Data Structures and Algorithms in Python.

Format:

Book

Author/Creator:

Lafore, Robert.

Contributor:

Broder, Alan.

Canning, John.

Series:

Developer's Library

Language:

English

Subjects (All):

Data structures (Computer science).

Python (Computer program language).

Computer algorithms.

Algorithms.

Physical Description:

1 online resource (1193 pages)

Edition:

1st ed.

Place of Publication:

[Place of publication not identified] : ADDISON-WESLEY, 2019.

Sydney : Addison Wesley, 2022.

Summary:

LEARN HOW TO USE DATA STRUCTURES IN WRITING HIGH PERFORMANCE PYTHON PROGRAMS AND ALGORITHMS This practical introduction to data structures and algorithms can help every programmer who wants to write more efficient software. Building on Robert Lafores legendary Java-based guide, this book helps you understand exactly how data structures and algorithms operate. Youll learn how to efficiently apply them with the enormously popular Python language and scale your code to handle todays big data challenges. Throughout, the authors focus on real-world examples, communicate key ideas with intuitive, interactive visualizations, and limit complexity and math to what you need to improve performance. Step-by-step, they introduce arrays, sorting, stacks, queues, linked lists, recursion, binary trees, 2-3-4 trees, hash tables, spatial data structures, graphs, and more. Their code examples and illustrations are so clear, you can understand them even if youre a near-beginner, or your experience is with other procedural or object-oriented languages. Build core computer science skills that take you beyond merely writing code Learn how data structures make programs (and programmers) more efficient See how data organization and algorithms affect how much you can do with todays, and tomorrows, computing resources Develop data structure implementation skills you can use in any language Choose the best data structure(s) and algorithms for each programming problemand recognize which ones to avoid Data Structures & Algorithms in Python is packed with examples, review questions, individual and team exercises, thought experiments, and longer programming projects. It's ideal for both self-study and classroom settings, and either as a primary text or as a complement to a more formal presentation.

Contents:

Cover Page

About This eBook

Title Page

Copyright Page

Contents at a Glance

Table of Contents

Pearson's Commitment to Diversity, Equity, and Inclusion

Dedication Page

Acknowledgments

Acknowledgments to the First Edition, Data Structures and Algorithms in Java

Acknowledgments to the Second Edition

About the Authors

Introduction

Who This Book Is For

What You Need to Know Before You Read This Book

What You Can Learn from This Book

Structure

History

Figure Credits

Chapter 1. Overview

What Are Data Structures and Algorithms?

Overview of Data Structures

Overview of Algorithms

Some Definitions

Programming in Python

Object-Oriented Programming

Summary

Questions

Experiments

Chapter 2. Arrays

The Array Visualization Tool

Using Python Lists to Implement the Array Class

The OrderedArray Visualization Tool

Binary Search

Python Code for an OrderedArray Class

Logarithms

Storing Objects

Big O Notation

Why Not Use Arrays for Everything?

Programming Projects

Chapter 3. Simple Sorting

How Would You Do It?

Bubble Sort

Selection Sort

Insertion Sort

Comparing the Simple Sorts

Chapter 4. Stacks and Queues

Different Structures for Different Use Cases

Stacks

Queues

Priority Queues

Parsing Arithmetic Expressions

Chapter 5. Linked Lists

Links

The LinkedList Visualization Tool

A Simple Linked List

Double-Ended Lists

Linked List Efficiency

Abstract Data Types and Objects

Ordered Lists

Doubly Linked Lists

Circular Lists

Iterators

Chapter 6. Recursion.

Triangular Numbers

Factorials

Anagrams

A Recursive Binary Search

The Tower of Hanoi

Sorting with mergesort

Eliminating Recursion

Some Interesting Recursive Applications

Chapter 7. Advanced Sorting

Shellsort

Partitioning

Quicksort

Radix Sort

Timsort

Chapter 8. Binary Trees

Why Use Binary Trees?

Tree Terminology

An Analogy

How Do Binary Search Trees Work?

Finding a Node

Inserting a Node

Traversing the Tree

Finding Minimum and Maximum Key Values

Deleting a Node

The Efficiency of Binary Search Trees

Trees Represented as Arrays

Printing Trees

Duplicate Keys

The BinarySearchTreeTester.py Program

The Huffman Code

Chapter 9. 2-3-4 Trees and External Storage

Introduction to 2-3-4 Trees

The Tree234 Visualization Tool

Python Code for a 2-3-4 Tree

Efficiency of 2-3-4 Trees

2-3 Trees

External Storage

Chapter 10. AVL and Red-Black Trees

Our Approach to the Discussion

Balanced and Unbalanced Trees

AVL Trees

The Efficiency of AVL Trees

Red-Black Trees

Using the Red-Black Tree Visualization Tool

Experimenting with the Visualization Tool

Rotations in Red-Black Trees

Inserting a New Node

Deletion

The Efficiency of Red-Black Trees

2-3-4 Trees and Red-Black Trees

Red-Black Tree Implementation

Chapter 11. Hash Tables

Introduction to Hashing

Open Addressing

Separate Chaining

Hash Functions

Hashing Efficiency

Hashing and External Storage

Experiments.

Programming Projects

Chapter 12. Spatial Data Structures

Spatial Data

Computing Distances Between Points

Circles and Bounding Boxes

Searching Spatial Data

Lists of Points

Grids

Quadtrees

Theoretical Performance and Optimizations

Practical Considerations

Further Extensions

Chapter 13. Heaps

Introduction to Heaps

The Heap Visualization Tool

Python Code for Heaps

A Tree-Based Heap

Heapsort

Order Statistics

Chapter 14. Graphs

Introduction to Graphs

Traversal and Search

Minimum Spanning Trees

Topological Sorting

Connectivity in Directed Graphs

Chapter 15. Weighted Graphs

Minimum Spanning Tree with Weighted Graphs

The Shortest-Path Problem

The All-Pairs Shortest-Path Problem

Efficiency

Intractable Problems

Chapter 16. What to Use and Why

Analyzing the Problem

Foundational Data Structures

Special-Ordering Data Structures

Sorting

Specialty Data Structures

Onward

Appendixes

Appendix A. Running the Visualizations

For Developers: Running and Changing the Visualizations

For Managers: Downloading and Running the Visualizations

For Others: Viewing the Visualizations on the Internet

Using the Visualizations

Appendix B. Further Reading

Data Structures and Algorithms

Object-Oriented Programming Languages

Object-Oriented Design (OOD) and Software Engineering

Appendix C. Answers to Questions

Chapter 1, "Overview"

Chapter 2, "Arrays"

Chapter 3, "Simple Sorting"

Chapter 4, "Stacks and Queues"

Chapter 5, "Linked Lists"

Chapter 6, "Recursion".

Chapter 7, "Advanced Sorting"

Chapter 8, "Binary Trees"

Chapter 9, "2-3-4 Trees and External Storage"

Chapter 10, "AVL and Red-Black Trees"

Chapter 11, "Hash Tables"

Chapter 12, "Spatial Data Structures"

Chapter 13, "Heaps"

Chapter 14, "Graphs"

Chapter 15, "Weighted Graphs"

Index

Code Snippets.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9780134855912

0134855914

9780134855882

0134855884

9780134855899

0134855892

OCLC:

1343718541