Data Encapsulation: Bundles data and methods within an object, hiding internal details and providing controlled access to the data.
Inheritance: Enables a new class to inherit properties and behaviors from an existing class, promoting code reusability and hierarchical organization.
Polymorphism: It allows objects to perform different functions based on the context (Class/Subclass) they are called in. In Python, this is mainly done using Method Overriding.
Data Abstraction: Hides implementation details, exposing only essential features of an object, improving code manageability and maintainability.
Composition: It allows a class to leverage the behaviors and functionalities of its component classes without necessarily inheriting from them. This is done by including the other class in the body of the object.
Intention of class structure, access protection, and abstract classes
Class Structure: The intention is to create blueprints (classes) for objects, which promotes code reuse and establishes a natural hierarchy between related classes.
Access Protection: The primary goal is to protect data from unrestricted access and modification. By using access specifiers (private, protected, public), it enforces data hiding, a core principle of encapsulation that enhances security and program stability.
Abstract Classes: The intention is to define a common interface for a group of subclasses while hiding complex implementation details. An abstract class cannot be instantiated on its own; it serves as a template that forces its child classes to implement specific methods, ensuring a consistent structure and improving code maintainability.