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Hands-On Data Structures and Algorithms with Python – Third Edition

Hands-On Data Structures and Algorithms with Python – Third Edition - Third Edition

By : Dr. Basant Agarwal
4.8 (26)
Buy this Book
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Hands-On Data Structures and Algorithms with Python – Third Edition

Hands-On Data Structures and Algorithms with Python – Third Edition

4.8 (26)
By: Dr. Basant Agarwal
Buy this Book

Overview of this book

Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You’ll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer. By the end of this Python book, you’ll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.
Table of Contents (17 chapters)
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Preface
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Preface
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Who this book is for
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What this book covers
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To get the most out of this book
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Get in touch
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1
Python Data Types and Structures
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Python Data Types and Structures
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Introducing Python 3.10
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Installing Python
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Setting up a Python development environment
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Overview of data types and objects
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Basic data types
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Complex data types
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Python’s collections module
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Summary
2
Introduction to Algorithm Design
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Introduction to Algorithm Design
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Introducing algorithms
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Performance analysis of an algorithm
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Asymptotic notation
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Amortized analysis
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Composing complexity classes
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Computing the running time complexity of an algorithm
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Summary
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Exercises
3
Algorithm Design Techniques and Strategies
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Algorithm Design Techniques and Strategies
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Algorithm design techniques
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Recursion
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Divide and conquer
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Dynamic programming
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Greedy algorithms
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Summary
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Exercises
4
Linked Lists
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Linked Lists
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Arrays
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Introducing linked lists
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Singly linked lists
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Doubly linked lists
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Circular lists
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Practical applications of linked lists
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Summary
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Exercise
5
Stacks and Queues
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Stacks and Queues
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Stacks
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Queues
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Summary
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Exercises
6
Trees
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Trees
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Terminology
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Binary trees
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Binary search trees
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Summary
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Exercises
7
Heaps and Priority Queues
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Heaps and Priority Queues
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Heaps
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Priority queues
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Summary
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Exercises
8
Hash Tables
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Hash Tables
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Introducing hash tables
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Resolving collisions
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Implementing hash tables
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Symbol tables
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Summary
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Exercise
9
Graphs and Algorithms
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Graphs and Algorithms
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Graphs
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Graph representations
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Graph traversals
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Other useful graph methods
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Summary
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Exercises
10
Searching
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Searching
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Introduction to searching
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Linear search
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Jump search
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Binary search
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Interpolation search
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Exponential search
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Choosing a search algorithm
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Summary
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Exercise
11
Sorting
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Sorting
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Technical requirements
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Sorting algorithms
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Bubble sort algorithms
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Insertion sort algorithm
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Selection sort algorithm
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Quicksort algorithm
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Implementation of quicksort
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Timsort algorithm
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Summary
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Exercise
12
Selection Algorithms
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Selection Algorithms
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Technical requirements
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Selection by sorting
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Randomized selection
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Deterministic selection
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Summary
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Exercise
13
String Matching Algorithms
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String Matching Algorithms
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Technical requirements
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String notations and concepts
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Pattern matching algorithms
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The brute force algorithm
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The Rabin-Karp algorithm
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The Knuth-Morris-Pratt algorithm
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The Boyer-Moore algorithm
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Summary
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Exercise
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Other Books You May Enjoy
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Other Books You May Enjoy
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Index
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Index
1
Appendix: Answers to the Questions
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Chapter 2: Introduction to Algorithm Design
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Chapter 3: Algorithm Design Techniques and Strategies
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Chapter 4: Linked Lists
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Chapter 5: Stacks and Queues
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Chapter 6: Trees
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Chapter 7: Heaps and Priority Queues
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Chapter 8: Hash Tables
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Chapter 9: Graphs and Algorithms
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Chapter 10: Searching
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Chapter 11: Sorting
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Chapter 12: Selection Algorithm
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Chapter 13: String Matching Algorithms

Practical applications of linked lists

As of now, we have discussed singly linked lists, circular linked lists, and doubly linked lists. Depending upon what kind of operations (insertion, deletion, updating, and so on) will be required in different applications, these data structures are used accordingly. Let’s see a few real-time applications where these data structures are being used.

Singly linked lists can be used to represent any sparse matrix. Another important application is to represent and manipulate polynomials by accumulating constants in the node of linked lists.

It can also be used in implementing a dynamic memory management scheme that allows the user to allocate and deallocate the memory as per requirements during the execution of programs.

On the other hand, doubly linked lists are used by the thread schedular in the operating system to maintain the list of processes running at that time. These lists are also used in the implementation of MRU (most...

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