Building Python Programs

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

Table of 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