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

Chapter 3. Containers and Collections – Storing Data the Right Way

Python comes bundled with several very useful collections, a few of which are basic Python collection data types. The rest are advanced combinations of these types. In this chapter, we will explain some of these collections, how to use them, and the pros and cons of each of them.

Before we can properly discuss data structures and the related performance, a basic understanding of time complexity (and specifically the big O notation) is required. No need to worry! The concept is really simple, but without it, we cannot easily explain the performance characteristics of operations.

Once the big O notation is clear, we will discuss the basic data structures:

  • list

  • dict

  • set

  • tuple

Building on the basic data structures, we will continue with more advanced collections, such as the following:

  • Dictionary-like types:

    • ChainMap

    • Counter

    • Defaultdict

    • OrderedDict

  • List types:

    • Deque

    • Heapq

  • Tuple types:

    • NamedTuple

  • Other types:

    • Enum