I really sick of such kind of benchmarks. I never have seen a real world python program that doesn't depend on any IO or doesn't have some C code behind wrapped calls. If your code is heavy with computations there are numpy/scipy libs that are very good at this. These optimizations bring < 10% of speed to real project/programm, but will require a lot of developers time to support it. If performance is the key feature and very critical, then likely python is not the right choice, because python is more about flexibility, ability to maintain and write solid, easy to read code.
I don't mind about knowing limitations. I'm saying that these optimizations usually are very hard tradeoffs and opposite side of it – code readability, speed of developer work, ability to maintain it working. I tried Cython and PyPy. Both are really good if your project is started with them, but if you decide to migrate to them in order to increase performance, it's like rewrite project to another language. Also both have a lot of limitations and cpython gives you still a lot more flexibility in decision making (choose frameworks, libraries and approaches how to solve certain problem)
