At the end of the day it should be to everyone clear, that *raw loops is nothing which increases readability* nor is it an anchor of good code. Years of C++ development (a bit more than in julia) showed that raw loops don't go hand in hand with understanding. (My advice to students was to avoid raw loops, whenever possible but use STL)
My opinion to this topic is, it is paradoxial to make users believe it is fully dynamic but stop at the most common use-case (the case where you want to collect easily results with shaping without type information and such) and state its slowness, since it is vectorised. If you think about what vectorisation is and to support the syntax plus not to forget to mention it is slow is rather confusing plus to support on the other hand broadcasting through operators. So where is the line? When does something become slow? To have a spot on speed is fulminant, but to fall back into bad coding practice? (Vectorisation in numpy did make sense and was a major key to success for scientific python). Why I chose Julia? Because it is clean and I lived with Mathematica for 12 years. Stop the speed comparison. Stop to avoid implementing certain algorithm's because they are known as bad performers which could shed a wrong light to the uberperforming julia. Let it grow. I want to go with julia since...it has taste/elegance. I favour especially the latter. Speed? I can go back to C++/Fortran or use numba on python. So why choosing a language no one knows and no one wants to spend money on it? Because I want to. I luv the design. I adore speed, but never was a major issue on choosing a language. (was lisp/matlab/mathematica/python?) I am a 14 years Mathematica user. Speed? I agree, this has nothing to do with the original OP's question, but was something I've had in my head since I've started to observe this list. Stefan
