Introduction to Computer Science in Python

• Context
  • Motivation for This Book
  • Resources Online
  • Computer Science, Broadly
  • Chapter Review Questions
• Episodes in Computing History
  • Numbers and Calculation
  • Nascent Computing Attempts
  • Communications and the Information Age
  • Looms and Mechanical Computing
  • Early Electronic Computing
  • “As We May Think” and the World Wide Web
  • Stored Program and Universal Computing
  • Further Reading
• Hardware and Software
  • What Is Hardware?
  • The Memory Hierarchy
  • Data Representation
  • Boolean Logic and Logic Gates
  • What Is Software?
  • How Hardware and Software Work Together
  • The Role of the Operating System
  • Processes: Programs in Motion
  • Types of Computer Systems
  • Information and Communication Technology Literacy
  • Metaphors for Hardware and Software
  • Exercises
• The Terminal and Python Setup
  • The Terminal
  • Installing and Setting Up Python
• Python Data and Operations
  • A Sample Python Program
  • Lab: Editing and Running Python Programs
  • Arithmetic
  • Variables and Assignment
  • Reading Python Syntax
  • Strings, Part I
  • Writing to the Screen
  • Python Program Structure
  • Combining Input and Output
  • String Special Cases
  • F-Strings and String Formatting
  • Types and Conversions
  • Learning to Solve Problems
  • Lab: Division Sentences
  • Chapter Review Questions
• Defining Functions of Your Own
  • A First Function Definition
  • Multiple Function Definitions
  • Function Parameters
  • Multiple Function Parameters
  • Returned Function Values
  • Type Hints for Functions
  • Two Roles: Writer and Consumer of Functions
  • Local Scope
  • Library Modules
  • Chapter Review Questions
• Modules and Variable Scope
  • Why Modules Matter
  • Importing Modules
  • Understanding Scope
  • Global and Nonlocal Variables
  • Variable Lifetime
  • Organizing Multi-File Projects
  • Common Errors
  • Exercises
• Basic String Operations
  • String Indexing and Slicing
  • String Methods and Length
  • A Creative Problem Solution
  • Lab: String Operations
  • Chapter Review Questions
• Decisions
  • Conditions
  • More Conditional Expressions
  • Compound Boolean Expressions
  • Simple if Statements
  • if-elif-else Statements
  • Nested if Statements
  • If-Statement Pitfalls
  • Chapter Review Questions
• User Input
  • The input() Function
  • Command-Line Interfaces with argparse
  • Reading Data from Files
  • Choosing the Right Input Method
  • Exercises
• While Loops
  • While Statements
  • User Input Utilities
  • Interactive while Loops
  • While Loops with Sequences
  • While Loop Examples
  • Greatest Common Divisor
  • Lab: Number Guessing Game
  • Chapter Review Questions
• For Loops
  • For Loop Syntax
  • The range() Function
  • For Loop Examples
  • List Comprehensions
  • Lab: Nested Loops
  • Chapter Review Questions
• Files, Paths, and Directories
  • Path Strings
  • Reading Files
  • Writing Files
  • Working with pathlib
  • Chapter Review Questions
• Error Handling
  • Types of Errors
  • Basic Exception Handling
  • Catching File Errors
  • Handling Errors Inside a Loop
  • Raising Exceptions
  • Prevention vs. Catching
  • Exercises
• Lists
  • List Syntax
  • List Methods
  • Searching
  • Sorting
  • Lab: Lists
  • Chapter Review Questions
• Linear Algebra in Python
  • Why Linear Algebra?
  • Vectors
  • Matrices
  • Applications: From Algebra to AI
• Tuples
  • Tuple Syntax
  • Tuple Examples
  • Tuple Unpacking
  • Chapter Review Questions
• Dictionaries
  • Dictionary Syntax
  • Dictionary Examples
  • Dictionary Efficiency
  • Lab: File Data and Collections
  • Chapter Review Questions
• Lists of Dictionaries
  • Why Lists of Dictionaries?
  • The One-Dictionary-Per-Record Principle
  • Consistent Structure with a Factory Function
  • Accessing Data
  • Iterating Over Records
  • Filtering Records
  • Searching for a Record
  • Updating a Record
  • Sorting
  • Grouping Records
  • Lists of Dictionaries and JSON
  • Exercises
• Dictionary Algorithms
  • Counting with Dictionaries
  • Filtering Dictionaries
  • Grouping with Dictionaries
  • Reversing a Dictionary
  • Merging Dictionaries
  • Safe Access with .get()
  • Nested Dictionaries
  • Algorithms on Lists of Dictionaries
  • Group by Length (Practice)
  • Real-World Applications
  • Exercises
• Internet Data
  • Internet Data
  • Case Study: Chicago 311 Graffiti Data
• Data Analysis with Pandas
  • Data Analysis with Pandas
• Monte Carlo Simulation
  • The Monte Carlo Method
  • Estimating π with Darts
  • How Accuracy Improves with N
  • Visualizing the Simulation
  • Where Monte Carlo Is Used
  • Exercises
• Classes and Object-Oriented Programming
  • A First Example of Class Instances
  • Class Instance Examples
  • Planning a Class Structure
  • Python Dataclasses and Named Tuples
  • The Rational Class
  • Chapter Review Questions
• Testing
  • Introduction to pytest
  • Writing Effective Tests
  • Chapter Review Questions
• Recursion
  • Introduction to Recursion
  • Recursion Examples
  • Recursive Filesystem Traversal
  • Recursive Descent Parsing
  • Chapter Review Questions
• Functional Programming
  • Functional Programming
  • Paradigms, Languages, and Types
  • Higher-Order Functions
  • Closures and Composition
  • Immutable Data and Pure Cores
  • Worked Examples: Newton and Monte Carlo
  • Testing for Correctness
  • Chapter Review Questions
  • Lab: Functional Programming
• Data Structures
  • Stacks and Queues
  • Linked Lists
  • Chapter Review Questions
• Terminal User Interfaces with Rich and Textual
  • Why Start with a Terminal UI?
  • Formatted Output with Rich
  • Adding a Summary
  • From Menus to Events
  • A Small Textual App
  • Keeping TUI Programs Understandable
  • Where Other Interfaces Fit
  • Exercises
• Case Studies
  • Case Study: Monte Carlo Simulation
  • Case Study: Chicago 311 Graffiti Data
• Alignment with ACM/IEEE Curriculum Standards
  • The CS Course Sequence
  • How to Read the KA Tables
  • Coverage Summary
  • Software Development Fundamentals (SDF)
  • Programming Languages (PL)
  • Algorithms and Complexity (AL)
  • Social Issues and Professional Practice (SP)
  • Architecture and Organization (AR)
  • Software Engineering (SE)
  • Gap Analysis
  • Notes on CS2023
  • Recommendations for Instructors
• Appendix
  • Suggested 15-Week Lesson Plan
  • Contributors
  • Contributing Guidelines
  • Acknowledgments
  • Command Line Introduction
  • Operator Precedence
  • Homework: Grade Calculation
  • Lab: Version Control
• Index