Cython. A Guide for Python Programmers
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Cython. A Guide for Python Programmers
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- Nombre de pages254
- FormatMulti-format
- ISBN978-1-4919-0154-0
- EAN9781491901540
- Date de parution21/01/2015
- Protection num.NC
- Infos supplémentairesMulti-format incluant PDF sans p...
- ÉditeurO'Reilly Media
Résumé
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
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
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
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
A propos de Kurt W. Smith