Personally I think numerical code should still mostly be written in C++, right now it still has by far the widest choice of options for doing so. It is also relatively easy to interface with python. For example both xtensor, libtorch/ATen, arrayfire have straightforward python interoperability via pybind11.
Finally no other language except for maybe FORTRAN has seamless parallelisation support and first class low level numerical primitives developed by vendors. Sometimes you will get a massive performance increase by #pragma omp parallel for.
Even for visualization some python libraries will suddenly fall off a cliff (Altair) once you reach a moderately large number of datapoints.
Finally no other language except for maybe FORTRAN has seamless parallelisation support and first class low level numerical primitives developed by vendors. Sometimes you will get a massive performance increase by #pragma omp parallel for.
Even for visualization some python libraries will suddenly fall off a cliff (Altair) once you reach a moderately large number of datapoints.