Is Python Object-Oriented? Exploring Object-Oriented Programming in Python

Python is a fully object-oriented language. It allows you to create classes and objects, apply inheritance, and implement encapsulation, polymorphism, and abstraction. Everything in Python is treated as an object, making it flexible and powerful for building scalable applications. Its OOP features let developers model real-world problems efficiently while maintaining clean, reusable code. 

In this guide, you'll read more about Python’s OOP principles, including classes, objects, inheritance, encapsulation, polymorphism, and abstraction. You’ll explore advanced concepts like magic methods, operator overloading, and composition. Practical examples and mini-project ideas will show how to implement OOP in real-world scenarios to strengthen your understanding of Python’s object-oriented programming capabilities. 

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Is Python an Object-Oriented Language? 

The answer to is Python object oriented language is a clear yes. Its design and features are deeply rooted in OOP principles, making it a natural choice for building object-oriented systems. 

Python’s OOP Capabilities 

Python provides all the necessary tools to implement object-oriented programming effectively. 

• Support for Classes and Objects: The class keyword is the foundation of OOP in Python, allowing you to create blueprints for objects. 
• Full Implementation of OOP Principles: Python supports inheritance (including multiple inheritance), polymorphism, and encapsulation out of the box. 
• Dynamic Typing and Flexibility: Python's dynamic nature allows for powerful OOP patterns like duck typing, which adds a layer of flexibility not always present in statically-typed languages. 
• "Everything is an Object": In Python, integers, strings, lists, and even functions are objects with their own attributes and methods. 

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Why Python is Object-Oriented Language 

Python's design choices clearly favor an object-oriented approach over a purely procedural one. This is a key reason why Python is an object-oriented language. 

• Unlike traditional procedural languages that focus on a sequence of tasks, Python encourages you to think in terms of objects and their interactions. 
• While some languages are purely OOP (meaning everything must be in a class), Python is a hybrid. It allows you to write simple procedural scripts without defining any classes. 
• This flexibility makes Python easy for beginners to pick up while providing the full power of OOP for building complex, large-scale applications. 

Also Read: Top 7 Python Data Types: Examples, Differences, and Best Practices (2025) 

Difference Between Object-Oriented and Procedural Python 

Let's compare the two approaches with a simple task: describing two different dogs. 

Key OOP Features in Python 

Let's dive into the specific features that make OOP in Python possible. We'll look at the syntax and provide simple code examples for each core concept. 

Classes and Objects 

A class is the blueprint. An object is the actual thing built from that blueprint. 

• You define a class using the class keyword. 
• The __init__() method is the constructor, which initializes an object's attributes when it is created. 
• self refers to the instance of the object itself. 
• You create an object (or instance) by calling the class name as if it were a function. 

Python 
# A simple class blueprint for a Car 
class Car: 
    def __init__(self, brand, model): 
        self.brand = brand 
        self.model = model 
 
    def display_info(self): 
        return f"This is a {self.brand} {self.model}." 
 
# Creating objects (instances) of the Car class 
my_car = Car("Toyota", "Camry") 
another_car = Car("Ford", "Mustang") 
 
# Accessing attributes and methods 
print(my_car.brand)             # Output: Toyota 
print(another_car.display_info()) # Output: This is a Ford Mustang. 
 

Inheritance in Python 

Inheritance allows us to define a class that inherits all the methods and properties from another class. 

• The parent class is the class being inherited from, also called the base class. 
• The child class is the class that inherits from another class, also called the derived class. 
• Python supports both single inheritance (inheriting from one parent) and multiple inheritance (inheriting from multiple parents). 

Python 
# Parent class 
class Vehicle: 
    def __init__(self, brand): 
        self.brand = brand 
 
    def drive(self): 
        print("The vehicle is moving.") 
 
# Child class inheriting from Vehicle 
class ElectricCar(Vehicle): 
    def __init__(self, brand, battery_size): 
        # Call the parent's constructor 
        super().__init__(brand) 
        self.battery_size = battery_size 
 
    def charge(self): 
        print("The electric car is charging.") 
 
my_ev = ElectricCar("Tesla", "100 kWh") 
my_ev.drive()  # Inherited from Vehicle 
my_ev.charge() # Specific to ElectricCar 
print(my_ev.brand) # Attribute from Vehicle 
 

Also Read: 5 Types of Inheritance in Python You Must Understand to Level Up! 

Encapsulation and Data Hiding 

Encapsulation restricts access to methods and variables to prevent accidental modification. 

• Public attributes can be accessed from anywhere. 
• Protected attributes are prefixed with a single underscore (_). This is a convention to indicate they should not be accessed from outside the class. 
• Private attributes are prefixed with a double underscore (__). Python name-mangles these attributes to make them harder to access from outside. 

Python 
class Account: 
    def __init__(self, initial_balance): 
        self.__balance = initial_balance  # Private attribute 
 
    def deposit(self, amount): 
        if amount > 0: 
            self.__balance += amount 
            print(f"Deposited ${amount}. New balance: ${self.__balance}") 
 
    def get_balance(self): 
        # A "getter" method to safely access the private balance 
        return self.__balance 
 
my_account = Account(1000) 
# print(my_account.__balance)  # This will cause an AttributeError 
print(f"Current balance is ${my_account.get_balance()}") 
my_account.deposit(500) 
 

Also Read: Understanding Encapsulation in OOPS with Examples 

Polymorphism in Python 

Polymorphism allows us to use a unified interface for objects of different classes. 

• Method Overriding: A child class can provide its own implementation of a method that is already defined in its parent class. 
• Duck Typing: This is a core concept in Python. If an object walks like a duck and quacks like a duck, then it must be a duck. In other words, Python cares more about an object's behavior (the methods it has) than its explicit type. 

Python 
class Dog: 
    def speak(self): 
        return "Woof!" 
 
class Cat: 
    def speak(self): 
        return "Meow!" 
 
def make_animal_speak(animal): 
    # This function doesn't care if the animal is a Dog or a Cat. 
    # It only cares that the object has a .speak() method. 
    print(animal.speak()) 
 
# Create different objects 
dog = Dog() 
cat = Cat() 
 
# Pass them to the same function 
make_animal_speak(dog)  # Output: Woof! 
make_animal_speak(cat)  # Output: Meow! 
 

Abstraction in Python 

Abstraction hides the implementation details and shows only the functionality to the user. 

• An abstract class cannot be instantiated on its own. Its purpose is to be inherited by other classes. 
• An abstract method is a method declared in an abstract class but has no implementation. The child class is forced to provide its own implementation. 
• Python's abc module is used to implement abstraction. 

Python 
from abc import ABC, abstractmethod 
 
class Shape(ABC):  # Inheriting from ABC makes it an abstract class 
    @abstractmethod 
    def area(self): 
        pass 
 
class Square(Shape): 
    def __init__(self, side): 
        self.side = side 
 
    def area(self):  # Must implement the abstract method 
        return self.side * self.side 
 
class Circle(Shape): 
    def __init__(self, radius): 
        self.radius = radius 
 
    def area(self): # Must implement the abstract method 
        return 3.14 * self.radius * self.radius 
 
# my_shape = Shape() # This would raise a TypeError 
my_square = Square(5) 
print(f"Square area: {my_square.area()}") # Output: Square area: 25 

Advantages of Using OOP in Python 

Adopting OOP is not just about following a trend; it provides concrete benefits that make your software better. Understanding these advantages helps clarify why Python is an object-oriented language by design. 

• Code Reusability: Inheritance allows you to reuse code, saving time and effort. 
• Easier Maintenance: With encapsulation, objects are self-contained. Changes within one class are less likely to break other parts of the application. 
• Modular Structure: OOP helps break down complex problems into smaller, manageable, and logical objects. 
• Real-World Problem Modeling: It allows you to create software models that closely resemble real-world objects, making the code more intuitive. 
• Improved Security: Encapsulation and abstraction hide sensitive data from the user, adding a layer of security. 

Also Read: Top 10 Advantages of Object-Oriented Programming 

Understanding Object-Oriented Programming (OOP) 

To fully grasp why is Python object oriented, we also need to understand the paradigm itself. OOP is not just a set of features; it's a way of structuring software to model real-world things. 

What is Object-Oriented Programming? 

Object-Oriented Programming is a programming model that organizes software design around data, or "objects," rather than functions and logic. An object can be defined as a data field that has unique attributes and behavior. The main idea is to bundle data and the methods that operate on that data into a single unit. 

Here are the key concepts at a glance: 

Core Principles of OOP 

The entire OOP paradigm stands on four main pillars. These principles help developers create organized, reusable, and maintainable code. 

• Encapsulation: This is like a protective capsule. It binds the data (attributes) and the code that manipulates the data (methods) together and keeps them safe from outside interference and misuse. 
• Inheritance: This principle promotes code reusability. It allows a class (child class) to inherit features from another class (parent class), so you don't have to write the same code again. 
• Polymorphism: This means "many forms." It allows us to perform a single action in different ways. For example, you can have a speak() method for both a Dog and Cat object, and each will respond differently. 
• Abstraction: This involves hiding the underlying complexity of a system and exposing only the necessary parts. When you drive a car, you use the steering wheel and pedals, without needing to know the complex mechanics of the engine. 

Also Read: Top 20 Advantages of Using Python Scripts in 2025: Your Ultimate Guide 

Accelerate Your Python Skills with upGrad

To circle back to our original question: is Python object oriented? The answer is an unequivocal yes. Python was built with object-oriented programming as a core feature, and it provides a rich, flexible, and intuitive toolkit for implementing OOP principles. From classes and inheritance to polymorphism and encapsulation, Python supports everything you need to build robust, scalable, and maintainable applications using an object-oriented approach. While it also supports other paradigms, its object-oriented nature is what makes it a powerhouse in modern software development. While these concepts are powerful for building scalable applications, many developers struggle to apply them effectively, especially when transitioning from procedural programming or handling complex projects.

upGrad’s courses offer hands-on experience with OOP, guiding you through practical examples and advanced techniques so you can apply these concepts confidently and efficiently in your real-life projects.

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