Cython is a tool that bridges the convenience of Python with the speed of C. Compared to C bindings, Cython programs are much easier to maintain and debug, thanks to the tight integration and compatibility with Python and the availability of excellent tools.

In this chapter, we introduced the basics of the Cython language and how to make our programs faster by adding static types to our variables and functions. We also learned how to work with C arrays, NumPy arrays, and memoryviews.

We optimized our particle simulator by rewriting the critical evolve function, obtaining a tremendous speed gain. Finally, we learned how to use the annotated view to spot hard-to-find interpreter related calls and how to enable cProfile support in Cython. Also, we learned how to take advantage of the Jupyter notebook for integrated profiling and analysis of Cython codes.

In the next chapter, we will explore other tools that can generate fast machine code on the fly, without requiring compilation of our code to C ahead of time.