Problem Solving with Algorithms and Data Structures Using Python SECOND EDITION

"This textbook is about computer science. It is also about Python. However, there is much more. The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms, typically taught as the second course in the computer science curriculum. Even though the second course is considered more advanced than the first course, this book assumes you are beginners at this level. You may still be struggling with some of the basic ideas and skills from a first computer science course and yet be ready to further explore the discipline and continue to practice problem solving. We cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science."--Page 4 de la couverture Introduction 7 Objectives 7 Getting Started 7 What Is Computer Science? 8 Review of Basic Python 12 Summary 42 Key Terms 42 Programming Exercises 42 Algorithm Analysis 45 Objectives 45 What Is Algorithm Analysis? 45 Performance of Python Data Structures 56 Summary 63 Key Terms 63 Discussion Questions 63 Programming Exercises 64 Basic Data Structures 65 Objectives 65 What Are Linear Structures? 65 Stacks 66 The Stack Abstract Data Type 68 Queues 86 Deques 98 Lists 101 The Unordered List Abstract Data Type 102 Implementing an Unordered List: Linked Lists 102 The Ordered List Abstract Data Type 112 Summary 115 Key Terms 116 Discussion Questions 116 Programming Exercises 117 Recursion 121 Objectives 121 What is Recursion? 121 Stack Frames: Implementing Recursion 127 Visualising Recursion 129 Complex Recursive Problems 137 Exploring a Maze 139 Summary 148 Key Terms 149 Discussion Questions 149 Programming Exercises 149 Sorting and Searching 151 Objectives 151 Searching 151 Sorting 167 Summary 185 Key Terms 186 Discussion Questions 186 Programming Exercises 187 Trees and Tree Algorithms 189 Objectives 189 Examples Of Trees 189 Vocabulary and Definitions 192 Implementation 194 Priority Queues with Binary Heaps 202 Binary Tree Applications 210 Tree Traversals 216 Binary Search Trees 219 Summary 235 Key Terms 236 Discussion Questions 236 Programming Exercises 237 JSON 239 Objectives 239 What is JSON? 239 The JSON Syntax 239 Thes book has three key features : fundamental data structures and algorithms; algorithm analysis in terms of Big-O running time in introducied early and applied throught; pytohn is used to facilitates the success in using and mastering data strucutes and algorithms