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

Summary


This chapter showed us some of the places where decorators can be used to make our code simpler and add some fairly complex behavior to very simple functions. Truthfully, most decorators are more complex than the regular function would have been by simply adding the functionality directly, but the added advantage of applying the same pattern to many functions and classes is generally well worth it.

Decorators have so many uses to make your functions and classes smarter and more convenient to use:

  • Debugging

  • Validation

  • Argument convenience (pre-filling or converting arguments)

  • Output convenience (converting the output to a specific type)

The most important takeaway of this chapter should be to never forget functools.wraps when wrapping a function. Debugging decorated functions can be rather difficult because of (unexpected) behavior modification, but losing attributes as well can make that problem much worse.

The next chapter will show us how and when to use generators and coroutines. This...