Book Image

Modern Python Cookbook

Book Image

Modern Python Cookbook

Overview of this book

Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide great speed, safety, and scalability. By exposing Python as a series of simple recipes, you can gain insight into specific language features in a particular context. Having a tangible context helps make the language or standard library feature easier to understand. This book comes with over 100 recipes on the latest version of Python. The recipes will benefit everyone ranging from beginner to an expert. The book is broken down into 13 chapters that build from simple language concepts to more complex applications of the language. The recipes will touch upon all the necessary Python concepts related to data structures, OOP, functional programming, as well as statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively use the advantages that it offers. You will end the book equipped with the knowledge of testing, web services, and configuration and application integration tips and tricks. The recipes take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe. You will be armed with the knowledge of creating applications with flexible logging, powerful configuration, and command-line options, automated unit tests, and good documentation.
Table of Contents (18 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Using more sophisticated collections


Python has a wide variety of built-in collections. In Chapter 4, Built-in Data Structures – list, set, dict, we looked at them closely. In the Choosing a data structure recipe we provided a kind of decision tree to help locate the appropriate data structure from the available choices.

When we fold in the standard library, we have more choices, and more decisions to make. How can we choose the right data structure for our problem?

Getting ready

Before we put data into a collection, we'll need to consider how we'll gather the data, and what we'll do with the collection once we have it. The big question is always how we'll identify a particular item within the collection. We'll look at a few key questions that we need to answer to help select a proper collection for our needs.

Here's the overview of the alternative collections. They're in three modules.

The collections module contains a number of variations on the built-in collections. These include the following...