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Chapter 27: Object-Oriented Programming - Part 1

Real-world programs model real-world entities. A banking app has accounts with balances and transactions. A game has characters with health and abilities. An AI system has agents with state and capabilities. Object-Oriented Programming (OOP) is the paradigm for organizing code around these objects—bundles of data (attributes) and behavior (methods) that work together.

You'll learn why OOP matters for building scalable, maintainable applications—especially in AI-native development where agents themselves are objects with state and capabilities.

Starting from the limitations of procedural programming, you'll discover how OOP solves real-world problems through the four pillars: encapsulation, abstraction, inheritance, and polymorphism. Through practical examples ranging from bank accounts to AI agents, you'll build a solid foundation in class design, object creation, and method implementation.

The chapter culminates in a Game Character Capstone Project where you'll design and implement a multi-class system, integrating all the concepts learned into a cohesive, working application.

🎯 Before You Begin​

What You'll Learn​

By the end of this chapter, you will be able to:

  • Understand OOP Fundamentals — Explain what Object-Oriented Programming is and how it differs from procedural programming, identify the four pillars of OOP (Encapsulation, Abstraction, Inheritance, Polymorphism) in code examples, analyze when to use OOP vs procedural approaches, evaluate why OOP matters for modularity, reusability, maintainability, and scalability
  • Create Classes and Objects — Write Python class definitions with proper naming conventions and docstrings, implement constructors (__init__) that initialize attributes with type hints, create multiple objects from a single class with independent state, explain the role of self in instance methods
  • Work with Attributes and Methods — Define instance attributes and methods with appropriate access modifiers, use type hints for constructor parameters, attributes, and method returns, implement different method types (instance, class, static), apply encapsulation principles to protect data
  • Design Multi-Class Systems — Design interactions between multiple classes with clear responsibilities, model object relationships (composition, association) in class architecture, organize multi-class projects with proper module structure, integrate OOP patterns into cohesive systems
  • Apply OOP to AI-Native Development — Connect OOP principles to AI agent-based systems (agents as objects with state and behavior), describe how modern AI frameworks use classes to represent models, agents, and tools, collaborate with AI to design class structures and validate generated code, plan projects by describing architecture to AI