If someone wants to do the kinds of computations done by NumPy, what's relevant is how fast that actual practice is. Not some stupid alternative implementation

If someone wants to do the kinds of computations done by NumPy, what's relevant is how fast that actual practice is. Not some stupid alternative implementation intended to show that Python is slow, but which nobody would ever actually use. In other words, it's nonsense to discard Python with NumPy as an option for fast computations just because we can imagine an imaginary world where NumPy was written differently, purely to penalize this environment for having used more than one language. To be honest, we should benchmark what we actually have, not imaginary made-up handicapped versions of the things we are judging.