By Kurt W. Smith
Build software program that mixes Python's expressivity with the functionality and keep an eye on of C (and C++). It's attainable with Cython, the compiler and hybrid programming language utilized by foundational programs comparable to NumPy, and renowned in tasks together with Pandas, h5py, and scikits-learn. during this functional advisor, you'll how to use Cython to enhance Python's performance—up to 3000x— and to wrap C and C++ libraries in Python with ease.
Author Kurt Smith takes you thru Cython's functions, with pattern code and in-depth perform workouts. If you're simply beginning with Cython, or are looking to cross deeper, you'll find out how this language is an important a part of any performance-oriented Python programmer's arsenal.
• Use Cython's static typing to hurry up Python code
• achieve hands-on adventure utilizing Cython good points to spice up your numeric-heavy Python
• Create new varieties with Cython—and see how briskly object-oriented programming in Python can be
• successfully arrange Cython code into separate modules and applications with out sacrificing performance
• Use Cython to provide Pythonic interfaces to C and C++ libraries
• Optimize code with Cython's runtime and compile-time profiling tools
• Use Cython's prange functionality to parallelize loops transparently with OpenMP
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Additional info for Cython: A Guide of Python Programmers
Pyx, we can say: # cython: nonecheck=True We can have more than one directive specified on one line. To turn off bounds checking for indexing globally (covered in Chapter 10), we can add a boundscheck=False directive: # cython: nonecheck=True, boundscheck=False or we can specify them on separate lines: # cython: nonecheck=True # cython: boundscheck=False Alternatively, we can set directives from the command line using the -X or -—directive option. Doing so overrides the value for the directive set in a directive comment.
These tools often provide simple commands that handle the details for us, much like Python’s own distutils package does. The benefit of these build tools is that they have improved dependency management and other advanced features that distutils lacks, which can be a tremendous productivity enhancement for large projects. Cython can be integrated into these build tools if it is not already, and we will cover a few of them here. CMake and Cython CMake is a powerful open source build system created by Kitware, Inc.
Tuple_of_ints = (a, b, c) This code is trivial, boring even. The point to emphasize here is that a, b, and c are statically typed integers, and Cython allows the creation of a dynamically typed Python tuple literal with them. We can then assign that tuple to the dynamically typed tuple_of_ints variable. The simplicity of this example is part of Cython’s power and beauty: we can just create a tuple of C ints in the obvious way without further thought. We want conceptually simple things like this to be simple, and that is what Cython provides.