Python Programming: An Introduction to Computer Science, 4th Ed.

This new edition has all the familiar elements that made previous editions a leading intro textbook, including:

• Extensive use of computer graphics. Coverage includes a simple-to-use graphics package (provided as a Python module) that allows students both to learn the principles of computer graphics and to practice object-oriented concepts without the complexity inherent in a full-blown graphics library and event-driven programming.
  
  
• Interesting examples. This book is packed with complete programming examples to solve real problems.
  
  
• Readable prose. Key computer science concepts are introduced in a natural way as an outgrowth of a developing discussion.
  
  
• Flexible spiral coverage. Each chapter is organized so that new ideas are introduced gradually, giving students time to assimilate an increasing level of detail. Ideas that take more time to master are introduced in early chapters and reinforced in later chapters.
  
  
• Just-in-time object coverage. This book gradually introduces object concepts after a brief initial grounding in the basics of imperative programming. Students learn multiple design techniques, including top-down (functional decomposition), spiral (prototyping), and object-oriented methods.
  
  
• Extensive end-of-chapter problems. Exercises at the end of every chapter provide ample opportunity for students to reinforce their mastery of the chapter material and to practice new programming skills.

NEW TO THE FOURTH EDITION

The focus of this edition continues to be on providing a solid foundation in computer science appropriate for a first computing course for CS majors (CS1). At the same time, many learners outside of CS are also keen to develop programming skills. All budding programmers are best served by a firm grounding in computer science and software design, so the material here has been streamlined and reorganized to make it more useful as a reference for learners in CS-adjacent fields such as the natural and social sciences, data science, and intelligent systems. Special attention is paid to essential idioms that students are likely to see in Python code that they encounter in the wild. In addition to technology updates throughout, those familiar with the previous edition will notice these changes:

• Addition of new material on operating systems and an extended discussion of persistent data including file systems, binary files, and data serialization over networks.
• Inclusion of new and additional Python features: f-strings for string formatting, context managers, list comprehensions, sequence functions, and the pathlib and pickle libraries.
• Streamlining of early chapters including covering all control structures before going into depth on sequence types such as strings and lists.
• Consolidation of objected-oriented design case studies in a dedicated chapter.
• Additional programming exercises.

TABLE OF CONTENTS

Chapter 1    Computers and Programs

    1.1     The Universal Machine
    1.2     Program Power
    1.3     What Is Computer Science?
    1.4     Hardware Basics
    1.5     Operating Systems
    1.6     Programming Languages
    1.7     The Magic of Python
    1.8     Inside a Python Program
    1.9     Chaos and Computers
    1.10     Chapter Summary
    1.11     Exercises

Chapter 2    Writing Simple Programs

    2.1     The Software Development Process
    2.2     Example Program: Temperature Converter
    2.3     Elements of Programs
              2.3.1     Names
              2.3.2     Expressions
    2.4     Output Statements
    2.5     Assignment Statements
              2.5.1     Simple Assignment
              2.5.2     Assigning Input
              2.5.3     Simultaneous Assignment
    2.6     Definite Loops
    2.7     Example Program: Future Value
    2.8    Chapter Summary
    2.9    Exercises

Chapter 3    Computing with Numbers

    3.1     Numeric Data Types
    3.2     Type Conversions and Rounding
              3.2.1     Numeric Type Conversions
              3.2.2     Converting Between Numbers and Strings
    3.3     Using the Math Library
    3.4     Accumulating Results: Factorials
    3.5     Limitations of Computer Arithmetic
    3.6     Chapter Summary
    3.7     Exercises

Chapter 4    Objects and Graphics   

    4.1     Overview
    4.2     The Object of Objects
    4.3     Simple Graphics Programming
    4.4     Using Graphical Objects
    4.5     Graphing Future Value
             4.5.1     Basic Design
             4.5.2     Choosing Coordinates
             4.5.3     Writing the Program
    4.6     Interactive Graphics
              4.6.1     Getting Mouse Clicks
              4.6.2     Handling Textual Input
    4.7     Graphics Module Reference
              4.7.1     GraphWin Objects
              4.7.2     Graphics Objects
              4.7.3     Entry Objects
              4.7.4     Displaying Images
              4.7.5     Generating Colors
              4.7.6     Controlling Display Updates (Advanced)
    4.8     Chapter Summary
    4.9     Exercises

Chapter 5     Defining Functions

    5.1     The Function of Functions
    5.2     Functions, Informally
    5.3     Future Value with a Function
    5.4     Functions and Parameters: The Exciting Details
    5.5     Functions That Return Values
    5.6     Functions That Modify Parameters
    5.7     Functions and Program Structure
    5.8     Chapter Summary
    5.9     Exercises

Chapter 6     Decision Structures

    6.1     Simple Decisions
              6.1.1     Example: Temperature Warnings
              6.1.2     Forming Simple Conditions
              6.1.3     Example: Conditional Program Execution
    6.2     Two-Way Decisions
    6.3     Multi-Way Decisions
    6.4     Exception Handling
    6.5     Study in Design: Max of Three
              6.5.1     Strategy 1: Compare Each to All
              6.5.2     Strategy 2: Decision Tree
              6.5.3     Strategy 3: Sequential Processing
              6.5.4     Strategy 4: Use Python
              6.5.5     Some Lessons
    6.6     Chapter Summary
    6.7     Exercises

Chapter 7     Loop Structures and Booleans

    7.1     For Loops: A Quick Review
    7.2     Indefinite Loops
    7.3     Common Loop Patterns
              7.3.1     Interactive Loops
              7.3.2     Sentinel Loops
    7.4     Computing with Booleans
              7.4.1     Boolean Operators
              7.4.2     Boolean Algebra
    7.5     Other Common Structures
              7.5.1     Post-Test Loop
              7.5.2     Loop and a Half
              7.5.3    Boolean Expressions as Decisions
    7.6     Example: A Simple Event Loop
    7.7     Chapter Summary
    7.8     Exercises

Chapter 8     Strings

    8.1     The String Data Type
    8.2     Simple String Processing
    8.3     String Representation and Message Encoding
              8.3.1     String Representation
              8.3.2     Programming an Encoder
    8.4     String Methods
              8.4.1     Programming a Decoder
              8.4.2     From Encoding to Encryption
    8.5     More String Methods
    8.6     String Formatting
              8.6.1     Using f-strings
              8.6.2     Better Change Counter
    8.7     Chapter Summary
    8.8     Exercises

Chapter 9    Data Collections

    9.1     Example Problem: Simple Statistics
    9.2     Python Lists
              9.2.1     Lists and Arrays as Sequences
              9.2.2     List Operations
              9.2.3     List Methods
    9.3     Statistics with Lists
    9.4     Pythonic List Manipulation
    9.5     Other Data Structures
              9.5.1     Tuples
              9.5.2     Dictionaries (Optional)
    9.6     Chapter Summary
    9.7     Exercises

Chapter 10    Persistent Data

    10.1    Text Files
               10.1.1     Multi-line Strings
               10.1.2     File-Processing Outline
               10.1.3     Reading from a File
               10.1.4     Writing to a File
               10.1.5     Batch Processing
    10.2     File Names and Paths
               10.2.1     Absolute and Relative Paths
               10.2.2     Using pathlib
               10.2.3     Iterating Over Directories
               10.2.4     File Dialogs (Optional)
    10.3     Binary Files and Pickling
               10.3.1     Strings and Bytes
               10.3.2     Binary Mode and Pickling (Optional)
    10.4     Remote Files (Optional)
    10.5     Chapter Summary
    10.6     Exercises

Chapter 11     Simulation and Design

    11.1     Simulating Racquetball
               11.1.1     A Simulation Problem
               11.1.2     Analysis and Specification
    11.2     Pseudo-Random Numbers
    11.3     Top-Down Design
               11.3.1     Top-Level Design
               11.3.2     Separation of Concerns
               11.3.3     Second-Level Design
               11.3.4     Designing simNGames
               11.3.5     Third-Level Design
               11.3.6     Finishing Up
               11.3.7     Summary of the Design Process
    11.4     Bottom-Up Implementation
               11.4.1     Unit Testing
               11.4.2     Simulation Results
    11.5     Other Design Techniques
               11.5.1     Prototyping and Spiral Development
               11.5.2     The Art of Design
    11.6     Chapter Summary
    11.7     Exercises

Chapter 12     Defining Classes

    12.1     Quick Review of Objects
    12.2     Example Program: Cannonball
               12.2.1     Program Specification
               12.2.2     Designing the Program
               12.2.3     Modularizing the Program
    12.3     Defining New Classes
               12.3.1     Example: Multi-Sided Dice
               12.3.2     Example: The Projectile Class
    12.4     Data Processing with Class
               12.4.1     Student as Object
               12.4.2     Lists of Objects
    12.5     Objects and Encapsulation
               12.5.1     Encapsulating Useful Abstractions
               12.5.2     Putting Classes in Modules
               12.5.3     Module Documentation
               12.5.4     Working with Multiple Modules
    12.6     Widgets
               12.6.1     Example Program: Dice Roller
               12.6.2     Building Buttons
               12.6.3     Building Dice
               12.6.4     The Main Program
               12.6.5     Application as a Class
    12.7     Chapter Summary
    12.8     Exercises

Chapter 13     Object-Oriented Design

    13.1     The Process of OOD
    13.2     Case Study: Racquetball Simulation
               13.2.1     Candidate Objects and Methods
               13.2.2     Implementing SimStats
               13.2.3     Implementing RBallGame
               13.2.4     Implementing Player
               13.2.5     The Complete Program
    13.3     Case Study: Cannonball Animation
               13.3.1     Creating an Animation Window
               13.3.2     Creating a ShotTracker
               13.3.3     Creating an Input Dialog
               13.3.4     The Main Event Loop
               13.3.5     Creating a Launcher
               13.3.6     Tracking Multiple Shots
               13.3.7     Final Structure
    13.4     Case Study: Dice Poker
               13.4.1     Program Specification
               13.4.2     Identifying Candidate Objects
               13.4.3     Implementing the Model
    13.4.4  A Text-Based UI
               13.4.5     Developing a GUI
    13.5    OO Concepts
              13.5.1     Encapsulation
              13.5.2     Polymorphism
              13.5.3     Inheritance
    13.6    Chapter Summary
    13.7    Exercises

Chapter 14     Algorithm Design and Recursion

    14.1    Searching
              14.1.1     A Simple Searching Problem
              14.1.2     Strategy 1: Linear Search
              14.1.3     Strategy 2: Binary Search
              14.1.4     Comparing Algorithms
    14.2    Recursive Problem Solving
              14.2.1     Recursive Definitions
              14.2.2     Recursive Functions
              14.2.3     Example: String Reversal
              14.2.4     Example: Anagrams
              14.2.5     Example: Fast Exponentiation
              14.2.6    Example: Binary Search
              14.2.7     Recursion vs. Iteration
    14.3    Sorting Algorithms
              14.3.1     Naive Sorting: Selection Sort
              14.3.2     Divide and Conquer: Merge Sort
              14.3.3     Comparing Sorts
    14.4    Hard Problems
              14.4.1     Tower of Hanoi
              14.4.2     The Halting Problem
              14.4.3     Conclusion
    14.5    Chapter Summary
    14.6    Exercises

Appendix A     Python Quick Reference
Appendix B    Glossary
Index