it wasn't such a ridiculously large sum. I don't have any issue paying for Jetbrains IDEs, but it's an order of magnitude smaller than Mathwork's yearly take.