On Sun, 03 Nov 2013 01:02:24 -0500, E.D.G. wrote: [...] > Since Perl has a calculation speed > limit that is probably not easy to get around, before too long another > language will be selected for initially doing certain things such as > performing calculations and plotting charts. And the existing Perl code > might then be gradually translated into that new language.
The nice things about Python are that it makes a great glue language for putting together components written in low-level languages like C and Fortran, and that there is a rich ecosystem of products for speeding it up in various ways. So when you hit the speed limits of pure Python, you have lots of options. In no particular order: * try using another Python compiler: PyPy is probably the most mature of the stand-alone optimizing compilers, and you can expect to double the speed of "typical" Python code, but there are others; * use numpy and scipy for vectorized mathematical routines; * re-write critical code as C or Fortran libraries; * use Pyrex (possibly unmaintained now) or Cython to write C extensions in a Python-like language; * use Psyco or Numba (JIT specialising compilers for Python); * use Theano (optimizing computer algebra system compiler); * use ctypes to call C functions directly; * use other products like Boost, Weave, and more. See, for example: http://jakevdp.github.io/blog/2013/06/15/numba-vs-cython-take-2/ http://technicaldiscovery.blogspot.com.au/2011/06/speeding-up-python-numpy-cython-and.html -- Steven -- https://mail.python.org/mailman/listinfo/python-list
