Build software that combines Pythonâ??s expressivity with the performance and control of C (and C++). Itâ??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, youâ??ll learn how to use Cython to improve Pythonâ??s performanceâ??up to 3000xâ?? and to wrap C and C++ libraries in Python with ease.

Author Kurt Smith takes you through Cythonâ??s capabilities, with sample code and in-depth practice exercises. If youâ??re just starting with Cython, or want to go deeper, youâ??ll learn how this language is an essential part of any performance-oriented Python programmerâ??s arsenal.

Use Cythonâ??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 Cythonâ??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 Cythonâ??s runtime and compile-time profiling tools

Use Cythonâ??s prange function to parallelize loops transparently with OpenMP

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