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Hands-On Data Structures and Algorithms with Python

Hands-On Data Structures and Algorithms with Python - Second Edition

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 hash tables. We looked at how to write a hashing function to turn string data into integer data. Then, we looked at how we can use hashed keys to quickly and efficiently look up the value that corresponds to a key.

Further, we looked at the difficulties in the implementation of hash tables due to collisions in hash values. This led us to look at collision resolution strategies, so we discussed two important collision resolution methods, which are linear probing and chaining.

In the last section of this chapter, we studied symbol tables, which are often built using hash tables. Symbol tables allow a compiler or an interpreter to look up a symbol (such as a variable, function, or class) that has been defined and retrieve all information about it.

In the next chapter, we will talk about graphs and other algorithms.

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Hands-On Data Structures and Algorithms with Python
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