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

By : Dr. Basant Agarwal

4.8 (26)

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

4.8 (26)

By: Dr. Basant Agarwal

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.

Preface

Preface

Who this book is for

What this book covers

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Python Data Types and Structures

Python Data Types and Structures

Introducing Python 3.10

Installing Python

Setting up a Python development environment

Overview of data types and objects

Basic data types

Complex data types

Python’s collections module

Summary

Introduction to Algorithm Design

Introduction to Algorithm Design

Introducing algorithms

Performance analysis of an algorithm

Asymptotic notation

Amortized analysis

Composing complexity classes

Computing the running time complexity of an algorithm

Summary

Exercises

Algorithm Design Techniques and Strategies

Algorithm Design Techniques and Strategies

Algorithm design techniques

Recursion

Divide and conquer

Dynamic programming

Greedy algorithms

Summary

Exercises

Linked Lists

Linked Lists

Arrays

Introducing linked lists

Singly linked lists

Doubly linked lists

Circular lists

Practical applications of linked lists

Summary

Exercise

Stacks and Queues

Stacks and Queues

Stacks

Queues

Summary

Exercises

Trees

Trees

Terminology

Binary trees

Binary search trees

Summary

Exercises

Heaps and Priority Queues

Heaps and Priority Queues

Heaps

Priority queues

Summary

Exercises

Hash Tables

Hash Tables

Introducing hash tables

Resolving collisions

Implementing hash tables

Symbol tables

Summary

Exercise

Graphs and Algorithms

Graphs and Algorithms

Graphs

Graph representations

Graph traversals

Other useful graph methods

Summary

Exercises

Searching

Searching

Introduction to searching

Linear search

Jump search

Binary search

Interpolation search

Exponential search

Choosing a search algorithm

Summary

Exercise

Sorting

Sorting

Technical requirements

Sorting algorithms

Bubble sort algorithms

Insertion sort algorithm

Selection sort algorithm

Quicksort algorithm

Implementation of quicksort

Timsort algorithm

Summary

Exercise

Selection Algorithms

Selection Algorithms

Technical requirements

Selection by sorting

Randomized selection

Deterministic selection

Summary

Exercise

String Matching Algorithms

String Matching Algorithms

Technical requirements

String notations and concepts

Pattern matching algorithms

The brute force algorithm

The Rabin-Karp algorithm

The Knuth-Morris-Pratt algorithm

The Boyer-Moore algorithm

Summary

Exercise

Other Books You May Enjoy

Other Books You May Enjoy

Index

Index

Appendix: Answers to the Questions

Chapter 2: Introduction to Algorithm Design

Chapter 3: Algorithm Design Techniques and Strategies

Chapter 4: Linked Lists

Chapter 5: Stacks and Queues

Chapter 6: Trees

Chapter 7: Heaps and Priority Queues

Chapter 8: Hash Tables

Chapter 9: Graphs and Algorithms

Chapter 10: Searching

Chapter 11: Sorting

Chapter 12: Selection Algorithm

Chapter 13: String Matching Algorithms

String notations and concepts

Strings are sequences of characters. Python provides a rich set of operations and functions that can be applied to the string data type. Strings are textual data and are handled very efficiently in Python. The following is an example of a string (s)—"packt publishing".

A substring is a sequence of characters that’s part of the given string, i.e., specified indices in the string in a continuous order. For example, “packt" is a substring of the string “packt publishing". On the other hand, a subsequence is also a sequence of characters that can be obtained from the given string by removing some of the characters from the string by keeping the order of occurrence of the characters. For example, “pct pblishing" is a valid subsequence for the string “packt publishing" that is obtained by removing the characters a, k, and u. However, this is not a substring since “pct pblishing...

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Tech Concepts

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Programming languages

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