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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