A typical speedup for the fast_gil directive is around 35% on this benchmark.

Add a Pythran backend for Numpy operation

This fixes #1752.

Clarify documentation regarding "cdef public"

Do not apply decorators twice

DOC: Add calls to Py_Initialize/Py_Finalize in code sample.

propagate "const char*" that Py3.7 returns from PyUnicode_AsStringAndSize() to user code and make the casts to "char*" explicit for each assignment/conversion
see https://bugs.python.org/issue28769

see https://bugs.python.org/issue28769

fused types: also ignore numpy import failures and not only failed lookups of the ndarray type (both just let ndarrays be ignored further on)

This fixes #1739.

Automatically add include_dirs for externs

This makes Pythran numpy backend only activated when such directive is
used. Update the documentation accordingly.