Book Image

Mastering Python

By : Rick van Hattem
Book Image

Mastering Python

By: Rick van Hattem

Overview of this book

Python is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward. This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also get familiar with different testing systems such as py.test, doctest, and unittest, and debugging tools such as Python debugger and faulthandler. You will learn to optimize application performance so that it works efficiently across multiple machines and Python versions. Finally, it will teach you how to access C functions with a simple Python call. By the end of the book, you will be able to write more advanced scripts and take on bigger challenges.
Table of Contents (22 chapters)
Mastering Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
6
Generators and Coroutines – Infinity, One Step at a Time
Index

Native C/C++ extensions


The libraries that we have used so far only showed us how to access a C/C++ library within our Python code. Now we are going to look at the other side of the story—how C/C++ functions/modules within Python are actually written and how modules such as cPickle and cProfile are created.

A basic example

Before we can actually start with writing and using native C/C++ extensions, we have a few prerequisites. First of all, we need the compiler and Python headers; the instructions in the beginning of this chapter should have taken care of this for us. After that, we need to tell Python what to compile. The setuptools package mostly takes care of this, but we do need to create a setup.py file:

import setuptools

spam = setuptools.Extension('spam', sources=['spam.c'])

setuptools.setup(
    name='Spam',
    version='1.0',
    ext_modules=[spam],
)

This tells Python that we have an Extension object named Spam that will be based on spam.c.

Now, let's write a function in C that sums...