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
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