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  • Book Overview & Buying Hands-On Data Structures and Algorithms with Python – Third Edition
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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)
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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
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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
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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
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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
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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

Exercises

  1. Which of the following is a true about binary trees:
    1. Every binary tree is either complete or full
    2. Every complete binary tree is also a full binary tree
    3. Every full binary tree is also a complete binary tree
    4. No binary tree is both complete and full
    5. None of the above
  2. Which of the tree traversal algorithms visit the root node last?

    Consider this binary search tree:

Figure 6.38: Sample binary search tree

  1. Suppose we remove the root node 8, and we wish to replace it with any node from the left subtree, then what will be the new root?
  2. What will be the inorder, postorder and preorder traversal of the following tree?

Figure 6.39: Example tree

  1. How do you find out if two trees are identical?
  2. How many leaves are there in the tree mentioned in question number 4?
  3. What is the relation between a perfect binary tree’s height and the...
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Tech Concepts
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Programming languages
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