Objected-oriented programming as a discipline has gained a universal following among developers. Python, an in-demand programming language also follows an object-oriented programming paradigm. It deals with declaring Python classes and objects, laying the foundation for OOPs concepts. In other words, it is an approach for developing applications that emphasize on objects. Let us explore more about Object-Oriented programming and its role and concept in Python.

Table of contents 

• Introduction to Python
• What is Object-Oriented Programming in Python?
• Overview of OOPs concepts
• Concepts in OOPs
• What are Classes?
• How to define a Class?
• What are Metaclasses?
• What are Objects?
• How to define an Object?
• Object-Oriented Programming methodologies
• What are the differences between Abstraction and Encapsulation?
• What is Method Overloading?
• What is Method Overriding?
• What are the advantages of OOPs in Python?
• Why OOPs in Python is better than Procedural programming?
• Conclusion
• FAQs

Introduction to Python

Python is a multi-paradigm programming language supporting OOP and other paradigms. You use classes to achieve OOP in Python. Python provides all the standard features of object-oriented programming. Developers often use OOP in their Python programs because it makes code more reusable and easier to work with larger programs. OOP programs prevent you from repeating code because a class can be defined once and reused many times. OOP, therefore, makes it easy to achieve the “Don’t Repeat Yourself” (DRY) principle.

What is Object-Oriented Programming in Python? 

Object-Oriented Programming (OOP) is a widely popular programming paradigm. This method of structuring a program uses objects that have properties and behaviours. Each programming language handles the principles of OOP differently, so it is important to learn OOP for each language you are learning. 

Object Oriented Programming uses objects to represent data and methods. It is also, an approach used for creating neat and reusable code instead of a redundant one. The program is divided into self-contained objects or several mini-programs. Every Individual object represents a different part of the application with its own logic and data to communicate. 

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Overview of OOP Concepts –

• Class − A user-defined prototype for an object that defines a set of attributes that characterize any class object. The attributes are data members (class and instance variables) and methods accessed via dot notation.
• Class variable – A variable that is shared by all class instances. Class variables are defined within a class but outside any of the Class’s methods. Class variables are not used as frequently as instance variables are.
• Data member – A class variable or instance variable that holds data associated with a class and its objects.
• Function overloading – Assigning more than one behaviour to a particular function. The operation performed varies by the types of objects or arguments involved.
• Instance variable – A variable defined inside a method and belongs only to the current instance of a class.
• Inheritance – The transfer of the characteristics of a class to other classes that are derived from it.
• Instance – An individual object of a certain class. An object obj that belongs to a class Circle, for example, is an instance of the class Circle.
• Instantiation – The creation of an instance of a class.
• Method – A special kind of function that is defined in a class definition.
• Object – A unique instance of a data structure defined by its Class. An object comprises data members (class and instance variables) and methods.
• Operator overloading – Assigning more than one function to a particular operator.

Concepts in Python OOPs

Major OOP (object-oriented programming) concepts in Python include Class, Object, Method, Inheritance, Polymorphism, Data Abstraction, and Encapsulation.

What are Classes?

A class is a collection of objects, or you can say it is a blueprint of objects defining common attributes and behaviour.

How to define a Class in Python?

Before creating a Class, we should know a few essential instructions to build an effective class.

• To create a class, use the “class” keyword followed by the class name.
• The end of the Class name must declare a colon.
• To declare a documentation string, getting more information about the Class is useful.
• Using a constructor in a class, we will be smoothly handling a large program. 

Syntax – Class classname:

<Statement 1 >

<Statement N >

What are Metaclasses in Python?

A Metaclass is the Class of a class. A class defines how an instance of the Class (i.e., an object) behaves, while a metaclass defines how a class behaves. A class is an instance of a metaclass. A Metaclass is most used as a class factory. When you create an object by calling the Class, Python creates a new class (when it executes the ‘class’ statement) by calling the Metaclass. However, Metaclasses define the class type, not just a factory for it so you can do much more with them.

Well, it logically groups the data in such a way that code reusability becomes easy. I can give you a real-life example- think of an office going’ employee’ as a class and all the attributes related to it like’ emp_name’,’ emp_age’,’ emp_salary’, and’ emp_id’ as the objects in Python.

What are Objects?

In a programming language, objects considered as a value or variable of the Class simulate a real-world entity to enhance their accessibility and understandability. It allows us to create an instance of the Class using the class name, and it can access all the specified class methods, like the “__init__” method. 

In Python, everything consists of an Object to deal with itself, and almost everything has attributes and methods. All functions have a built-in attribute __doc__, which returns the docstring defined in the function source code.

How to create an Object in Python?

To create an object, we first must set our initializer method. The initializer method is unique because it has a predefined name, __init__, and does not have a return value. The program automatically calls the initializer method when a new object from that Class is created. We can use the Class named calculation to create an object to achieve that.

An initializer method should accept the special self-parameter and all class properties as parameters. The self-parameter allows the initializer to select the newly created object instance.

We then populate the initializer method with one instance variable initialization for each property. Each initialization sets a property of the created object to the value of the corresponding parameter.

For example, the first self. Size = size sets the size property of the created object to equal the size parameter passed at object creation.

Once the initializer is set up, we can create an object with [objectName] = Shoe() and pass the necessary parameters. On line 10, we create a Shoe object called sneaker3 with properties of size = 11, is on sale = false, material = “leather”, and price = 81

Syntax – <object-name> = <class-name>(<arguments>)

Object-Oriented Programming methodologies 

Object-Oriented Programming methodologies deal with the following concepts.

• Inheritance
• Polymorphism
• Encapsulation
• Abstraction

• Inheritance – In the programming aspect, inheritance generally means “inheriting or transfer of characteristics from parent to child class without any modification”. The new Class called the derived/child class, and the one from which it derived called a parent/base class.

• Single Inheritance – Single-level inheritance enables a derived class to inherit characteristics from a single-parent class.
• Multilevel Inheritance – Multilevel inheritance enables a derived class to inherit properties from an immediate parent class which in turn inherits properties from his parent class.
• Hierarchical Inheritance – Hierarchical-level inheritance enables more than one derived Class to inherit properties from a parent class.
• Multiple Inheritance – Multiple-level inheritance enables one derived Class to inherit properties from more than one base class.

• Polymorphism- You all must have used GPS to navigate the route. Isn’t it amazing how many different routes you come across for the same destination depending on the traffic? From a programming point of view, this called polymorphism. It an OOP methodology where one task can performed in several ways. 

• Run-time Polymorphism – A run-time Polymorphism also called dynamic polymorphism, where it gets resolved into the run time. One common example of Run-time polymorphism is method overriding. Let me show you an example for a better understanding.

• Compile-time Polymorphism – A compile-time polymorphism, also called static polymorphism, gets resolved during the compilation time of the program. One common example is method overloading. 

• Encapsulation – In a raw form, encapsulation means binding up data in a single class. Python does not have any private keywords, unlike Java. A class should not directly accessed but prefixed in an underscore.

• Abstraction – Suppose you booked a movie ticket from Bookmyshow using net banking or any other process. You don’t know the procedure of how the pin generated or how the verification done. This called ‘abstraction’ from the programming aspect; you only show the implementation details of a particular process and hide the details from the user. It used to simplify complex problems by modelling classes appropriate to the problem.

What is the difference between Abstraction and Encapsulation?

Method Overloading

The concept of method overloading found in almost every well-known programming language that follows object-oriented programming concepts. It simply refers to using many methods with the same name that take various numbers of arguments within a single class.

Method Overriding

When a method with the same name and arguments is used in a derived class and a base or super Class, we say that the derived class method “overrides” the method provided in the base class. When the overridden method gets called, the derived Class’s method is always invoked. The method that was used in the base class is now hidden.

What are the advantages of OOPs in Python?

The advantages of Object-Oriented Programming in Python are as follows – 

• OOPs helps us to write clean code which resembles a real-world problem’s solution. Thus, it helps us to solve real world problems in much easier way.
• OOPs boosts easy maintenance, reusability and updating existing code base.
• OOPs give our code a better modular approach. Thus, partial updates are easy to do. In other hand, modularity helps us to add or improvise existing functionalities and check their dependencies in much easier way.
• Frameworks built around the OOP structure which helps us to render any component into our codebase without writing the entire structure of the framework. We can just create objects and use their methods to accomplish our task.

Why OOPs in Python is better than Procedural programming?

• Development and maintenance are easier in OOPs whereas in procedural programming, it is not easy to maintain the codes when the project becomes lengthy.
• Real-world problems can easily solved through OOPs. On the other hand, procedural programming does not simulate the real world. 
• OOPs supports data hiding. Therefore, it is more secure than procedural languages. You cannot access private data from anywhere. Procedural language, on the other hand, does not provide any proper way for data binding, so it is less secure.

 Conclusion 

Object-Oriented Programming makes the program easy to understand as well as efficient. OOP is often the best use when we are dealing with manufacturing and designing applications. It provides modularity in programming. It allows us to break down the software into chunks of small problems that we then can solve one object at a time. It majorly used in cases where the reusability of code and maintenance is a major concern. It makes development easy and we can easily append code without affecting other code blocks. Overall, it solves the problem of complex programming.

FAQs

1. Define OOPs.

OOPS stands for Object-Oriented Programming System, which is a programming paradigm based on the concept of objects. It is a way of organizing and designing computer programs using objects, which are instances of classes. The primary goal of OOPS is to make programming more modular, reusable, and maintainable.

2. Is Python 100 per cent Object-oriented?

Python does not have access specifiers like “private”, as in Java. It supports most terms associated with objected-oriented programming language. Hence, it not fully object-oriented.

3. What is the difference between Static Method and Class Method?

Static method function is nothing more than a function defined inside a class. It is callable without instantiating the Class first. Its definition is immutable via inheritance. Classmethod function is also callable without instantiating the Class, but its definition follows the Subclass, not the Parent class, via inheritance.

4. What are the examples of OOPs and Procedural programming?

Example of object-oriented programming languages include C++, Java, .Net, Python, C#, etc. Examples of procedural languages are C, Fortran, Pascal, VB etc.

5. What is Method overriding in Python?

It a feature of object-oriented programming in which a subclass provides its own implementation of a method that already defined in its parent class. 

6. What is Method overloading in Python?

Method overloading is a feature of some programming languages in which a method can have multiple definitions with different parameters. 

7. Give one difference between Abstraction and Encapsulation?

A primary difference between Abstraction and Encapsulation in the way they achieved. Abstraction achieved using abstract classes and interfaces. Encapsulation achieved by access modifiers.

8. Can we create multiple Objects in one Class?

Yes. You can create multiple Objects of one Class.

9. How many types of Polymorphism are there?

There are two types of Polymorphism – run time and compile time.

10.  What are some applications of OOPs?

Some key applications of OOPs include computer graphics applications, object-oriented database, user-interface design such as windows, real-time systems, client-server system, and artificial intelligence systems.

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