> could you tell us the shortcomings of Cython

In order to achieve top performance, in the context of numerical simulations, you generally end up explicity writing the loops are implicit in high-level numpy (less abstraction).

Cython does not perform any high-level optimisation on the code, while Pythran does. For instance Pytrhan computes whether an array index may be negative or not, and generates wraparound only when needed. On the otherhand Cython requires a compiler directive to do so.

That being said, Cython can do plenty of stuff Pythran cannot: import native libraries, wrap classes, mixed Python/native mode etc. It has a much stronger codebase (more tested/validated) and a larger community.

For me, the biggest shortcoming: Cython does not create independent C++ code (independent of the python interpreter that is) that can be used in a separate C++ code base. My main point is that pythran makes it possible to deploy python/numpy code as C++ code.

I didn't realize you're the author of the blog post!

Thanks to both of you for the reply