Classroom-tested by generations of students, this new edition of the popular intro to programming book is for anyone who wants to understand computer science.
Learn about design, algorithms, testing, and debugging. Discover the fundamentals of programming with Python: a language that's used across industries and platforms. Write programs to solve real-world problems, and come away with everything you need to produce quality code. This edition has been updated to use the new language features in Python 3.14.
No programming experience required! Incremental examples show you the steps and missteps that happen while developing programs, so you know what to expect when you tackle a problem on your own. Inspired by "How to Design Programs" (HtDP), discover a five-step recipe for designing functions, which helps you learn the concepts-and becomes an integral part of writing programs.
In this detailed introduction to Python and to computer programming, find out exactly what happens when your programs are executed. Work with numbers, text, sequences, and files using real-world examples. Create and use your own data types. Make your programs robust and reliable; develop an idiomatic programming style; download data from the web automatically. As you use the fundamental programming tools in this book, you'll see how to document and organize your code so that you and other programmers can more easily read and understand it. This new edition takes advantage of Python 3.14's new features, including f-strings, the walrus operator, and richer type annotations on parameters, return types, and variable declarations.
Most importantly, you'll learn how to think like a professional programmer.
Table of Contents:
- Acknowledgments
- Our Approach
- Further Reading
- What You’ll See
- What’s Programming?
- Programs and Programming
- What’s a Programming Language?
- What’s a Bug?
- The Difference Between Brackets, Braces, and Parentheses
- Installing Python
- Hello, Python
- How Does a Computer Run a Python Program?
- Expressions and Values: Arithmetic in Python
- What Is a Type?
- Variables and Computer Memory: Remembering Values
- How Python Tells You Something Went Wrong
- A Single Statement That Spans Multiple Lines
- Describing Code
- Making Code Readable
- The Object of This Chapter
- Exercises
- Designing and Using Functions
- Functions That Python Provides
- Identities: How Python Keeps Track of Values
- Defining Custom Functions
- Using Local Variables for Temporary Storage
- Tracing Function Calls in the Memory Model
- Designing New Functions: A Recipe
- Writing and Running a Program
- Omitting a return Statement: None
- Dealing with Situations That Your Code Doesn’t Handle
- What Did You Call That?
- Exercises
- Working with Text
- Creating Strings of Characters
- Using Special Characters in Strings
- Creating a Multiline String
- Printing Information
- Getting Information from the Keyboard
- Formatted Strings
- Quotes About Strings
- Exercises
- Making Choices
- A Boolean Type
- Choosing Which Statements to Execute
- Nested if Statements
- Memorizing Results of a Boolean Expression Evaluation
- You Learned About Booleans: True or False?
- Exercises
- A Modular Approach to Program Organization
- Importing Modules
- Defining Your Modules
- Testing Your Code Semiautomatically
- Tips for Grouping Your Functions
- Organizing Your Thoughts
- Exercises
- Using Methods
- Modules, Classes, and Methods
- Calling Methods
- Exploring String Methods
- What Are Those Underscores?
- A Methodical Review
- Exercises
- Storing Collections of Data Using Lists
- Storing and Accessing Data in Lists
- Type Annotations for Lists
- Modifying Lists
- Operations on Lists
- Slicing Lists
- Aliasing: What’s in a Name?
- List Methods
- Working with a List of Lists
- Splitting Strings
- A Summary List
- Exercises
- Repeating Code Using Loops
- Processing Items in a List
- Processing Characters in Strings
- Looping Over a Range of Numbers
- Processing Lists Using Indices
- Nesting Loops in Loops
- Looping Until a Condition Is Reached
- Repetition Based on User Input
- Controlling Loops Using break and continue
- Repeating What You’ve Learned
- Exercises
- Reading and Writing Files
- What Kinds of Files Are There?
- Opening a File
- Techniques for Reading Files
- Files over the Internet
- Writing Files
- Writing Example Calls Using StringIO
- Writing Algorithms That Use the File-Reading Techniques
- Multiline Records
- Looking Ahead
- Notes to File Away
- Exercises
- Storing Data Using Other Collection Types
- Storing Data Using Sets
- Storing Data Using Tuples
- Storing Data Using Dictionaries
- Inverting a Dictionary
- Using the in Operator on Tuples, Sets, and Dictionaries
- Comparing Collections
- Creating New Type Annotations
- A Collection of New Information
- Exercises
- Designing and Benchmarking Algorithms
- Searching for the Two Smallest Values
- Timing the Functions
- At a Minimum, You Saw This
- Exercises
- Searching and Sorting
- Searching a List
- Binary Search
- Sorting
- More Efficient Sorting Algorithms
- Merge Sort: A Faster Sorting Algorithm
- Sorting Out What You Learned
- Exercises
- Object-Oriented Programming
- Understanding a Problem Domain
- Function isinstance, Class object, and Class Book
- Writing a Method in Class Book
- Plugging into Python Syntax: More Special Methods
- A Little Bit of OO Theory
- A Case Study: Molecules, Atoms, and PDB Files
- Classifying What You’ve Learned
- Exercises
- Testing and Debugging
- Why Do You Need to Test?
- Case Study: Testing above_freezing
- Case Study: Testing running_sum
- Choosing Test Cases
- Hunting Bugs
- Bugs We’ve Put in Your Ear
- Exercises
- Mastering Iteration Tools
- Core Idioms
- Functional Programming
- Built-In and Standard Library Helpers
- Let’s Reiterate
- Exercises
- Handling Exceptions
- Core Idioms
- Accessing Exception Details
- Common Built-in Exceptions
- Raising and Chaining Exceptions
- Defining Custom Exceptions
- Exceptionally Important!
- Exercises
Review :
I wish I could go back in time and give this book to my 10-year-old self when I first learned programming! It's so much more engaging, practical, and accessible than the dry introductory programming books that I tried (and often failed) to comprehend as a kid. I love the authors' hands-on approach of mixing explanations with code snippets that students can type into the Python prompt.
— Philip Guo, Creator of Online Python Tutor, Assistant Professor, Department of Cognitive Science, UCSD
Practical Programming delivers just what it promises: a clear, readable, usable introduction to programming for beginners. This isn't just a guide to hacking together programs. The book provides foundations to lifelong programming skills: a crisp, consistent, and visual model of memory and execution and a design recipe that will help readers produce quality software.
— Steven Wolfman, Professor of Teaching, Department of Computer Science, University of British Columbia
This excellent text reflects the authors' many years of experience teaching Python to beginning students. Topics are presented so that each leads naturally to the next, and common novice errors and misconceptions are explicitly addressed. The exercises at the end of each chapter invite interested students to explore computer science and programming language topics.
— Kathleen Freeman, Director of Undergraduate Studies, Department of Computer and Information Science, University of Oregon
I've written and read a lot of introductory texts in my forty-six years as a computer science faculty member. This one takes the cake. It presents the material in an appropriate order, talks in a manner that beginners can understand, and covers topics in a way that helps people learn Python. If I were to teach an introductory course using Python, this is the text I would use.
— David Gries, Professor Emeritus, Department of Computer Science, Cornell University
