Cython - A guide for Python programmers by Kurt W. Smith PDF

By Kurt W. Smith

ISBN-10: 1491901551

ISBN-13: 9781491901557

Build software program that mixes Python’s expressivity with the functionality and regulate of C (and C++). It’s attainable with Cython, the compiler and hybrid programming language utilized by foundational programs equivalent to NumPy, and well-known in initiatives together with Pandas, h5py, and scikits-learn. during this useful advisor, you’ll easy methods 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 features, with pattern code and in-depth perform workouts. If you’re simply beginning with Cython, or are looking to pass 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
  • Gain hands-on event utilizing Cython gains to spice up your numeric-heavy Python
  • Create new varieties with Cython—and see how briskly object-oriented programming in Python can be
  • Effectively arrange Cython code into separate modules and programs with no 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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Construct software program that mixes Python's expressivity with the functionality and regulate of C (and C++). It's attainable with Cython, the compiler and hybrid programming language utilized by foundational applications corresponding to NumPy, and well known in initiatives together with Pandas, h5py, and scikits-learn. during this functional consultant, you'll how to use Cython to enhance Python's performance—up to 3000x— and to wrap C and C++ libraries in Python very easily.

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For those interested in why Cython works, it can be attributed to two differences: run‐ time interpretation versus ahead-of-time compilation, and dynamic versus static typing. Interpreted Versus Compiled Execution To better understand how and why Cython improves the performance of Python code, it is useful to compare how the Python runtime runs Python code with how an operating system runs compiled C code. Before being run, Python code is automatically compiled to Python bytecode. Byteco‐ des are fundamental instructions to be executed, or interpreted, by the Python virtual machine (VM).

The entries can also be glob patterns that match multiple files at once. pyx file being imported. pyx file, then pyximport will recompile on import. pyxdeps file is nice to communicate file dependencies to pyximport, but how do we tell pyximport to compile and link several source files into one extension module? pyxbld file: its purpose is to customize pyximport for this and other use cases. pyxbld. pyx file being imported. pyxbld file? One or two Python functions, each optional: make_ext(modname, pyxfilename) If defined, the make_ext function is called with two string arguments before compilation.

The interpreter asks the type for an implementation of the addition method, which may require one or more additional pointer lookups and internal function calls. 3. If the method in question is found, the interpreter then has an actual function it can call, implemented either in Python or in C. 4. The interpreter calls the addition function and passes in a and b as arguments. 5. The addition function extracts the necessary internal data from a and b, which may require several more pointer lookups and conversions from Python types to C types.

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Cython - A guide for Python programmers by Kurt W. Smith


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