What Is Object-Oriented Programming in Python?

A programming paradigm known as object-oriented programming offers a way to organize programs so that attributes and actions are combined into separate objects.

An object might, for instance, be a person having attributes like a name, age, and address as well as actions like breathing, jogging, walking, and conversing. Alternatively, it might be a representation of an email with attributes like a topic, body, and recipient list as well as actions like sending and attaching files.

In other words, object-oriented programming is a method for simulating tangible, real-world objects, like as cars, as well as relationships between objects, such as businesses and their staff or students and their instructors. Real-world items are modeled by OOP as software objects with related data and the ability to carry out certain tasks.

OOP also exists in other programming languages and is often described to center around the four pillars, or four tenants of OOP:

By using encapsulation, you may combine behaviors (methods) and data (attributes) into a class to form a coherent whole. Encapsulation supports modular, secure programs and preserves data integrity by establishing ways to restrict access to attributes and their alteration.
A subclass can inherit properties and methods from a parent class thanks to inheritance, which makes it possible to establish hierarchical relationships between classes. This lessens duplication and encourages code reuse.
The goal of abstraction is to reveal only an object’s core functionality while concealing implementation specifics. Abstraction streamlines interactions with things by imposing a uniform interface, freeing developers to concentrate on the functions of an object rather than how it does them.
As long as they implement a common interface or behavior, polymorphism enables you to treat objects of different kinds as instances of the same base type. Because Python’s duck typing lets you access attributes and functions on objects without worrying about their actual class, it’s particularly well-suited for polymorphism.

This lesson will help you grasp OOP in Python in a practical way. However, you might find it easier to recall the data you collect if you keep these four object-oriented programming concepts in mind.

The most important lesson learned is that Python object-oriented programming revolves around objects. Only the data is represented by objects in other programming paradigms. They also contribute to the general structure of the program in OOP.

1. ✅ Classes and Objects

The class keyword appears at the beginning of every class definition, followed by the class name and a colon. Any code that you indent beneath the class definition will be regarded by Python as belonging to the class body.

class Car:
def init(self, brand, color):
self.brand = brand
self.color = color

def start(self):
    print(f"The {self.color} {self.brand} car is starting.")

Creating objects

my_car = Car(“Toyota”, “Red”)
my_car.start()

🧾 Output:
The Red Toyota car is starting.

2. 🔐 Encapsulation

Encapsulation means hiding the internal state of an object and requiring all interactions to be performed through an object’s methods.

🔒 Example:

class BankAccount:
    def __init__(self, balance):
        self.__balance = balance  # private variable

    def deposit(self, amount):
        if amount > 0:
            self.__balance += amount

    def get_balance(self):
        return self.__balance

account = BankAccount(1000)
account.deposit(500)
print(account.get_balance())

🧾 Output:
1500

You can’t access __balance directly outside the class. It’s protected.

3. 🧬 Inheritance

Inheritance allows one class to inherit attributes and methods from another.

🧬 Example:

class Animal:
    def speak(self):
        print("I make a sound.")

class Dog(Animal):
    def speak(self):
        print("Bark!")

pet = Dog()
pet.speak()

🧾 Output:
Bark!

Dog inherits from Animal, but also overrides its speak() method.

You can also read for:- Python Modules and Packages

4. 🌀 Polymorphism

Using a single interface to work with many object types is known as polymorphism.

🌀 Example:

class Cat:
    def sound(self):
        print("Meow")

class Dog:
    def sound(self):
        print("Bark")

def make_sound(animal):
    animal.sound()

make_sound(Cat())
make_sound(Dog())

🧾 Output:

nginxCopyEditMeow  
Bark

The function make_sound() works for both Cat and Dog due to polymorphism.

🛠 Advanced OOP Features in Python

🔁 Multiple Inheritance

class Father:
    def skills(self):
        print("Guitar")

class Mother:
    def skills(self):
        print("Painting")

class Child(Father, Mother):
    pass

c = Child()
c.skills()  # Output: Guitar (due to method resolution order)

🧬 Super Function

The super() function is used to call methods of the parent class.

class Parent:
    def greet(self):
        print("Hello from Parent")

class Child(Parent):
    def greet(self):
        super().greet()
        print("Hello from Child")

c = Child()
c.greet()

🧾 Output:

Hello from Parent Hello from Child

Classes vs Instances

You can design user-defined data structures with classes. Classes specify functions known as methods that specify the actions and behaviors that an object derived from the class is capable of carrying out with its data.

The Dog class that you’ll design in this tutorial will hold some data on the traits and actions that a certain dog may exhibit.

A class serves as a guide for defining a concept. In reality, it is devoid of any info. The Dog class does not include the name or age of any particular dog, but it does state that a dog must have a name and an age in order to be defined.

An instance is an object that is constructed from a class and contains actual data, whereas the class is the blueprint. A Dog class instance is no longer a blueprint. It’s a real dog with a name, such as four-year-old Miles.

In other words, a class is comparable to a survey or form. An instance is comparable to a form you have filled out with data. You can make numerous instances from a single class, just as numerous persons can complete the same form with their own distinct information.

Conclusion
Gaining proficiency with OOP in Python will enable you to create practical applications, such as GUI apps, games, REST APIs, and machine learning models. To obtain practical experience, concentrate on comprehending the fundamentals and then putting them to use in modest tasks.

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