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Hands-On Data Structures and Algorithms with Python

Hands-On Data Structures and Algorithms with Python

By : Dr. Basant Agarwal, Benjamin Baka
3 (13)
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Hands-On Data Structures and Algorithms with Python

Hands-On Data Structures and Algorithms with Python

3 (13)
By: Dr. Basant Agarwal, Benjamin Baka

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.
Table of Contents (16 chapters)
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Summary

In this chapter, we looked at tree data structures and their uses. We studied binary trees in particular, which is a subtype of tree where each node has two children at most. We also looked at how a binary tree can be used as a searchable data structure with a BST. The breadth-first and depth-first search traversal modes were also implemented in Python by using queue recursion.

We also looked at how a binary tree can be used to represent an arithmetic or a Boolean expression. We then built an expression tree to represent an arithmetic expression. Afterward, we showed you how to use a stack to parse an expression written in RPN, build up the expression tree, and finally traverse it to get the result of the arithmetic expression.

Finally, we mentioned heaps, a specialization of a tree structure. We have tried to at least lay down the theoretical foundation for the heap in...

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