Indeed. It is pretty easy to just write some Cython routine against the data pointer & range lifted out of some NumPy array and then still let Python do all th

Indeed. It is pretty easy to just write some Cython routine against the data pointer & range lifted out of some NumPy array and then still let Python do all the memory management for you. I think Cython is great for just speeding up profiling-revealed hot spots. And `cython --annotate` is even a nice helper along that path. { In fact, I think gcc should have a similar system one could integrate so that you can click-expand the Python to get the C and then click again the C to get the assembly. :-) } It really makes Python more like the gradually typed system Common Lisp always was. In fact, there was talk back in the very early noughties of bundling a precursor of Cython with the Python interpreter itself. I was always a bit disappointed that didn't go very far. Ah well.