Exactly, that's why I think Julia is a good idea.
For scientific users used to R or Python, the performance should knock their socks off. (But users doing their work in C, C++ or Fortran will probably see little or no improvement).
For scientific users used to R or Python, the performance should knock their socks off. (But users doing their work in C, C++ or Fortran will probably see little or no improvement).
The question really is the converse ... given how deft Julia is with general programming as well as numerically intensive programming, do you really need Python + numpy(C).
There are many things I hate about MATLAB, having matrices built into the syntax is nice.