Foundations of Python Programming

This interactive book is a product of the Runestone Interactive Project.

• This book is based on the Original work by: Jeffrey Elkner, Allen B. Downey, and Chris Meyers, the Interactive edition of How to Think Like a Computer Scientist by Brad Miller, David Ranum and many more and Programs Information and People by Paul Resnick

• Activecode based on Skulpt

• Codelens based on Online Python Tutor

• Many contributions from the CSLearning4U research group at Georgia Tech.

• ACM-SIGCSE for the special projects grant that funded our student Isaac Dontje Lindell for the summer of 2013.

• NSF

The Runestone Interactive tools are open source and we encourage you to contact us, or grab a copy from GitHub <https://github.com/RunestoneInteractive> if you would like to use them to write your own resources.

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Table of Contents

• 1. General Introduction
  • 1.1. Introduction: The Way of the Program
    • 1.1.1. Learning Goals
    • 1.1.2. Objectives
  • 1.2. Algorithms
  • 1.3. The Python Programming Language
  • 1.4. Special Ways to Execute Python in this Book
  • 1.5. More About Programs
    • 1.5.1. Preview of Control Structures
  • 1.6. Formal and Natural Languages
  • 1.7. A Typical First Program
  • 1.8. 👩‍💻 Predict Before You Run!
  • 1.9. 👩‍💻 To Understand a Program, Change It!
  • 1.10. Comments
  • 1.11. Glossary
  • 1.12. Chapter Assessment
    • 1.12.1. Contributed Exercises
• 2. Variables, Statements, and Expressions
  • 2.1. Introduction
    • 2.1.1. Learning Goals
    • 2.1.2. Objectives
  • 2.2. Values and Data Types
  • 2.3. Operators and Operands
  • 2.4. Function Calls
    • 2.4.1. Function calls as part of complex expressions
    • 2.4.2. Functions are objects; parentheses invoke functions
  • 2.5. Data Types
  • 2.6. Type conversion functions
  • 2.7. Variables
  • 2.8. Variable Names and Keywords
  • 2.9. 👩‍💻 Choosing the Right Variable Name
  • 2.10. Statements and Expressions
  • 2.11. Order of Operations
  • 2.12. Reassignment
    • 2.12.1. Developing your mental model of How Python Evaluates
  • 2.13. Updating Variables
  • 2.14. 👩‍💻 Hard-Coding
  • 2.15. Input
  • 2.16. Glossary
  • 2.17. Exercises
    • 2.17.1. Contributed Exercises
  • 2.18. Chapter Assessment
• 3. Debugging
  • 3.1. Introduction to Debugging
    • 3.1.1. Learning Goals
    • 3.1.2. Objectives
  • 3.2. 👩‍💻 Programming in the Real World
  • 3.3. 👩‍💻 Debugging
    • 3.3.1. How to Avoid Debugging
  • 3.4. 👩‍💻 Beginning tips for Debugging
  • 3.5. Syntax errors
  • 3.6. Runtime Errors
  • 3.7. Semantic Errors
    • 3.7.1. Test Cases
  • 3.8. 👩‍💻 Know Your Error Messages
    • 3.8.1. SyntaxError
    • 3.8.2. TypeError
    • 3.8.3. NameError
    • 3.8.4. ValueError
  • 3.9. Exercises
    • 3.9.1. Contributed Exercises
• 4. Python Modules
  • 4.1. Introduction to Python Modules
    • 4.1.1. Learning Goals
    • 4.1.2. Objectives
  • 4.2. Modules
    • 4.2.1. Importing Modules
    • 4.2.2. Syntax for Importing Modules and Functionality
  • 4.3. The random module
  • 4.4. Glossary
  • 4.5. Exercises
    • 4.5.1. Contributed Exercises
• 5. Python Turtle
  • 5.1. Hello Little Turtles!
    • 5.1.1. Learning Goals
    • 5.1.2. Objectives
  • 5.2. Our First Turtle Program
  • 5.3. Instances: A Herd of Turtles
  • 5.4. Object Oriented Concepts
    • 5.4.1. User-defined Classes
    • 5.4.2. Instances
    • 5.4.3. Attributes
    • 5.4.4. Methods
  • 5.5. Repetition with a For Loop
  • 5.6. A Few More turtle Methods and Observations
  • 5.7. Summary of Turtle Methods
  • 5.8. 👩‍💻 Incremental Programming
  • 5.9. 👩‍💻 Common turtle Errors
  • 5.10. Exercises
    • 5.10.1. Contributed Exercises
  • 5.11. Chapter Assessment - Turtle and Object Mechanics
  • 5.12. Chapter Assessment - Drawing with Turtle
• 6. Sequences
  • 6.1. Introduction: Sequences
    • 6.1.1. Learning Goals
    • 6.1.2. Objectives
  • 6.2. Strings, Lists, and Tuples
    • 6.2.1. Strings
    • 6.2.2. Lists
    • 6.2.3. Tuples
  • 6.3. Index Operator: Working with the Characters of a String
    • 6.3.1. Index Operator: Accessing Elements of a List or Tuple
  • 6.4. Disambiguating []: creation vs indexing
  • 6.5. Length
  • 6.6. The Slice Operator
    • 6.6.1. List Slices
    • 6.6.2. Tuple Slices
  • 6.7. Concatenation and Repetition
  • 6.8. Count and Index
    • 6.8.1. Count
    • 6.8.2. Index
  • 6.9. Splitting and Joining Strings
  • 6.10. Exercises
    • 6.10.1. Contributed Exercises
  • 6.11. Chapter Assessment
• 7. Iteration
  • 7.1. Introduction: Iteration
  • 7.2. The for Loop
  • 7.3. Flow of Execution of the for Loop
  • 7.4. Strings and for loops
  • 7.5. Lists and for loops
    • 7.5.1. Using the range Function to Generate a Sequence to Iterate Over
    • 7.5.2. Iteration Simplifies our Turtle Program
  • 7.6. The Accumulator Pattern
  • 7.7. Traversal and the for Loop: By Index
  • 7.8. Nested Iteration: Image Processing
    • 7.8.1. The RGB Color Model
    • 7.8.2. Image Objects
    • 7.8.3. Image Processing and Nested Iteration
  • 7.9. 👩‍💻 Printing Intermediate Results
  • 7.10. 👩‍💻 Naming Variables in For Loops
  • 7.11. The Gory Details: Iterables
  • 7.12. 👩‍💻 Keeping Track of Your Iterator Variable and Your Iterable
  • 7.13. Glossary
  • 7.14. Exercises
    • 7.14.1. Contributed Exercises
  • 7.15. Chapter Assessment
• 8. Conditionals
  • 8.1. Intro: What we can do with Turtles and Conditionals
    • 8.1.1. Learning Goals
    • 8.1.2. Objectives
  • 8.2. Boolean Values and Boolean Expressions
  • 8.3. Logical operators
    • 8.3.1. Smart Evaluation
  • 8.4. The in and not in operators
  • 8.5. Precedence of Operators
  • 8.6. Conditional Execution: Binary Selection
  • 8.7. Omitting the else Clause: Unary Selection
  • 8.8. Nested conditionals
  • 8.9. Chained conditionals
  • 8.10. The Accumulator Pattern with Conditionals
    • 8.10.1. Accumulating the Max Value
  • 8.11. 👩‍💻 Setting Up Conditionals
    • 8.11.1. Choosing your type of Conditional
  • 8.12. Glossary
  • 8.13. Exercises
    • 8.13.1. Contributed Exercises
  • 8.14. Chapter Assessment
• 9. Transforming Sequences
  • 9.1. Introduction: Transforming Sequences
    • 9.1.1. Learning Goals
    • 9.1.2. Objectives
  • 9.2. Mutability
    • 9.2.1. Lists are Mutable
    • 9.2.2. Strings are Immutable
    • 9.2.3. Tuples are Immutable
  • 9.3. List Element Deletion
  • 9.4. Objects and References
  • 9.5. Aliasing
  • 9.6. Cloning Lists
  • 9.7. Mutating Methods
    • 9.7.1. List Methods
  • 9.8. Append versus Concatenate
  • 9.9. Non-mutating Methods on Strings
  • 9.10. String Format Method
  • 9.11. f-Strings
  • 9.12. The Accumulator Pattern with Lists
  • 9.13. The Accumulator Pattern with Strings
  • 9.14. 👩‍💻 Accumulator Pattern Strategies
    • 9.14.1. When to Use it
    • 9.14.2. Before Writing it
    • 9.14.3. Choosing Good Accumulator and Iterator Variable Names
  • 9.15. 👩‍💻 Don’t Mutate A List That You Are Iterating Through
  • 9.16. Summary
  • 9.17. Exercises
    • 9.17.1. Contributed Exercises
  • 9.18. Chapter Assessment - List Methods
    • 9.18.1. Chapter Assessment - Aliases and References
    • 9.18.2. Chapter Assessment - Split and Join
    • 9.18.3. Chapter Assessment - For Loop Mechanics
    • 9.18.4. Chapter Assessment - Accumulator Pattern
    • 9.18.5. Chapter Assessment - Problem Solving
• 10. Files
  • 10.1. Introduction: Working with Data Files
    • 10.1.1. Learning Goals
    • 10.1.2. Objectives
  • 10.2. Reading a File
  • 10.3. Alternative File Reading Methods
  • 10.4. Iterating over lines in a file
  • 10.5. Finding a File in your Filesystem
  • 10.6. Using with for Files
  • 10.7. Recipe for Reading and Processing a File
  • 10.8. Writing Text Files
  • 10.9. CSV Format
  • 10.10. Reading in data from a CSV File
  • 10.11. Writing data to a CSV File
  • 10.12. 👩‍💻 Tips on Handling Files
  • 10.13. Glossary
  • 10.14. Exercises
    • 10.14.1. Contributed Exercises
  • 10.15. Chapter Assessment
• 11. Dictionaries
  • 11.1. Introduction: Dictionaries
    • 11.1.1. Learning Goals
    • 11.1.2. Objectives
  • 11.2. Getting Started with Dictionaries
  • 11.3. Dictionary operations
  • 11.4. Dictionary methods
    • 11.4.1. Iterating over Dictionaries
    • 11.4.2. Safely Retrieving Values
  • 11.5. Aliasing and copying
  • 11.6. Introduction: Accumulating Multiple Results In a Dictionary
  • 11.7. Accumulating Results From a Dictionary
  • 11.8. Accumulating the Best Key
  • 11.9. 👩‍💻 When to use a dictionary
  • 11.10. Glossary
  • 11.11. Exercises
    • 11.11.1. Contributed Exercises
  • 11.12. Chapter Assessment
    • 11.12.1. Assessment - Dictionaries
    • 11.12.2. Assessment - Dictionary Accumulation
• 12. Functions
  • 12.1. Introduction to Functions
    • 12.1.1. Topics
    • 12.1.2. Learning Objectives
  • 12.2. Function Definition
  • 12.3. Function Invocation
  • 12.4. Function Parameters
  • 12.5. Returning a value from a function
  • 12.6. 👩‍💻 Decoding a Function
  • 12.7. Type Annotations
  • 12.8. A function that accumulates
  • 12.9. Variables and parameters are local
  • 12.10. Global Variables
  • 12.11. Functions can call other functions (Composition)
  • 12.12. Flow of Execution Summary
  • 12.13. 👩‍💻 Print vs. return
  • 12.14. Passing Mutable Objects
  • 12.15. Side Effects
  • 12.16. Glossary
  • 12.17. Exercises
    • 12.17.1. Contributed Exercises
  • 12.18. Chapter Assessment
• 13. Tuple Packing and Unpacking
  • 13.1. Introduction
    • 13.1.1. Learning Objectives
  • 13.2. Tuple Packing
  • 13.3. Tuple Assignment with Unpacking
    • 13.3.1. Swapping Values between Variables
    • 13.3.2. Unpacking Into Iterator Variables
    • 13.3.3. The Pythonic Way to Enumerate Items in a Sequence
  • 13.4. Tuples as Return Values
  • 13.5. Unpacking Tuples as Arguments to Function Calls
  • 13.6. Glossary
  • 13.7. Exercises
    • 13.7.1. Contributed Exercises
  • 13.8. Chapter Assessment
• 14. More About Iteration
  • 14.1. Introduction
    • 14.1.1. Learning Goals
    • 14.1.2. Objectives
  • 14.2. The while Statement
  • 14.3. The Listener Loop
    • 14.3.1. Other uses of while
      • 14.3.1.1. Sentinel Values
      • 14.3.1.2. Validating Input
  • 14.4. Randomly Walking Turtles
  • 14.5. Break and Continue
  • 14.6. 👩‍💻 Infinite Loops
  • 14.7. Exercises
    • 14.7.1. Contributed Exercises
  • 14.8. Chapter Assessment
• 15. Advanced Functions
  • 15.1. Introduction: Optional Parameters
  • 15.2. Keyword Parameters
    • 15.2.1. Keyword Parameters with .format
  • 15.3. Anonymous functions with lambda expressions
  • 15.4. 👩‍💻 Programming With Style
  • 15.5. Method Invocations
  • 15.6. Function Wrapping and Decorators
  • 15.7. Exercises
    • 15.7.1. Contributed Exercises
  • 15.8. Chapter Assessment
• 16. Sorting
  • 16.1. Introduction: Sorting with Sort and Sorted
  • 16.2. Optional reverse parameter
  • 16.3. Optional key parameter
  • 16.4. Sorting a Dictionary
  • 16.5. Breaking Ties: Second Sorting
  • 16.6. 👩‍💻 When to use a Lambda Expression
  • 16.7. Glossary
  • 16.8. Exercises
    • 16.8.1. Contributed Exercises
  • 16.9. Chapter Assessment
• 17. Nested Data and Nested Iteration
  • 17.1. Introduction: Nested Data and Nested Iteration
    • 17.1.1. Lists with Complex Items
  • 17.2. Nested Dictionaries
  • 17.3. Processing JSON results
  • 17.4. Nested Iteration
  • 17.5. 👩‍💻 Structuring Nested Data
  • 17.6. Deep and Shallow Copies
  • 17.7. 👩‍💻 Extracting from Nested Data
    • 17.7.1. Understand
    • 17.7.2. Extract
    • 17.7.3. Repeat
      • 17.7.3.1. Level 2
      • 17.7.3.2. Level 3
      • 17.7.3.3. Level 4
      • 17.7.3.4. Reflections
  • 17.8. Exercises
    • 17.8.1. Contributed Exercises
  • 17.9. Chapter Assessment
• 18. Test Cases
  • 18.1. Introduction: Test Cases
  • 18.2. Checking Assumptions About Data Types
  • 18.3. Checking Other Assumptions
  • 18.4. Testing Conditionals
  • 18.5. Testing Loops
  • 18.6. Writing Test Cases for Functions
    • 18.6.1. Return Value Tests
    • 18.6.2. Side Effect Tests
  • 18.7. Testing Optional Parameters
  • 18.8. 👩‍💻 Test Driven Development
  • 18.9. Glossary
  • 18.10. Chapter Assessment
  • 18.11. Exercises
    • 18.11.1. Contributed Exercises
• 19. Exceptions
  • 19.1. What is an exception?
  • 19.2. Exception Handling Flow-of-control
    • 19.2.1. Raising and Catching Errors
  • 19.3. 👩‍💻 When to use try/except
  • 19.4. Standard Exceptions
  • 19.5. Exercises
    • 19.5.1. Contributed Exercises
  • 19.6. Chapter Assessment
• 20. Defining your own Classes
  • 20.1. Introduction: Classes and Objects - the Basics
    • 20.1.1. Object-oriented programming
  • 20.2. Objects Revisited
  • 20.3. User Defined Classes
  • 20.4. Adding Parameters to the Constructor
  • 20.5. Adding Other Methods to a Class
  • 20.6. Objects as Arguments and Parameters
  • 20.7. Converting an Object to a String
  • 20.8. Instances as Return Values
  • 20.9. Sorting Lists of Instances
    • 20.9.1. Approach 1: Sorting Lists of Instances with key
    • 20.9.2. Approach 2: Defining Sort Orders with Comparison Operators
  • 20.10. Class Variables and Instance Variables
  • 20.11. Public and Private Instance Variables
  • 20.12. Thinking About Classes and Instances
  • 20.13. Testing classes
  • 20.14. A Tamagotchi Game
  • 20.15. Class Decorators
  • 20.16. Glossary
  • 20.17. Exercises
    • 20.17.1. Contributed Exercises
  • 20.18. Chapter Assessment
• 21. Building Programs
  • 21.1. Building A Program: A Strategy
    • 21.1.1. Sketch an Outline
    • 21.1.2. Code One Section at a Time
    • 21.1.3. Clean Up
  • 21.2. 👩‍💻 Sketch an Outline
  • 21.3. 👩‍💻 Code one section at a time
  • 21.4. 👩‍💻 Clean Up
  • 21.5. Exercises
    • 21.5.1. Contributed Exercises
• 22. Inheritance
  • 22.1. Introduction: Class Inheritance
  • 22.2. Inheriting Variables and Methods
    • 22.2.1. Mechanics of Defining a Subclass
    • 22.2.2. How the interpreter looks up attributes
  • 22.3. Overriding Methods
  • 22.4. Invoking the Parent Class’s Method
  • 22.5. Multiple inheritance
  • 22.6. Tamagotchi Revisited
  • 22.7. Exercises
    • 22.7.1. Contributed Exercises
  • 22.8. Chapter Assessment
  • 22.9. Project - Wheel of Python
• 23. More on Accumulation: Map, Filter, List Comprehension, and Zip
  • 23.1. Introduction: Map, Filter, List Comprehensions, and Zip
  • 23.2. Map
  • 23.3. Filter
  • 23.4. List Comprehensions
  • 23.5. Zip
  • 23.6. Exercises
    • 23.6.1. Contributed Exercises
  • 23.7. Chapter Assessment

Appendices

Project List

This book includes many projects. These projects are not meant to test your knowledge they are here to give you an opportunity to challenge yourself and your teammates to learn new programming and problem solving skills. Each project builds on the skills learned in the previous projects. If you are brand new to programming you will want to start at the beginning, if you have some prior experience, you can dive in with any project that looks interesting to you.

	Project	Skills Required	Learning Goal
1	A Preview of the End Goal	An Open Mind	What is programming?
2	Driving the Turtle	Turtle Graphics Basics	Your First Program
3	How Many Handshakes?	Statements and Expressions	Breaking down a problem
4	Drawing a Circle with a Turtle	🐢 Turtle Graphics | Repetition
5	Generating a Password XKCD Style	Sequences | Repetition	Working with Strings
6	Computing statistics with Kiva	Iteration | [Optional] Functions 12.1-12.5	Computing statistics on tabular data
7	Graphing Kiva Data with a Turtle	Conditionals | [Optional] Functions 12.1-12.5	Practice with Turtle Graphics, Graphing Basics
8	Graphing Kiva Data with Altair	Conditionals | [Optional] Functions 12.1-12.5	Transforming Data, Declarative Graphing
9	Substitution Cipher	Transforming Sequences | [Optional] Functions 12.1-12.5	String manipulation
10	Image Processing	Nested Iteration | [Optional] 12.1-12.5	Nested Iteration, Function Practice
11	Exploring Common Words and SETI	Files	Reading data from files
12	Monte Carlo Simulation	Files	Working with CSV files
13	Converting Roman Numerals	Dictionaries	Practice with dictionary operations
14	Stack Overflow Developer Survey	Dictionaries	Learn the split-apply-combine pattern
15	Image Processing Revisited	Functions	Using Functions
16	Turtles and Strings and L-Systems	Functions	Using Functions
17	Predicting Pizza Prices - Linear Regression	Functions	Functions and Statistics
18	Build your own Google	Functions	Functions, Dictionary, HTML, Web API’s
19	Better Pizza Predictions	More Iteration	Multiple Regression
20	K-means clustering	Advanced Functions	Clustering, Data Science
21	Sentiment Analysis of Climate Change Tweets	Advanced Functions	Text Processing, Bayes, Functions

Acknowledgements

Acknowledgements

• Copyright Notice
• Foreword
• Contributor List
• GNU Free Documentation License
• ADDENDUM: How to use this License for your documents

Index and Search

• Index

• Search Page

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