Python Programming An Introduction to Computer Science

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Python Programming An Introduction to Computer Science

PDF Free Download | Python Programming An Introduction to Computer Science by John M. Zelle

Contents of Python Programming eBook

  • Chapter 1. Computers and Programs
  • The Universal Machine
  • Program Power
  • What Is Computer Science?
  • Hardware Basics
  • Programming Languages
  • The Magic of Python
  • Inside a Python Program
  • Chaos and Computers
  • Exercises
  • Chapter 2. Writing Simple Programs
  • The Software Development Process
  • Exam pie Program: T em perature Converter
  • Elements of Programs
  • Names
  • Expressions
  • Assignment Statements
  • SimpIe Assignment
  • Assigning Input
  • Simultaneous Assignment
  • Definite Loops
  • Example Program: Future Value
  • Exercises
  • Chapter 3. Computing with Numbers
  • Numeric Data Types
  • Type Conversions and Rounding
  • Using the Math Library
  • Accumulating Results: Factorials
  • Limitations of Computer Arithmetic
  • Exercises
  • Chapter 4. Objects and Graphics
  • Overview
  • Simple Graphics Programming
  • Using Graphical Objects
  • Graphing Future Value
  • Choosing Coordinates
  • Interactive Graphics
  • Getting Mouse Clicks
  • Handling Textual Input
  • Graphics Module Reference
  • Graph Win Objects
  • Entry Objects
  • Displaying I mages
  • Generating Colors
  • Controlling Display Updates (Advanced)
  • Exercises
  • Chapter 5. Sequences: Strings, Lists, and Files
  • The String Data Type
  • Simple String Processing
  • Lists as Sequences
  • String Representation and Message Encoding
  • String Representation
  • Programming an Encoder
  • String Methods
  • Programming a Decoder
  • More String Methods
  • Lists Have Methods Too
  • From Encoding to Encryption
  • Input/Output as String Manipulation
  • Exam pie Application: Date Conversion
  • String Formatting
  • Better Change Counter
  • File Processing
  • Multi-line Strings
  • File Processing
  • Example Program: Batch Usernames
  • File Dialogs (Optional)
  • Exercises
  • Chapter 6. Defining Functions
  • The Function of Functions
  • Functions, Informally
  • Future Value with a Function
  • Functions and Para meters: The Exciting Deta i Is
  • Functions That Return Values
  • Functions that Modify Para meters
  • Functions and Program Structure
  • Exercises
  • Chapter 7. Decision Structures
  • Sim pie Decisions
  • Example: Temperature Warnings
  • Forming Simple Conditions
  • Example: Condition a I Program Execution
  • Two-Way Decisions
  • Multi-Way Decisions
  • Exception Handling
  • Study in Design: Max of Three
  • Strategy : Compare Each to All
  • Strategy : Decision Tree
  • Strategy : Sequential Processing
  • Strategy : Use Python
  • Some Lessons
  • Exercises
  • Chapter 8. Loop Structures and Booleans
  • For Loops: A Quick Review
  • Indefinite Loops
  • Common Loop Patterns
  • Interactive Loops
  • Sentinel Loops
  • File Loops
  • Nested Loops
  • Computing with Boo leans
  • Boolean Operators
  • Boolean Algebra
  • Other Common Structures
  • Post-test Loop
  • Loop and a Half
  • Boolean Expressions as Decisions
  • Example: A Simple Event Loop
  • Exercises
  • Chapter 9. Simulation and Design
  • A Simulation Problem
  • Ana lysis and Specification
  • Pseudo-random Numbers
  • Top-Down Design
  • Top-Level Design
  • Separation of Concerns
  • Second-Level Design
  • Designing simNGames
  • Third-Level Design
  • Finishing Up
  • Summary of the Design Process
  • Bottom-Up Implementation
  • Unit Testing
  • Simulation Results
  • Other Design Techniques
  • Prototyping and Spiral Development
  • The Art of Design
  • Exercises
  • Chapter 10. Defining Classes
  • Quick Review of Objects
  • Example Program: Cannonball
  • Program Specification
  • Designing the Program
  • Mod ularizing the Program
  • Defining New Classes
  • Example: Multi-sided Dice
  • Example: The Projectile Class
  • Data Processing with Class
  • Objects and Encapsulation
  • Encapsulating Useful Abstractions
  • Putting Classes in Modules
  • Module Documentation
  • Working with Multiple Modules
  • Widgets
  • Example Program: Dice Roller
  • Building Buttons
  • Building Dice
  • The Main Program
  • Drawing the Animation Window
  • Creating a Shot Tracker
  • Creating an Input Dialog
  • The Main Event Loop
  • Exercises
  • Chapter 11. Data Collections
  • Exam pie Problem: S i m pie Statistics
  • Applying Lists
  • Lists and Arrays
  • List perations
  • Statistics with Lists
  • Lists of Records
  • Designing with Lists and Classes
  • Case Study: Python Ca leu Ia tor
  • A Calculator as an Object
  • Constructing the Interface
  • Processing Buttons
  • Case Study: Better Can non ba II Animation
  • Creating a Launcher
  • Tracking Multiple Shots
  • Non-sequentiaI Collections
  • Dictionary Basics
  • Dictionary perations
  • Example Program: Word Frequency
  • Exercises
  • Chapter 12. Object-Oriented Design
  • The Process of OOD
  • Case Study: Racq uetba II Simulation
  • Candidate Objects and Methods
  • Implementing SimStats
  • Implementing RBaiiGame
  • Implementing Player
  • The Complete Program
  • Case Study: Dice Poker
  • Program Specification
  • Identifying Candidate Objects
  • Implementing the Model
  • A Text-Based U I
  • Developing a G U I
  • Concepts
  • Encapsulation
  • Polymorph ism
  • Inheritance
  • Exercises
  • Chapter 13. Algorithm Design and Recursion
  • Searching
  • Strategy : Linear Search
  • Strategy : Binary Search
  • Com paring Algorithms
  • Recursive Problem Solving
  • Recursive Definitions
  • Recursive Functions
  • Example: String Reversal
  • Example: Anagrams
  • Example: Fast Exponentiation
  • Example: Binary Search
  • Recursion vs Iteration
  • Sorting Algorithms
  • Native Sorting: Selection Sort
  • Divide and Conquer: Merge Sort
  • Hard Problems
  • Tower of Hanoi
  • The Halting Problem
  • Conclusion
  • Exercises

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