On Sat, 26 Feb 2022 at 05:49, Richard Damon <rich...@damon-family.org> wrote: > > On 2/25/22 4:12 AM, BELAHCENE Abdelkader wrote: > > Hi, > > a lot of people think that C (or C++) is faster than python, yes I agree, > > but I think that's not the case with numpy, I believe numpy is faster than > > C, at least in some cases. > > > My understanding is that numpy is written in C, so for it to be faster > than C, you are saying that C is faster that C.
Fortran actually, but ultimately, they both get compiled to machine code. Really, what the OP has demonstrated is that good, well-written code called from bad code produces meaningless numbers that are not the same as bad code written in C. I can't even use that to prove that good code is faster than bad code, since the measurements aren't comparable; but if that were what was being measured, it wouldn't be very surprising. To do a fair comparison of C and Numpy, you'd have to: 1) Use the same type of timer 2) Use the same algorithm (unless you're benchmarking "naive C code" against "well-written Fortran code") 3) Have comparable levels of compile-time optimization 4) Cope with the vagaries of CPU caching 5) Ensure that the same data types are being used everywhere 6) Probably several other things that I didn't think of. The precise way you run the test could easily skew it by orders of magnitude in either direction. > The key point is that numpy was written by skilled programmers who > carefully optimized their code to be as fast as possible for the major > cases. Thus it is quite possible for the numpy code to be faster in C > than code written by a person without that level of care and effort. This is clearly true. ChrisA -- https://mail.python.org/mailman/listinfo/python-list
