Python Programming in Context 2nd edition by Bradley Miller, David Ranum – Ebook PDF Instant Download/Delivery: 1284089045 , 9781284089042
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ISBN 10: 1284089045
ISBN 13: 9781284089042
Author: Bradley Miller, David Ranum
A user-friendly, object-oriented language, Python is quickly becoming the favorite introductory programming language among students and instructors. Many find Python to be a more lucid language than Java but with much of the functionality and therefore the ideal first language for those entering the world of Computer Science. Python Programming in Context, Second Edition is a clear, accessible introduction to the fundamental programming and problem solving concepts necessary for students at this level. The authors carefully build upon the many important computer science concepts and problem solving techniques throughout the text and offer relevant, real-world examples and exercises to reinforce key material. Programming skills throughout the text are linked to applied areas such as Image Processing, Cryptography, Astronomy, Music, the Internet, and Bioinformatics, giving students a well-rounded look of its capabilities.
Python Programming in Context 2nd Table of contents:
1 Introduction
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
Integer Numbers
Floating-Point Numbers
Complex Numbers
Summary of Numeric Types
1.5.2 Naming Objects
1.5.3 Abstraction
The turtle Module
Writing Your Own Functions
1.5.4 Repetition
Drawing a Spiral
Drawing a Circle
1.6 Summary
Key Terms
Python Keywords
Bibliography
Programming Exercises
2 πthon
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
Bibliography
Programming Exercises
3 Codes and Other Secrets
3.1 Objectives
3.2 Introduction
3.2.1 Concatenation
3.2.2 Repetition
3.2.3 Indexing
3.2.4 Slicing
3.2.5 String Methods
3.2.6 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 Vignère Cipher
3.8 Summary
Key Terms
Python Keywords
Bibliography
Programming Exercises
4 A Nest of Snakes: 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 Simple Dispersion
4.5 Central Tendency
4.5.1 Mean
4.5.2 Median
4.5.3 Mode
Python Dictionaries
Computing the 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
Bibliography
Programming Exercises
5 Earthquakes, Floods, and Other Natural Disasters
5.1 Objectives
5.2 Using Files for Large Data Sets
5.2.1 Iterating over Lines in a File
5.2.2 Writing a File
5.2.3 String Formatting
5.2.4 Alternative File-Reading Methods
5.2.5 Statistics with Real Data
Earthquakes
Earthquake Statistics
5.3 Reading Data from the Internet
5.3.1 Using a while Loop to Process Data
5.3.2 Stock Market Data
Accessing Stock Data
Correlating Stock Data
5.4 Summary
Key Terms
Python Keywords
Bibliography
Programming Exercise
6 Pycture Perfect Programs
6.1 Objectives
6.2 What Is Digital Image Processing?
6.2.1 The RGB Color Model
6.2.2 The cImage Module
The Pixel Object
The ImageWin Object
The FileImage Object
The EmptyImage Object
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
Bibliography
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
Indefinite Iteration
The while loop
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
Bibliography
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 Keywords
Bibliography
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
Python Keywords
Bibliography
Programming Exercises
10 Astronomy
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
Distance Between Objects
Velocity
Acceleration
Calculating Distance from Velocity and Velocity from Acceleration
Mass and Gravity
Interaction of the Planets
10.6.3 Implementation
10.7 Summary
Key Terms
Python Keywords
Bibliography
Programming Exercises
11 Bears, Fish, and Plants, Oh My!
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
Bibliography
Programming Exercises
12 Your Father Was a Rectangle
12.1 Objectives
12.2 Introduction
12.3 First Design
12.4 Basic Implementation
12.4.1 Canvas
12.4.2 GeometricObject
12.4.3 Point
12.4.4 Line
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
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 turtle
13.3.1 A Simple Etch-a-Sketch
13.3.2 Placing Turtles
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 Alien Class
13.4.4 The Bomb Class
13.4.5 Putting All the Pieces Together
13.5 Summary
Key Terms
Bibliography
Python Keywords
Programming Exercises
A Installing the Required Software
A.1 Installing Python
A.2 Installing the Python Image Library and cImage
B Python Quick Reference
B.1 Python Reserved Words
B.2 Numeric Data Types
B.3 Sequences
B.3.1 String
B.3.2 List
B.3.3 Tuple
B.4 Dictionaries
B.5 Files
B.6 Formatting Output
B.7 Iteration
B.7.1 Simple Iteration over Collections of Data
B.7.2 Iteration with while
B.7.3 List Comprehensions
B.8 Boolean Expressions
B.8.1 Relational Operators
B.8.2 Compound Boolean Expressions
B.9 Selection
B.9.1 Binary Selection
B.9.2 Unary Selection
B.9.3 Nested Selection with elif
B.10 Python Modules
B.10.1 Math
B.10.2 Random Numbers
B.10.3 Regular Expression Patterns
B.11 Defining Functions
B.12 Defining Classes
B.13 Common Error Messages
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
Index
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Tags: Bradley Miller, David Ranum, Python Programming