Overview of this book

Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.
Preface
Free Chapter
Python Objects, Types, and Expressions
Python Data Types and Structures
Principles of Algorithm Design
Lists and Pointer Structures
Stacks and Queues
Trees
Hashing and Symbol Tables
Graphs and Other Algorithms
Searching
Sorting
Selection Algorithms
String Algorithms and Techniques
Design Techniques and Strategies
Implementations, Applications, and Tools
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Ternary search tree

A ternary tree is a data structure where each node of the tree can contain up to 3 children. It is different compared to the binary search tree in the sense that a node in a binary tree can have a maximum of 2 children, whereas a node in the ternary tree can have a maximum of 3 children. The ternary tree data structure is also considered a special case of the trie data structure. In trie data structure, each node contains 26 pointers to its children when we use trie data structure to store strings in contrast to the ternary search tree data structure, where we have 3 pointers to its children.

The ternary search tree can be represented as follows:

• Each node stores a character in it
• It has the equal pointer that points to a node that stores a value equal to the current node
• It has the left pointer that points to a node that stores a value smaller than the current...