Introduction to Object-Oriented Programming in Python

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Introduction to Object-Oriented Programming in Python

Object-Oriented Programming (OOP) is a popular programming paradigm used to structure code in a more modular, reusable, and organized manner. Python, being a versatile and beginner-friendly language, supports OOP principles, making it easier for developers to build scalable and maintainable applications.

In OOP, the focus is on objects—real-world entities that have attributes (data) and behaviors (methods/functions). These objects are created from classes, which act as blueprints. Python makes working with classes and objects intuitive and simple.

Key Concepts of OOP in Python
Class and Object:
A class is a template for creating objects. An object is an instance of a class. For example:

python
class Car:
    def __init__(self, brand, model):
        self.brand = brand
        self.model = model
    
    def display_info(self):
        print(f"Brand: {self.brand}, Model: {self.model}")

my_car = Car("Toyota", "Camry")
my_car.display_info()
Encapsulation:
Encapsulation refers to bundling data and methods that operate on that data within a single unit (class). It also helps in hiding internal details from outside access. Python uses underscores to indicate private variables (e.g., _speed).

Inheritance:
Inheritance allows one class to inherit the attributes and methods of another, promoting code reusability.

python
class ElectricCar(Car):
    def __init__(self, brand, model, battery):
        super().__init__(brand, model)
        self.battery = battery
Polymorphism:
Polymorphism allows different classes to be treated as instances of the same class through shared methods. For instance, different classes can have the same method name but behave differently.

Abstraction:
Abstraction hides complex implementation details and shows only the essential features. In Python, abstraction is achieved through abstract base classes using the abc module.

Why Use OOP in Python?

Enhances code reusability and readability

Promotes DRY (Don’t Repeat Yourself) principle

Makes it easier to manage large codebases

Supports design patterns and software architecture best practices

Python’s OOP features make it an excellent choice for building robust applications—from web development and games to data analysis tools and AI systems. By mastering OOP in Python, developers can write cleaner and more efficient code, while also preparing for advanced software engineering concepts.

Read More

Python Lists, Tuples, Sets, and Dictionaries Explained

Python Conditional Statements (if, elif, else)

Looping in Python: For Loops and While Loops

Functions in Python: Parameters, Return Values, and Scope

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