On Fri, 25 Feb 2022 at 23:13, Barry <ba...@barrys-emacs.org> wrote: > > > On 25 Feb 2022, at 23:00, Richard Damon <rich...@damon-family.org> wrote: > > > > On 2/25/22 2:47 PM, Chris Angelico wrote: > >>> 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. > > > > Looking at the Github repo I see: > > > > Languages: > > Python. 62.5% > > C 35.3% > > C++. 1.0% > > Cython. 0.9% > > Shell. 0.2% > > Fortran. 0.1% > > I assume that this is just for bumpy and not for all its dependencies. > That will add a lot of Fortran and c++ I expect.
NumPy links with BLAS/LAPACK that will do the heavy lifting for common linear algebra operations. Multiple different BLAS libraries can be used with NumPy and those libraries might be written in Fortran and might also involve some hand-crafted assembly for particular architectures. Some explanation of NumPy's BLAS/LAPACK support is here: https://numpy.org/devdocs/user/building.html By default if you install NumPy from conda (or at least if you install the Anaconda distribution) then I think that NumPy will use the Intel MKL library: https://en.wikipedia.org/wiki/Math_Kernel_Library As I understand it the core of MKL is Fortran and is compiled with Intel's ifortran compiler but some parts might be C/C++. MKL is also the same library that is used by Matlab for its own heavy lifting. It's not sufficiently free to be used in NumPy's PyPI wheels though. If you install the precompiled NumPy wheels with pip from PyPI then I think those are statically linked with OpenBLAS: https://github.com/xianyi/OpenBLAS Again I think the core of OpenBLAS is Fortran but there's some C in there. In the pre-wheel days the situation was that NumPy provided installer files for Windows that would give binaries linked with ATLAS (also Fortran): https://en.wikipedia.org/wiki/Automatically_Tuned_Linear_Algebra_Software I think at some point NumPy used to use the OSX Accelerate library but the page I linked above says that's now deprecated. I don't know anything about Accelerate but I wouldn't be surprised to hear that it was a bunch of old Fortran code! If you build NumPy from source without having any BLAS/LAPACK libraries then I think it uses its own backup version of these that is written in C but not as well optimised. This used to be the default for a pip install on Linux in pre-wheel times. Many operations in NumPy don't actually use BLAS/LAPACK and for those parts the heavy lifting is all done in NumPy's own C code. Lastly SciPy which is very often used together with NumPy does have a load of Fortran code. As I understand it at some point NumPy and SciPy were divided from the previous numerical Python libraries and there was a deliberate split so that the Fortran code all ended up in SciPy rather than NumPy. -- Oscar -- https://mail.python.org/mailman/listinfo/python-list
