Python for Everyone. 2nd Edition

  • ID: 3610078
  • Book
  • 752 Pages
  • John Wiley and Sons Ltd
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With Wiley s Interactive Edition, you get all the benefits of a downloadable, reflowable eBook with added resources to make your study time more effective, including: Lambda Expressions, Default & Static Method interfaces

Embedded Problem Solving Sections & How–To Guides

Worked Examples & Self–Check Exercises at the end of each chapter

Progressive Figures that trace code segments using color for easy recognition

Linked Programming Tips & Common Errors for programming best practices

Cay Horstmann′sPython for Everyone, Interactive Edition, 2nd Edition provides a comprehensive and approachable introduction to fundamental programming techniques and design skills, and helps students master basic concepts and become competent coders. The inclusion of advanced chapters makes the text suitable for a 2 or 3–term sequence, or as a comprehensive reference to programming in Python. Major rewrites and an updated visual design make this student–friendly text even more engaging. Filled with realistic programming examples, a great quantity and variety of homework assignments, and lab exercises that build student problem–solving abilities, it is no surprise Python for Everyone is the number one text for early objects in the Python market.
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Chapter 1: Introduction

1.1 Computer Programs

1.2 The Anatomy of a Computer

1.3 The Python Programming Language

1.4 Becoming Familiar with Your Programming Environment

1.5 Analyzing Your First Program

1.6 Errors

1.7 Problem Solving: Algorithm Design

Chapter 2: Programming with Numbers and Strings

2.1 Variables

2.2 Arithmetic

2.3 Problem Solving: First Do It By Hand

2.4 Strings

2.5 Input and Output

2.6 Graphics: Simple Drawings

Chapter 3: Decisions

3.1 The if Statement

3.2 Relational Operators

3.3 Nested Branches

3.4 Multiple Alternatives

3.5 Problem Solving: Flowcharts

3.6 Problem Solving: Test Cases

3.7 Boolean Variables and Operators

3.8 Analyzing Strings

3.9 Application: Input Validation

Chapter 4: Loops

4.1 The while Loop

4.2 Problem Solving: Hand–Tracing

4.3 Application: Processing Sentinel Values

4.4 Problem Solving: Storyboards

4.5 Common Loop Algorithms

4.6 The for Loop

4.7 Nested Loops

4.8 Processing Strings

4.9 Application: Random Numbers and Simulations

4.10 Graphics: Digital Image Processing

4.11 Problem Solving: Solve a Simpler Problem First

Chapter 5: Functions

5.1 Functions as Black Boxes

5.2 Implementing and Testing Functions

5.3 Parameter Passing

5.4 Return Values

5.5 Functions Without Return Values

5.6 Problem Solving: Reusable Functions

5.7 Problem Solving: Stepwise Refinement

5.8 Variable Scope

5.9 Graphics: Building an Image Processing Toolkit

5.10 Recursive Functions (Optional)

Chapter 6: Lists

6.1 Basic Properties of Lists

6.2 List Operations

6.3 Common List Algorithms

6.4 Using Lists with Functions

6.5 Problem Solving: Adapting Algorithms

6.6 Problem Solving: Discovering Algorithms by Manipulating Physical Objects

6.7 Tables

Chapter 7: Files and Exceptions

7.1 Reading and Writing Text Files

7.2 Text Input and Output

7.3 Command Line Arguments

7.4 Binary Files and Random Access

7.5 Exception Handling

7.6 Application: Handling Input Errors

Chapter 8: Sets and Dictionaries

8.1 Sets

8.2 Dictionaries

8.3 Complex Structures

Chapter 9: Objects and Classes

9.1 Object–Oriented Programming

9.2 Implementing a Simple Class

9.3 Specifying the Public Interface of a Class

9.4 Designing the Data Representation

9.5 Constructors

9.6 Implementing Methods

9.7 Testing a Class

9.8 Problem Solving: Tracing Objects

9.9 Problem Solving: Patterns for Object Data

9.10 Object References

9.11 Application: Writing a Fraction Class

Chapter 10: Inheritance

10.1 Inheritance Hierarchies

10.2 Implementing Subclasses

10.3 Calling the Superclass Constructor

10.4 Overriding Methods

10.5 Polymorphism

10.6 Application: A Geometric Shape Class Hierarchy

Chapter 11: RECURSION

11.1 Triangle Numbers Revisited

11.2 Problem Solving: Thinking Recursively

11.3 Recursive Helper Functions

11.4 The Efficiency of Recursion

11.5 Permutations

11.6 Backtracking

11.7 Mutual Recursion

Chapter 12: Sorting and Searching

12.1 Selection Sort

12.2 Profiling the Selection Sort Algorithm

12.3 Analyzing the Performance of the Selection Sort Algorithm

12.4 Merge Sort

12.5 Analyzing the Merge Sort Algorithm

12.6 Searching

12.7 Problem Solving: Estimating the Running Time of an Algorithm









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Cay Horstmann grew up in Northern Germany and attended the Christian–Albrechts–Universitat in Kiel, a harbor town at the Baltic sea. He received a M.S. in computer science from Syracuse University, and a Ph.D. in mathematics from the University of Michigan in Ann Arbor. For four years, he was VP and CTO of an Internet startup that went from 3 people in a tiny office to a public company. He now teaches computer science at San Jose State University. Cay also writes books and articles on programming languages and computer science education.
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