Cython

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

Table of Contents

Chapter 1. Cython Essentials
Chapter 2. Compiling and Running Cython Code
Chapter 3. Cython in Depth
Chapter 4. Cython in Practice: N-Body Simulation
Chapter 5. Cython and Extension Types
Chapter 6. Organizing Cython Code
Chapter 7. Wrapping C Libraries with Cython
Chapter 8. Wrapping C++ Libraries with Cython
Chapter 9. Cython Profiling Tools
Chapter 10. Cython, NumPy, and Typed Memoryviews
Chapter 11. Cython in Practice: Spectral Norm
Chapter 12. Parallel Programming with Cython
Chapter 13. Cython in Context