Pythran as a Numpy backend

This can lead to really interesting speedup in some cases, going from 2 up to 16, depending on the targeted CPU architecture and the original algorithm.

Please note that this feature is experimental.

Then, simply add a cython: np_pythran=True directive at the top of the Python files that needs to be compiled using Pythran numpy support.

Here is an example of a simple file using distutils:

hello_pythran.pyx will be compiled using Pythran numpy support.

Please note that Pythran can further be tweaked by adding settings in the file. For instance, this can be used to enable Boost.SIMD support. See the for more information.