Cython is a tool that makes writing native extensions to Python as easy as writing them in Python. For those who are unaware, you can implement Python modules as pure the C code, which will, for all intents and purposes, look and act like any Python code. This is required when implementing modules in Python, such as the built-in zip module which use native zlib under the hood. Doing this makes sense for the standard library modules part of Python, though for most users of Python, writing native modules should be the last course of action if possible.
Writing native modules is hard and requires prerequisite knowledge of how to use the garbage collector calls correctly in order to avoid memory leaks. It also requires an understanding of how the GIL is used, which changes if you are using CPython or PyPy. It also requires knowledge of the module structures and argument passing internally to the Python runtime. Therefore, it isn't a trivial process when the need arises. Cython lets us write and work with the native code without having to know anything about the Python runtime. We can write almost pure Python code that just so happens to let us manipulate C/C++ types and classes. We can call back and forth from the native code and into the Python code.
More importantly, Cython removes the complexity and intrinsicity and lets the programmer focus on solving problems.
Chapter 1, Cython Won't Bite, introduces core concepts and demonstrates Cython "Hello World". It discusses the typing and type conversion.
Chapter 2, Understanding Cython, acts as a reference throughout the book. We look at custom C types and function pointers. Using this, we will successfully use Python modules directly from C code.
Chapter 3, Extending Applications, uses everything from the previous chapters to write native Tmux commands using Python instead of C/C++.
Chapter 4, Debugging Cython, uses the cygdb wrapper over gdb to debug Cython code.
Chapter 5, Advanced Cython, introduces how well Cython can work with C++ classes and templates. In general, it also covers caveats in Cython.
Chapter 6, Further Reading, briefly looks at the related projects and interesting sources of new learning.
For this book, I used my MacBook and an Ubuntu virtual machine (GDB is too old on Mac OS X for debugging). You will require the following on Mac OS X:
Xcode
Cython
GCC/Clang
Make
Python
Python con g
Python distutils
On Ubuntu/Debian you can install everything via the following command:
$ sudo apt-get install build-essential gdb cython
I will go over this in the introduction, but as long as you have a working C compiler and Python along with Python libraries and headers installed, you will have everything you need for Cython.
This book is intended for C/C++ developers who like using Python and Python users wanting to implement native C/C++ extensions to Python. As a reader, you can expect to be shown how you can develop applications with Cython with an emphasis on extending existing systems and with help on how you can approach it.
Extending legacy systems can be difficult, but the rewards can be great. Consider low-level thread-aware or I/O-sensitive operations in C and maintain the logic handled and provided by Python. This model of development can prove to be efficient and of great return to the development time, which can be particularly expensive when it comes to C applications.
It also allows for much more rapid development of the state or logic in a system. There is no need to worry about long data conversion algorithms in C to do small things and then needing to change them all again.
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "The preferred one would be to use pip."
A block of code is set as follows:
#include <stdio.h>
int AddFunction(int a, int b) {
printf("look we are within your c code!\n");
return a + b;
}When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
>>> pyximport.install()
(None, <pyximport.pyximport.PyxImporter object at 0x102fba4d0>)
>>> import helloworld
Hello World from cython!New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Clicking the Next button moves you to the next screen."
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