Build software that combines Python'??s expressivity with the performance and control of C (and C++). It'??s 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'??s performance'??up to 3000x'?? and to wrap C and C++ libraries in Python with ease. Author Kurt Smith takes you through Cython'??s 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'??s arsenal. Use Cython'??s 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'??s runtime and compile-time profiling tools Use Cython'??s prange function to parallelize loops transparently with OpenMP.