Python and Object-Oriented Programming (OOP)

• Python is a high-level, interpreted, general-purpose programming language.
• Python emphasizes code readability with its notable use of significant indentation.
• Python is dynamically typed and garbage-collected.
• It supports multiple programming paradigms, including structured (particularly procedural), object-oriented, and functional programming.
• Python is often described as a "batteries included" language due to its comprehensive standard library.

Core Concepts of Object-Oriented Programming (OOP)

• OOP is a programming paradigm based on the concept of "objects".
• Objects contain data, in the form of fields (also known as attributes or properties).
• Objects contain code, in the form of procedures (also known as methods).
• Objects methods can access and modify the data fields of the object with which they are associated.
• Computer programs are designed by making them out of objects that interact with one another in OOP.

Key Principles of OOP

• Abstraction shows only relevant object data, hiding unnecessary implementation details.
• Encapsulation restricts direct access to some of an object's components.
• Inheritance allows new objects to take on the properties of existing objects.
• Polymorphism allows objects to take on many forms.

Objects and Classes

• A class serves as a blueprint or a template for creating objects.
• Classes define the attributes (data) and methods (behavior) that its objects will possess.
• An object represents an instance of a class.
• Multiple objects can be created from a single class, each possessing its own unique data values.

Attributes (Data)

• Attributes are variables holding data associated with an object.
• Attributes represent the state of an object.
• Attributes are defined within a class.
• Each object of a class maintains its own set of values for these attributes.

Methods (Behavior)

• Methods are functions defining object behavior.
• Methods define what an object can do.
• Methods are defined within a class.
• Methods can access and modify object attributes.

Abstraction

• Abstraction simplifies complex concepts by modeling classes appropriately.
• It focuses on essential characteristics, while ignoring non-essential details.
• Abstraction provides a generalized view of objects.
• It hides implementation complexity from the user.

Encapsulation

• Encapsulation bundles data and the methods operating on that data within a single unit, namely a class.
• It restricts direct access to some of the object's components.
• It protects data integrity by preventing unauthorized access.
• Data access is typically provided through methods, specifically getters and setters.

Inheritance

• Inheritance is a mechanism where a new class (subclass or derived class) inherits properties and behavior from an existing class (superclass or base class).
• It promotes code reuse and reduces redundancy.
• The subclass can override or extend the functionality of the superclass.
• Types of inheritance include single, multiple, and multilevel inheritance.

Polymorphism

• Polymorphism means "many forms".
• It allows objects of different classes to respond to the same method call in their own way.
• Polymorphism is achieved through method overriding (in inheritance) and method overloading.
• It enables the creation of generic code compatible with objects of various types.

Class Definition in Python

• Classes are defined using the class keyword.
• The class name typically follows the PascalCase convention.
• The body of the class contains attributes and methods.

Constructor (__init__)

• The __init__ method serves as a constructor in Python.
• It is automatically called upon object creation.
• It is used to initialize object attributes.
• It accepts self as the first parameter, referring to the instance being created.

Self

• self is a reference to the current class instance.
• It is used to access the object's attributes and methods within the class.
• It is automatically passed as the first argument to instance methods.

Instance Methods

• Instance methods are functions defined within a class that operate on a class instance.
• They can access and modify object attributes.
• Instance methods are called using dot notation on an object such as object.method().

Class Methods

• Class methods are bound to the class and not the instance of the class.
• They can access and modify the class state.
• They are defined using the @classmethod decorator.
• They take cls as the first parameter, which refers to the class itself.

Static Methods

• Static methods are not bound to the instance or the class.
• They are essentially regular functions within a class.
• They lack access to object attributes or the class state.
• They are defined using the @staticmethod decorator.

Inheritance in Python

• A subclass inherits all attributes and methods of its superclass.
• To inherit from a class, specify the superclass in parentheses after the subclass name during class definition.
• The super() function is used to call superclass methods from within a subclass.
• Method overriding allows a subclass to provide a specific implementation for a method already defined in its superclass.

Polymorphism in Python

• Polymorphism is achieved through method overriding and duck typing.
• Method overriding lets subclasses implement superclass methods in their own specific ways.
• Duck typing is a concept prioritizing an object's methods over its type: "If it walks like a duck and quacks like a duck, then it is a duck".

Data Encapsulation in Python

• Python lacks strict access modifiers like private, protected, and public found in languages such as Java or C++.
• Naming conventions are used to indicate the intended visibility of attributes and methods.
• Attributes and methods starting with a single underscore _ are considered "protected", indicating they shouldn't be directly accessed from outside the class.
• Attributes/methods starting with double underscores __ undergo name mangling, making them harder but not impossible to access from outside the class.

Benefits of OOP

• Modularity: OOP encourages breaking down complex problems into smaller, manageable objects.
• Reusability: Inheritance allows you to reuse existing code and build upon it.
• Maintainability: Encapsulation and abstraction make code easier to understand and maintain.
• Scalability: OOP facilitates the development of large and complex systems.
• Flexibility: Polymorphism allows you to write generic code that can work with objects of different types.

Common OOP Design Principles

• Single Responsibility Principle: A class should have only one reason to change.
• Open/Closed Principle: Software entities (classes, modules, functions, etc.) should be open for extension but closed for modification.
• Liskov Substitution Principle: Subtypes must be substitutable for their base types without altering the correctness of the program.
• Interface Segregation Principle: Clients should not be forced to depend on methods they do not use.
• Dependency Inversion Principle: High-level modules should not depend on low-level modules. Both should depend on abstractions. Abstractions should not depend on details. Details should depend on abstractions.