Python Programming in Context 3rd edition by Bradley Miller, David Ranum, Julie Anderson ISBN 1284175554 9781284175554

1 Introduction to Pythona

1.1 Objectives

1.2 What Is Computer Science?

1.3 Why Study Computer Science?

1.3.1 Everyday Applications of Computer Science

1.3.2 Why Computer Science Is Important

1.4 Problem-Solving Strategies

1.5 Python Overview

1.5.1 Primitive Elements

1.5.2 Naming Objects

1.5.3 Abstraction

1.5.4 Repetition

1.6 Summary

Key Terms

Python Keywords

Programming Exercises

2 πthon: Estimating Pi

2.1 Objectives

2.2 What Is Pi?

2.3 More About the math Module

2.4 The Archimedes Approach

2.4.1 The Python Implementation

2.4.2 Developing a Function to Compute Pi

2.5 Accumulator Approximations

2.5.1 The Accumulator Pattern

2.5.2 Summation of Terms: The Leibniz Formula

2.5.3 Product of Terms: The Wallis Formula

2.6 A Monte Carlo Simulation

2.6.1 Boolean Expressions

2.6.2 Compound Boolean Expressions and Logical Operators

2.6.3 Selection Statements

2.6.4 Completing the Implementation

2.6.5 Adding Graphics

2.7 Summary

Key Terms

Python Keywords, Modules and Commands

Programming Exercises

3 Codes and Other Secrets

3.1 Objectives

3.2 The String Data Type

3.2.1 Concatenation

3.2.2 Repetition

3.2.3 Indexing

3.2.4 String Slicing

3.2.5 String Searching

3.2.6 String Methods

3.2.7 Character Functions

3.3 Encoding and Decoding Messages

3.4 Transposition Cipher

3.4.1 Encrypting Using Transposition

3.4.2 Decrypting a Transposed Message

3.4.3 Asking for Input

3.5 Substitution Cipher

3.6 Creating a Key

3.7 The Vigenère Cipher

3.8 Summary

Key Terms

New Python Keywords, Functions, and Constants

Programming Exercises

4 Introducing the Python Collections

4.1 Objectives

4.2 What Is Data?

4.3 Storing Data for Processing

4.3.1 Strings Revisited

4.3.2 Lists

4.4 Calculating Statistics on Data

4.4.1 Simple Dispersion

4.5 Central Tendency

4.5.1 Mean

4.5.2 Median

4.5.3 Mode

4.6 Frequency Distribution

4.6.1 Using a Dictionary to Compute a Frequency Table

4.6.2 Computing a Frequency Table Without a Dictionary

4.6.3 Visualizing a Frequency Distribution

4.7 Dispersion: Standard Deviation

4.8 Summary

Key Terms

Python Keywords, Functions, and Methods

Programming Exercises

5 Bigger Data: File I/O

5.1 Objectives

5.2 Using Files for Large Data Sets

5.2.1 Text Files

5.2.2 Iterating over Lines in a File

5.2.3 Writing a File

5.2.4 String Formatting

5.2.5 Alternative File-Reading Methods

5.3 Reading Data from the Internet

5.3.1 Using CSV Files

5.3.2 Using a while Loop to Process Data

5.3.3 List Comprehension

5.3.4 Reading JSON Data from the Internet

5.4 Correlating Data

5.5 Summary

Key Terms

Python Keywords and Functions

Programming Exercise

6 Image Processing

6.1 Objectives

6.2 What Is Digital Image Processing?

6.2.1 The RGB Color Model

6.2.2 The cImage Module

6.3 Basic Image Processing

6.3.1 Negative Images

6.3.2 Grayscale

6.3.3 A General Solution: The Pixel Mapper

6.4 Parameters, Parameter Passing, and Scope

6.4.1 Call by Assignment Parameter Passing

6.4.2 Namespaces

6.4.3 Calling Functions and Finding Names

6.4.4 Modules and Namespaces

6.5 Advanced Image Processing

6.5.1 Resizing

6.5.2 Stretching: A Different Perspective

6.5.3 Flipping an Image

6.5.4 Edge Detection

6.6 Summary

Key Terms

Python Keywords, Functions, and Variables

Programming Exercises

7 Data Mining: Cluster Analysis

7.1 Objectives

7.2 What Is Data Mining?

7.3 Cluster Analysis: A Simple Example

7.4 Implementing Cluster Analysis on Simple Data

7.4.1 Distance Between Two Points

7.4.2 Clusters and Centroids

7.4.3 The K-Means Cluster Analysis Algorithm

7.4.4 Implementation of K-Means

7.4.5 Implementation of K-Means, Continued

7.5 Implementing Cluster Analysis: Earthquakes

7.5.1 File Processing

7.5.2 Visualization

7.6 Cluster Analysis Shortcomings and Solutions

7.7 Summary

Key Terms

Python Keywords

Programming Exercises

8 Cryptanalysis

8.1 Objectives

8.2 Introduction

8.3 Cracking the Rail Fence

8.3.1 Checking Our Work with a Dictionary

8.3.2 A Brute-Force Solution

8.3.3 A Rail Fence Decryption Algorithm

8.4 Cracking the Substitution Cipher

8.4.1 Letter Frequency

8.4.2 Ciphertext Frequency Analysis

8.4.3 Letter Pair Analysis

8.4.4 Word Frequency Analysis

8.4.5 Pattern Matching with Partial Words

8.4.6 Regular Expression Summary

8.5 Summary

Key Terms

Python Functions, Methods, and Keywords

Programming Exercises

9 Fractals: The Geometry of Nature

9.1 Objectives

9.2 Introduction

9.3 Recursive Programs

9.3.1 Recursive Squares

9.3.2 Classic Recursive Functions

9.3.3 Drawing a Recursive Tree

9.3.4 The Sierpinski Triangle

9.3.5 Call Tree for a Sierpinski Triangle

9.4 Snowflakes, Lindenmayer, and Grammars

9.4.1 L-Systems

9.4.2 Automatically Expanding Production Rules

9.4.3 More Advanced L-Systems

9.5 Summary

Key Terms

Programming Exercises

10 Planet Objects

10.1 Objectives

10.2 Introduction

10.2.1 Programming

10.2.2 Object-Oriented Programming

10.2.3 Python Classes

10.3 Designing and Implementing a Planet Class

10.3.1 Constructor Method

10.3.2 Accessor Methods

10.3.3 Mutator Methods

10.3.4 Special Methods

10.3.5 Methods and self

10.3.6 Details of Method Storage and Lookup

10.4 Designing and Implementing a Sun Class

10.5 Designing and Implementing a Solar System

10.6 Animating the Solar System

10.6.1 Using Turtles

10.6.2 Planetary Orbits

10.6.3 Implementation

10.7 Summary

Key Terms

Python Keywords and Functions

Programming Exercises

11 Simulation

11.1 Objectives

11.2 Bears and Fish

11.3 What Is a Simulation?

11.4 Rules of the Game

11.5 Design

11.6 Implementation

11.6.1 The World Class

11.6.2 The Fish Class

11.6.3 The Bear Class

11.6.4 Main Simulation

11.7 Growing Plants

11.8 A Note on Inheritance

11.9 Summary

Key Terms

Python Keywords and Functions

Programming Exercises

12 Father Was a Rectangle

12.1 Objectives

12.2 Introduction

12.3 First Design

12.4 Basic Implementation

12.4.1 The Canvas Class

12.4.2 The GeometricObject Class

12.4.3 The Point Class

12.4.4 The Line Class

12.4.5 Testing Our Implementation

12.5 Understanding Inheritance

12.6 Limitations

12.7 An Improved Implementation

12.8 Implementing Polygons

12.9 Summary

Key Terms

Python Keywords, Methods, and Decorator

Programming Exercises

13 Video Games

13.1 Objectives

13.2 Introduction

13.2.1 Event-Driven Programming

13.2.2 Simulating an Event Loop

13.2.3 A Multithreaded Event Loop

13.3 Event-Driven Programming with the Turtle

13.3.1 A Simple Etch-a-Sketch Using Key Presses

13.3.2 Placing Turtles Using Mouse Clicks

13.3.3 Bouncing Turtles

13.4 Creating Your Own Video Game

13.4.1 The LaserCannon Class

13.4.2 The BoundedTurtle Class

13.4.3 The Drone Class

13.4.4 The Bomb Class

13.4.5 Putting All the Pieces Together

13.5 Summary

Key Terms

Python Keywords and Decorator

Programming Exercises

APPENDIX A Installing the Required Software

A.1 Installing Python

A.2 Installing the Python Image Library and cImage

APPENDIX B Python Quick Reference

B.1 Python Reserved Words

B.2 Numeric Data Types

B.3 Built-in Functions

B.4 Sequence Operators

B.5 Dictionaries

B.6 Files

B.7 Formatting Output

B.8 Iteration

B.9 Boolean Expressions

B.10 Selection

B.11 Python Modules

B.12 Regular Expression Patterns

B.13 Defining Functions

B.14 Defining Classes

B.15 Deleting Objects

B.16 Common Error Messages

APPENDIX C turtle Reference

C.1 Basic Move and Draw

C.2 Turtle State

C.3 Drawing State

C.4 Filling

C.5 More Drawing Control

C.6 Controlling the Shape and Appearance

C.7 Measurement Settings

C.8 Drawing Speed

C.9 Color

C.10 Events

C.11 Miscellaneous

APPENDIX D Answers to Selected “Try It Out” Exercises

INDEX