It is indeed one of the few existing languages appropriate for generic experimentation in numeric programming.
For example, computing the product of two matrices in C or Fortran is exactly as fast by writing three nested loops or by calling a library function. In python, julia, octave, etc, the difference is abysmal. This is a very sad state of affairs, that forces a mindset where you are allowed a limited toolset of fast operations and the rest are either slow or cumbersome. If you want to compute a variant of the matrix product using a slightly different formula, in Fortran it is trivial change, you just write the new formula inside the loop. But in python or julia you are stuck with either an unusably slow code or you have to write it in another language entirely.
"Vectorized" operations are cool, elegant, and beautiful. But they should not be the only tool available. As differential geometers often resort to coordinates to express their tensor operations, so should programmers be able to.