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

itertools


The itertools library contains iterable functions inspired by those available in functional languages. All of these are iterable and have been constructed in such a way that only a minimal amount of memory is required to process even the largest of datasets. While you can easily write most of these functions yourself using a simple function, I would still recommend using the ones available in the itertools library. These are all fast, memory efficient, and—perhaps more importantly—tested.

Note

Even though the titles of the paragraphs are capitalized, the functions themselves are not. Be careful not to accidently type Accumulate instead of accumulate.

accumulate – reduce with intermediate results

The accumulate function is very similar to the reduce function, which is why some languages actually have accumulate instead of reduce as the folding operator.

The major difference between the two is that the accumulate function returns the immediate results. This can be useful when summing...