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1. Working with Data

1.1 The Different Types of Data 1.2 Introducing the Python Programming Language 1.3 Representing Data in Python 1.4 Storing Data in Variables 1.5 Building Up Data with Comprehensions 1.6 Application: Representing Colour

2. Functions

2.1 Python’s Built-In Functions 2.2 Defining Our Own Functions 2.3 Local Variables and Function Scope 2.4 Importing Modules 2.5 The Function Design Recipe 2.6 Testing Functions I: doctest and pytest 2.7 Type Conversion Functions 2.8 Application: Representing Text

3. Formal Logic

3.1 Propositional Logic 3.2 Predicate Logic 3.3 Filtering Collections 3.4 Conditional Execution 3.5 Simplifying If Statements 3.6 if __name__ == '__main__' 3.7 Function Specification 3.8 Richer Type Annotations 3.9 Working With Definitions 3.10 Testing Functions II: hypothesis 3.11 Working with Multiple Quantifiers

4. Working with Complex Data

4.1 Tabular Data 4.2 Defining Our Own Data Types, Part 1 4.3 Defining Our Own Data Types, Part 2 4.4 Repeated Execution: Loops 4.5 For Loop Variations 4.6 Index-Based For loops 4.7 Nested For Loops

5. Modifying Values and Variables

5.1 Variable Reassignment and Object Mutation 5.2 Operations on Mutable Data Types 5.3 The Full Python Memory Model: Introduction 5.4 Aliasing and “Mutation at a Distance” 5.5 The Full Python Memory Model: Function Calls 5.6 Testing Functions III: Testing Mutation

6. Formal Proofs

6.1 An Introduction to Number Theory 6.2 Proofs with Number Theory 6.3 Proofs and Algorithms I: Primality Testing 6.4 Proof by Cases and Disproofs 6.5 Greatest Common Divisor 6.6 Proofs and Algorithms II: Computing the Greatest Common Divisor 6.7 Modular Arithmetic

7. Cryptography

7.1 Introduction to Cryptography 7.2 The One-Time Pad and Perfect Secrecy 7.3 Computing Shared Secret Keys 7.4 The RSA Cryptosystem 7.5 Implementing RSA in Python 7.6 Application: Securing Online Communications

8. Analyzing Algorithm Running Time

8.1 An Introduction to Running Time 8.2 Comparing Asymptotic Function Growth with Big-O 8.3 Big-O, Omega, Theta 8.4 Analyzing Algorithm Running Time 8.5 Analyzing Comprehensions and While Loops 8.6 Analyzing Built-In Data Type Operations 8.7 Worst-Case Running Time Analysis 8.8 Testing Functions IV: Efficiency

9. Abstraction, Classes, and Software Design

9.1 An Introduction to Abstraction 9.2 Defining Our Own Data Types, Part 3 9.3 Data Types, Abstract and Concrete 9.4 Stacks 9.5 Exceptions as a Part of the Public Interface 9.6 Queues 9.7 Priority Queues 9.8 Defining a Shared Public Interface with Inheritance 9.9 The object Superclass

10. Building a Simulation

10.1 The Problem Domain: Food Delivery Networks 10.2 Object-Oriented Modelling of Our Problem Domain 10.3 A “Manager” Class 10.4 Food Delivery Events 10.5 Creating a Discrete-Event Simulation

A. Python Reference

A.1 Python Built-In Function Reference A.2 Python Built-In Data Types Reference A.3 Python Special Method Reference A.4 Python Exceptions Reference A.5 Python Syntax Diagrams

B. Python Libraries

B.1 doctest B.2 pytest B.3 python-ta B.4 typing B.5 pdb

C. Math Reference

C.1 Summations and Products C.2 Inequalities Links