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Cython can yield massive performance improvements over pure Python speedups of 3000X are easily attainable for certain patterns. With this book, Kurt Smith shows you how to use Cython to easily wrap C and C++ libraries in Python, handling all the details of memory management for you. By removing the barrier between Python and C, Cython harnesses the best of both languages while remaining familiar and comfortable to Python users.
Cython has proven its usefulness in many foundational projects: Pandas, SymPy, Sage, and dozens of others, both open and closed source. You'll learn how Cython is an essential part of any performance-oriented Python programmer's arsenal.
About the author
Kurt Smith has been using Python in scientific computing ever since his college days, looking for any opportunity to incorporate it into his computational physics classes. He has contributed to the Cython project as part of the 2009 Google Summer of Code, implementing the initial version of typed memoryviews and native cython arrays. He uses Cython extensively in his consulting work at Enthought, training hundreds of scientists, engineers, and researchers in Python, NumPy, Cython, and parallel and high-performance computing.
Summary
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.
