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

Interactive debugging


Now that we have discussed basic debugging methods that will always work, we will look at interactive debugging for some more advanced debugging techniques. The previous debugging methods made variables and stacks visible through modifying the code and/or foresight. This time around, we will look at a slightly smarter method, which constitutes doing the same thing interactively, but once the need arises.

Console on demand

When testing some Python code, you may have used the interactive console a couple of times, since it's a simple yet effective tool for testing your Python code. What you might not have known is that it is actually simple to start your own shell from within your code. So, whenever you want to drop into a regular shell from a specific point in your code, that's easily possible:

import code


def spam():
    eggs = 123
    print('The begin of spam')
    code.interact(banner='', local=locals())
    print('The end of spam')
    print('The value of eggs: %s...