spaCy might be a good example. It's a natural language processing library that's written in Cython, so yeah, a lot of the hard computation work is essentially j

spaCy might be a good example. It's a natural language processing library that's written in Cython, so yeah, a lot of the hard computation work is essentially just calling into C code. But it's usually being driven from a Python script that's in charge of loading the data and feeding it into spaCy's processing pipeline. That code is subject to the GIL, and, since it cannot be effectively multithreaded, it tends to become the program's bottleneck. So what you typically end up doing instead is using multiprocessing to parallelize. But that comes with its own costs. You end up wasting a lot of computrons on inter-process communication.