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Full Description
For courses in Java programming.
A layered, back-to-basics approach to Python programming
The authors of the long successful title, Building Java Programs, bring their proven and class-tested, back-to-basics strategy to teaching Python programming for the first time in Building Python Programs. Their signature layered approach introduces programming fundamentals first, with new syntax and concepts added over multiple chapters. Object-oriented programming is discussed only after students have developed a basic understanding of Python programming. This newly published textfocuses on problem solving with an emphasis on algorithmic thinking and is appropriate for the two-semester sequence in introductory computer science.
Also available with MyLab Programming
By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student.With MyLab Programming, students work through hundreds of short, auto-graded coding exercises and receive immediate and helpful feedback based on their work.
Note: You are purchasing a standalone product; MyLab Programming does not come packaged with this content. Students, if interested in purchasing this title with MyLab Programming, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information.
If you would like to purchase both the physical text and MyLab Programming, search for:
0135287057/9780135287057 Building Python Programs Plus MyLab Programming with Pearson eText -- Access Card Package
Package consists of:
0135201276 / 9780135201275 MyLab Programming with Pearson eText -- Access Card -- for Building Python Programs
0135205980 / 9780135205983 Building Python Programs
Contents
Chapter 1 Introduction to Python Programming
1.1 Basic Computing Concepts
Why Programming?
Hardware and Software
The Digital Realm
The Process of Programming
Why Python?
The Python Programming Environment
1.2 And Now: Python
Printing Output
String Literals (Strings)
Escape Sequences
Printing a Complex Figure
Comments, Whitespace, and Readability
1.3 Program Errors
Syntax Errors
Logic Errors (Bugs)
1.4 Procedural Decomposition
Functions
Flow of Control
Identifiers and Keywords
Functions That Call Other Functions
An Example Runtime Error
1.5 Case Study: Drawing Figures
Structured Version
Final Version without Redundancy
Analysis of Flow of Execution
Chapter 2 Data and Definite Loops
2.1 Basic Data Concepts
Types
Expressions
Literals
Arithmetic Operators
Precedence
Mixing and Converting Types
2.2 Variables
A Program with Variables
Increment/Decrement Operators
Printing Multiple Values
2.3 The for Loop
Using a Loop Variable
Details about Ranges
String Multiplication and Printing Partial Lines
Nested for Loops
2.4 Managing Complexity
Scope
Pseudocode
Constants
2.5 Case Study: Hourglass Figure
Problem Decomposition and Pseudocode
Initial Structured Version
Adding a Constant
Chapter 3 Parameters and Graphics
3.1 Parameters
The Mechanics of Parameters
Limitations of Parameters
Multiple Parameters
Parameters versus Constants
Optional Parameters
3.2 Returning Values
The math Module
The random Module
Defining Functions That Return Values
Returning Multiple Values
3.3 Interactive Programs
Sample Interactive Program
3.4 Graphics
Introduction to DrawingPanel
Drawing Lines and Shapes
Colors
Drawing with Loops
Text and Fonts
Images
Procedural Decomposition with Graphics
3.5 Case Study: Projectile Trajectory
Unstructured Solution
Structured Solution
Graphical Version
Chapter 4 Conditional Execution
4.1 if/else Statements
Relational Operators
Nested if/else Statements
Factoring if/else Statements
Testing Multiple Conditions
4.2 Cumulative Algorithms
Cumulative Sum
Min/Max Loops
Cumulative Sum with if
Roundoff Errors
4.3 Functions with Conditional Execution
Preconditions and Postconditions
Raising Exceptions
Revisiting Return Values
Reasoning about Paths
4.4 Strings
String Methods
Accessing Characters by Index
Converting between Letters and Numbers
Cumulative Text Algorithms
4.5 Case Study: Basal Metabolic Rate
One-Person Unstructured Solution
Two-Person Unstructured Solution
Two-Person Structured Solution
Procedural Design Heuristics
Chapter 5 Program Logic and Indefinite Loops
5.1 The while Loop
A Loop to Find the Smallest Divisor
Loop Priming
5.2 Fencepost Algorithms
Fencepost with if
Sentinel Loops
Sentinel with Min/Max
5.3 Boolean Logic
Logical Operators
Boolean Variables and Flags
Predicate Functions
Boolean Zen
Short-Circuited Evaluation
5.4 Robust Programs
The try/except Statement
Handling User Errors
5.5 Assertions and Program Logic
Reasoning about Assertions
A Detailed Assertions Example
5.6 Case Study: Number Guessing Game
Initial Version without Hinting
Randomized Version with Hinting
Final Robust Version
Chapter 6 File Processing
6.1 File-Reading Basics
Data and Files
Reading a File in Python
Line-Based File Processing
Structure of Files and Consuming Input
Prompting for a File
6.2 Token-Based Processing
Numeric Input
Handling Invalid Input
Mixing Lines and Tokens
Handling Varying Numbers of Tokens
Complex Input Files
6.3 Advanced File Processing
Multi-Line Input Records
File Output
Reading Data from the Web
6.4 Case Study: ZIP Code Lookup
Chapter 7 Lists
7.1 List Basics
Creating Lists
Accessing List Elements
Traversing a List
A Complete List Program
Random Access
List Methods
7.2 List-Traversal Algorithms
Lists as Parameters
Searching a List
Replacing and Removing Values
Reversing a List
Shifting Values in a List
Nested Loop Algorithms
List Comprehensions
7.3 Reference Semantics
Values and References
Modifying a List Parameter
The Value None
Mutability
Tuples
7.4 Multidimensional Lists
Rectangular Lists
Jagged Lists
Lists of Pixels
7.5 Case Study: Benford's Law
Tallying Values
Completing the Program
Chapter 8 Dictionaries and Sets
8.1 Dictionary Basics
Creating a Dictionary
Dictionary Operations
Looping Over a Dictionary
Dictionary Ordering
8.2 Advanced Dictionary Usage
Dictionary for Tallying
Nested Collections
Dictionary Comprehensions
8.3 Sets
Set Basics
Set Operations
Set Efficiency
Set Example: Lottery
Chapter 9 Recursion
9.1 Thinking Recursively
A Nonprogramming Example
Iteration to Recursion
Structure of Recursive Solutions
Reversing a File
The Recursive Call Stack
9.2 Recursive Functions and Data
Integer Exponentiation
Greatest Common Divisor
Directory Crawler
9.3 Recursive Graphics
Cantor Set
Sierpinski Triangle
9.4 Recursive Backtracking
Traveling North/East
Eight Queens Puzzle
Stopping after One Solution
9.5 Case Study: Prefix Evaluator
Infix, Prefix, and Postfix Notation
Evaluating Prefix Expressions
Complete Program
Chapter 10 Searching and Sorting
10.1 Searching and Sorting Libraries
Binary Search
