There is not effort to "get numpy working on cython" (I am not sure what it would really mean). There is an effort to refactor numpy code between the python-dependent part and the more core, "pure C" part, which would help.

Adding pypy as a target to cython is news to me, but that also seems like a significant work given the nature of both projects.

What fundamentally bothers me with those approaches is that they rely on a lot of work before even proving they can work at all. Whereas a more complete C API emulation layer would help many more projects, and give a more iterative process. The latter almost always works better in my experience.

Enough with the Cython nonsense! Cython has excellent marketing but it is a really naive compiler. Just figure out how to translate Cython to ctypes+Python for backwards compatibility and use pypy.

Cython is supposed to be a naive compiler, it's primary use-case is for speeding up specific functions by having them compiled. That it uses a python-like language to do this is great.

I'm reasonably certain the C parts of numpy rely more on implementation optimisations than compiler optimisations for their increased efficiency.

You don't know what you're talking about. Using something like Cython (I'm still using Pyrex) to make C extensions dramatically speeds development, if only because it largely solves the reference count problem.