Is Python Object-Oriented?

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Yes, Python is an object-oriented programming language, though not purely. Discover what makes it an OOP language and what not.

[Featured Image] A programmer works at her computer in an office with Python, and object oriented programming language.

Programmers often need clarification on whether Python is an object-oriented programming (OOP) language. The answer is quite simple: Yes! Python is an OOP language, but it is not purely OOP. 

To be precise, Python is a multi-paradigm language. Like Lisp and C++, it supports several different approaches. You can write predominantly object-oriented, procedural, or functional programs using such languages.

Nearly everything in Python is an object, and a class in Python serves as an object constructor or, in other words, a blueprint for object creation. As a result, creating and using objects and classes in Python is relatively easy. 

Before we explore Python's object-oriented aspects, it is important to clearly understand what an object-oriented language is and what computer languages are object-oriented.

What is object-oriented programming?

OOP is a computer programming model based on objects rather than logic and functions. The "object" in object-oriented is a field of data with specific attributes and behaviour, while "oriented" oriented implies an interest in a particular kind of entity. Thus, an OOP model concentrates on the objects that software developers are likely to change instead of the logic needed. 

The OOP approach suits complex, large, and actively updated programs for mobile applications, manufacturing and design, system simulation software, and more.

Some of the popular OOP languages are:

  • Java

  • Python

  • Ruby

  • Scala

  • C++

Why is Python object-oriented?

The following sections will help you understand why Python is object-oriented. The building blocks of Python as an object-oriented programming language include the following:


These are instances of a class containing specifically defined data. They are like abstract entities or real-world objects. Using objects, you can access the method and function of a class.

An object in Python has attributes and behaviours. For example, a nightingale is an object. It has the following:

  • Attributes: Name, colour, age, and more

  • Behaviour: Flying, singing, and more


These are user-defined data types. Classes serve as the objects’ blueprints. They comprise variables, functions, and methods. 

The keyword class helps create classes in Python. A class contains attributes or variables. These attributes are always public. You can retrieve them using the dot (.) operator. 

Like any other object-oriented programming language, Python is based on the following principles:

Classes with inheritance 

Python classes support inheritance. A class can inherit properties from some other class, giving rise to the following two types of classes:

  • Child/derived class: The one that derives/inherits properties from some other class 

  • Parent/base class: The class from which the properties are taken/derived 

The benefits of Python inheritance are as follows:

  • It enables the reusability of a code.

  • It enables you to add features to an existing class without modification.

  • Inheritance is transitive, i.e., when class B inherits from class A, all the subclasses of B will inherit from class A automatically.

Python exhibits different types of inheritance: 

  • Single inheritance: A child class inherits characteristics from a single-parent class.

  • Multilevel inheritance: A child class inherits an immediate parent class’ properties, which has inherited properties from its parent class.

  • Hierarchical inheritance: More than one child class inherits properties from a base/parent class.

  • Multiple Inheritance: A child/derived class inherits properties from multiple parent classes. 


Python supports the combination of behaviour and data in a class. However, it does not enforce data hiding. In other words, attributes/methods do not have a private/protected status. 

Encapsulation is yet another fundamental concept in OOP. It implies wrapping data and methods in a single unit. 

Encapsulation restricts direct access to variables and methods and prevents accidental data modification. To avoid unintentional change, an object's variable can only be altered by its process, and such variables are called private variables.

In Python, private attributes are denoted using an underscore prefix, such as single _ or double __. 


As an object-oriented programming language, Python supports polymorphism, which means multiple forms. In other words, the same entity (method/operator/object) can perform different functions in different scenarios.

Python supports polymorphism via multiple inheritance. It can emulate the "interface" concept using abstract classes and abstract methods on those classes.

Data abstraction

Python classes exhibit high-level data and features via methods, attributes, and properties. 

Data abstraction hides unnecessary code details from the user when you don’t want to share sensitive code parts.

In Python, you can achieve data abstraction by creating abstract classes. Internal functionality and data stay hidden through strong community conventions and tools. Thus, data abstraction in Python makes the data less complex and more secure for the user. 

What are the key benefits of Python as an OOP?

Some of the key perks of OOP are as follows: 

  • Greater Flexibility: Polymorphism provides much-needed flexibility as a particular function can adapt to the class it is put in. 

  • Interface descriptions: The message-passing techniques used for object communication simplify the descriptions of external systems.

  • Code Reusability: You can reuse the code as the class is sharable and favours inheritance. Thus, your team need not write the exact code over and over.

  • Boosted Productivity: The reusable code and multiple libraries allow programmers to construct new programs more quickly.  

  • Better Scalability: As a programmer, you can implement system functionalities independently.

  • Modularity: Encapsulation makes objects self-contained, making troubleshooting and collaborative development easier.

  • Optimal Security: Both encapsulation and abstraction make software maintenance easier, and the internet protocols stay protected.

Final word: Is Python object-oriented?

Given the above points, we can strongly state that Python possesses the properties of an OOP language. However, we cannot strictly classify Python as an OOP language as it doesn’t support strong encapsulation. Although it takes firmly from the object-oriented programming language, it is also procedural, functional, reflective, and imperative. 

Thus, it is a multi-paradigm, high-level programming language that supports OOP and aspect-oriented programming features. 

Next steps

Being an object-oriented programming language, Python makes computer programs efficient and easy to understand. The shareable class makes the code reusable. Moreover, all data is secure with Python data abstraction, and polymorphism adds flexibility. 

Get well-versed in Python basics with Programming for Everybody (Getting Started with Python). All you need is moderate computer experience, and you will be able to grasp the crucial concepts in this course. Moreover, upon course completion, you will have a shareable certificate and be ready to take more advanced Python programming courses.

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