Em quinta-feira, 4 de dezembro de 2014 07h51min14s UTC-2, Sturla Molden escreveu: > Dan Stromberg <drsali...@gmail.com> wrote: > > > 1) writing in Cython+CPython (as opposed to wrapping C++ with Cython) > > That is an option, but it locks the code to Cython and CPython forever. C > and C++ are at least semi-portable. > > > 2) using numba+CPython (It's a pretty fast decorator - I've heard it's > > faster than Cython) > > Numba is usually not "faster than Cython" (Cython can be as fast as C), but > it can be pretty fast. Sometimes it is comparable to -O2 in C for the > subset of Python it supports, but usually a bit slower. But if you can use > it, it is easier to use than Cython. There are no extra compilation steps, > etc. Just add a couple of decorators to the Python code and it takes off > like a rocket. For anyone who are familiar with PyPy and Psyco, Numba is > far better than those. It is a Python JIT compiler that often can perform > better than the Java VM. Numba will also JIT-compile Python code that uses > ctypes or cffi to call external libraries down to almost zero overhead. > > You forgot to mention using Fortran and f2py. Many scientists and engineers > prefer Fortran to C and C++ because it is easier to use. And Fortran 90 and > later standards are not anything like the loathed Fortran 66 and 77 > languages. Fortran is a high-level language particularly suited for > numerical computing, C is a semi-portable high-level assembler. > > Sturla
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