One of the main issues is that, because you compile things separately with a context-switch managed by python in the middle, if you pass a Cython compiled function to code that is calling compiled code (C/Fortran/etc.), then you still get a huge overhead. We tested this with ODE solvers, and things like Numba+SciPy odeint were still about 10x slower than they should be because of this phenomena ([1] mentions some of our tests). In the end, we found a very good reason to make sure the whole stack can compile together!

[1]: http://juliadiffeq.org/2018/04/30/Jupyter.html