Build software that combines Python expressivity with the performance and control of C (and C ). It possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python performance—up to 3000x— and to wrap C and C libraries in Python with ease. Author Kurt Smith takes you through Cython capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer arsenal. Use Cython static typing to speed up Python code Gain hands-on experience using Cython features to boost your numeric-heavy Python Create new types with Cython—and see how fast object-oriented programming in Python can be Effectively organize Cython code into separate modules and packages without sacrificing performance Use Cython to give Pythonic interfaces to C and C libraries Optimize code with Cython runtime and compile-time profiling tools Use Cython prange function to parallelize loops transparently with OpenMP