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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
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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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Other useful graph methods

It is very often that we need to use graphs for finding a path between two nodes. Sometimes, it is necessary to find all the paths between nodes, and in some situations, we might need to find the shortest path between nodes. For example, in routing applications, we generally use various algorithms to determine the shortest path from the source node to the destination node. For an unweighted graph, we would simply determine the path with the lowest number of edges between them. If a weighted graph is given, we have to calculate the total weight of passing through a set of edges.

Thus, in a different situation, we may have to find the longest or shortest path using different algorithms.

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