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

functools


In addition to the list/dict/set comprehensions, Python also has a few (more advanced) functions that can be really convenient when coding functionally. The functools library is a collection of functions that return callable objects. Some of these functions are used as decorators (we'll cover more about that in Chapter 5, Decorators – Enabling Code Reuse by Decorating), but the ones that we are going to talk about are used as straight-up functions to make your life easier.

partial – no need to repeat all arguments every time

The partial function is really convenient for adding some default arguments to a function that you use often but can't (or don't want to) redefine. With object-oriented code, you can usually work around cases similar to these, but with procedural code, you will often have to repeat your arguments. Let's take the heapq functions from Chapter 3, Containers and Collections – Storing Data the Right Way, as an example:

>>> import heapq
>>> heap ...