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

Introduction


Python has a rich collection of built-in data structures. A great deal of useful programming is commonly done with these built-in structures. These collections cover a variety of common situations.

We'll look at an overview of the various structures that are available and what problems they solve. From there, we can look at lists, dictionaries, and sets in detail.

Note that we've set the built-in tuple and string aside as being different from the list structure. There are some important similarities as well as some differences. In Chapter 1, Numbers, Strings, and Tuples, we emphasized the way strings and tuples behave more like immutable numbers than mutable collections.

We'll also look at some more advanced topics related to how python handles references to objects. We'll look at some issues related to the mutability of these data structures, as well.