Why are you trying to push this point, when you plainly admit you don't know much about this? And so strongly, too! "Anything else is misinformation." I've seldom seen someone so confidently wrong.

PyPy can address Python's slow loop performance and slow numeric calculations, in particular examples. This can help a lot. But if the problem requires you to carefully manage your data structures so that you get good cache performance, PyPy cannot help much at all.

Consider this: there are very few non-toy examples of PyPy giving order of magnitude efficiency improvements over CPython, while other languages do typically run that much faster than Python implementations.

Finally, if you don't want to talk about generalities...Consider my NLP library, spaCy: http://honnibal.github.io/spaCy/#speed-comparison . It's the fastest library with this functionality in the world, among any language.

This library is an example where you need C data structures just to make the working set manageable. You would need an enormous amount of memory just to load the models. In pure Python, the library would not be of much use to anyone --- so I would have written it in Java or C++.