Python Tutorial



Python Tutorial

OOPs Concepts in Python


Object-oriented programming is used in Python for representing and working with data in the form of various classes and objects. The fundamental idea of OOPs in Python is to unite various functions and data and use them in such a manner that no other portion of the program can gain access to this particular data. OOPs concepts in Python include polymorphism, inheritance, data encapsulation, data abstraction, and so on.

In this tutorial, we dive deep into the study of OOPs concepts in Python. This comprehensive guide serves as a necessary arsenal for Python fans looking to advance their skill set, covering everything from comprehending their fundamental nature to the use of object-oriented programming in Python. This tutorial will help you to grasp the utility of OOP in Python. 


OOPs concepts in Python act as the fundamental building blocks for developing reusable codes in various programming languages. Integral to fostering efficient and clean coding, they provide a mechanism to reduce data redundancy to create and store error-free codes. The data are encapsulated within smaller objects to ensure code is not just readable but also reusable. In this comprehensive tutorial, we’ll cover OOPs concepts in Python along with its advantages, disadvantages, and a lot more.

What is Object-oriented Programming?

Object-oriented programming is a popular approach to working with programming languages that exhibit data in the form of objects. This is a very common approach and is used in various programming languages including Python. OOP in Python helps to develop error-free codes that you can use multiple times which makes it reusable in nature. In this way, object-oriented programming helps to avoid redundancy of work.

Object-oriented programming is mainly classified into multiple mini-programs or self-contained objects. You can view each of the objects separately that contain distinct features and data and are used for better communication among various programmers. OOP follows a button-up approach and provides the feature of inheritance. 

Why Use OOPs?

You may use object-oriented programming in Python as it is an efficient technique for working with various different types of codes. It is an effective way of programming that makes the codes easy to understand. Also, it offers reusability of course as they are contained in shareable classes or objects. Its attributes like data abstraction and polymorphism keep the data safe and also protect data from unauthorized users. Polymorphism allows you to share the same interface for various objects so that you can write efficient programs that will be preserved.

Applications of OOP Concepts

There is a diverse range of applications of object-oriented programming which are enumerated as follows:

i) Client-server system

OOP is applied in client-server systems so that clients can communicate with each other through a common interface. It has a centralized server for communication and to request access to various resources. the client-server processes the request and generates a response accordingly. OOP enhances code reusability, maintainability, and modularity for building software components through client-server systems.

ii) Hypertext and hypermedia

Hypertext is a form of text that connects people from one text to another. It has the feature of cross-referencing that works in a multi-sequential and non-linear way. Hypermedia is a broader category when compared to hypertext. Hypertext and hypermedia frameworks can be developed with the help of object-oriented programming.

iii) Object-oriented database

In order to retain the integrity and identity of an object, op databases are used to build a close correlation between the physical counterparts of objects and the various databases.

iv) Neural networks and parallel programming

Neural networks can be defined as a collection of multiple algorithms that work to identify the true sense of data using various procedures that work like a human brain. OOP is applied in parallel programming where a big issue is divided into smaller subproblems that can be looked up to and dealt with separately without messing with the other counterparts. In this way, object-oriented programming helps to streamline the problem-solving procedure and enhances the procedure of prediction and approximation.

v) Stimulation and modeling systems

Modeling complex systems is a difficult task as the specification of the variables is different and not universal. The complex system stimulation requires precise modeling and a grave understanding of the interactions. OOP has to simplify complex structures with useful approaches.

vi) AI expert systems

The AI expert systems provide solutions for complex programming issues and address a range of technical problems that become very difficult for the human brain to process. The features of OOP assist in creating AI expert systems that offer high performance, increased responsiveness, dependability, and understandability.

vii) Computer-aided designs

Computer-aided design (CAD) software uses object-oriented programming to build classes of diverse design components such as solids, curves, lines, points, surfaces, etc. These designs also incorporate various methods and attributes to develop relationships between various design elements.

viii) Office automation systems

OOP is used by office automation systems to build high-performing and reusable programming components. It develops various documentation tasks with the help of efficient management and work collaboration. The automation duties are enhanced with the help of object-oriented programming.

Advantages of Using OOPs

Object-oriented programming is all about the concepts of objects and how data is classified and represented with the help of objects. 

Take a glimpse of the various advantages of using object Oriented programming in Python:

  • OOP is very beneficial for troubleshooting problems in a sorted and easy manner. This is because the code in OOP is reusable and stored in a particular location that is exactly known by the user. The user can easily identify the section of the problematic code and take rectification measures.

  • One of the most important advantages that OOP offers is the concept of inheritance. Inheritance allows you to reuse the code as in when required and you do not have to write the same code repeatedly. It reduces the redundancy of work and upholds the feature of code reusability.

  • Increased productivity of course is another important benefit of object-oriented programming. As it contains a huge amount of libraries for the new programs to be accessible at a large scale, it promotes faster development of programs.

  • OOP eliminates data redundancy which means it reduces the reiteration of mundane pieces of work. As the data is safely stored in objects you do not need to code the same programs time and again. You can easily go to the location of the particular program and use it from there.

  • One of the greatest advantages of object-oriented programming in Python is that it offers flexibility of course with the help of polymorphism. This future is based on the pillars of simplicity and extensibility. The codes can be used differently in distinct scenarios.

  • OOP is very beneficial in solving huge problems as it breaks down an entire problem into smaller compartments. This is considered a good programming practice as it becomes easier to identify where the problem lies. These smaller pieces can also be used to deal with other problems and to derive meaningful conclusions.

  • Object-oriented programming provides a higher level of security as it uses access modifiers.  Which means you can decide whom you want to grant access to. The data in OOP can be public, private, or protected as per the security requirements of the same.

Limitations of Using OOPs

Object-oriented programming in Python is a very popular concept but it also comes with certain limitations that are enumerated as follows:

  • The programs developed using object-oriented programming are usually way more lengthy than that of the programs created through procedural programming. As the codes are huge, it takes more time to execute the codes and generates results at a slower pace.

  • OOP is a tricky area and programmers need to have an excellent skill set to perform object-oriented programming at its best. You need to come up with a concrete plan of how to proceed with the codes in OOP which is not so essential in procedural programming.

  • We cannot use object-oriented programming everywhere as it is not a universal concept. it is only applicable to certain programming languages such as Python, C++, Java, etc. You cannot solve all the technical errors using OOP as it can only be used when necessary.

  • OOP is a complex concept as compared to procedural programming. you may need a little more time to get used to OOP concepts. It may also not seem very organic to a lot of people.

  • OOP concepts treat everything as an object. Before we start working with object-oriented programming, we need to develop a brilliant understanding of objects. Sometimes, it may not be possible to place data in terms of objects all the time.


In summary, OOPs concepts in Python are a programming paradigm that deals with the concepts of objects. We have seen that object-oriented programming possesses the ability to reusability of codes, making data more secure and efficient to use at a later time. It incorporates numerous real-life aspects such as inheritance and abstraction. In the end, having a solid understanding of OOP functions allows for more efficient, modular programming, which ensures Python's appeal and usefulness across a range of applications. 

We at upGrad offer upskilling courses that can assist you at the beginning of your career as a Python developer.

Frequently Asked Questions

1. What are the four fundamental pillars of Python?

OOP concepts in Python are based on 4 major pillars that are inheritance, polymorphism, abstraction, and encapsulation. Without these, programmers cannot work on Python.

2. What is class and object in Python?

OOP works on the basis of classes and objects in Python. An object is known as a collection of data. There can be many classes as data can be divided and put in multiple objects. A class is a blueprint of those objects. The user develops a class in a certain way that specifies what kind of objects it will contain.

3. How do OOP concepts in Java work?

The function of OOP concepts in Java is similar to that of their function in Python. However, the code that is written in Java is different from that of Python but the concepts remain the same. OOP concepts in Java include inheritance polymorphism abstraction and encapsulation.

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