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Post By Admin Last Updated At 2020-12-31
What is Python OOPs (Object-oriented programming) Concept?

Python is a high-level and interpreted programming language and use in a wide range of applications. Python OOPs or Object-oriented programming tech is a programming approach that concentrates on using objects and classes like any general language. 

Developers can use Python OOPs for developing many apps with code reusability. Hence, in Python programming, it’s very easy and simple to build classes and objects. 

The concept of object-oriented programming is a way of using the idea of objects and classes to represent data and methods. Moreover, this program is categorized into several self-contained objects that help in reducing redundancy. Every single object within this programming approach displays a different portion of the application. Here, it includes self objects and data to contact within themselves. According to the concept, objects are similar to the components of a system.

An object also includes raw data to process. The approach Python OOPs is like a structuring program where several properties and behaviors are lines up into single objects. 

Moreover, objects, in this case, can be defined as real-world entities like books, pens, etc., or any other material. 

Let us learn these Python OOPs concepts using various examples and instances that give much knowledge.

Python OOPs Concepts

There are some important principles of Python OOPs/object-oriented programming systems are as follows:-

Class

Object

Method

Data Abstraction

Encapsulation

Inheritance

Polymorphism

Let us discuss the above OOPs concepts in detail using examples.

Python OOPs concept

Define Classes and Objects

Classes

A class in Python OOPs is a group of data and functions or a collection of various objects that defines the general attributes and behavior. It’s like a blueprint or prototype in Python. Let us look at a simple example to know about the class. 

The class logically divides the data that makes code reusability easier. The objects & classes in Python OOPs can be defined with the example. Here, “student” refers to the class, and the “std_name”, “std_code”, “std_id” refers to the Python objects. 

The following syntax for Class in python is defined as follows:-

class ClassName:     

             

        .     

        .      

        

Furthermore, there are different types of variables that exist within the class that is associated with objects. These are - Instance variable, Static variable, and Local variable. Moreover, the methods within Python OOPs are also the same such as the Instance method, static method, and Local method.

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Objects 

Objects in Python are the instances of the class that includes real data with a state and behavior. This may be any real-world object or item like a system, screen, table, chair, etc. Besides, all the functions within Python include a built-in attribute. 

Moreover, whenever we define a class, we need to build an object to distribute the memory in various parts. The below syntax is an example of the Objects in Python OOPs.

class bus:  

    def __init__(self,model name, yr):  

        self.modelname = model name  

        self.yr= yr

    def display(self):  

        print(self.modelname,self.yr)    

c1 = bus("Tata", 2018)  

c1.display()  

Output - The output for the above syntax will be as follows;-

Tata 2018

The above instance describes that we have built the class named “bus”. This class includes two attributes i.e. “model name” and “yr” (year). Furthermore, we also built a “c1” object to access the class attribute. Here, the c1 object distributes memory for those values.

Method

The method under the Python OOPs concept is a function that is related to any object. Any object can have several methods.

Inheritance

Inheritance is an important aspect of Python OOPs (object-oriented programming). It simulates the real-world concept of inheritance that defines the properties and behaviors of the parent object are transferred to the child class. Furthermore, this happens without any change or modification.

By using inheritance, users can build a class that utilizes all the properties and behavior of other classes. Here, the new class that emerged is a derived/child class. And the other class whose properties are obtained is known as a base/parent class.

Furthermore, there are different types of “Inheritance” within Python OOPs.

These are - Single-level Inheritance, Multi-level inheritance, Hierarchical, and Multiple inheritances. 

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SIngle-inheritance 

A single inheritance within the OOPs concept allows the derived/child class to transfer features from a single base class.

The following example will define the instance for a single inheritance;-

class Operations:

       c = 20

       d = 30

       def add(self):

              sum = self.c + self.d

class MyClass(Operations):

       k = 100

      m = 20

      def sub(self):

            sub = self.k – self.m

ob = MyClass()

ob.add()

ob.sub() 

Output:

Add/Sum of “c and d” is: 50

Minus/Subtraction of “k and m” is: 80

Code explanation

In the above example, we have taken the Class operations into considerations. Moreover, in this, we are inheriting the properties of the ‘Operations’ class into ‘MyClass’ objects.

Moreover, we can access all these methods or statements that exist within the ‘Operations’ class by using “MyClass” objects.

Multilevel Inheritance

A multilevel inheritance within the Python OOPs concept refers to one or more classes perform as a parent class. 

The concept refers to the second class will take over the properties of the first class. And the third class will inherit or take over the properties of a second class. Hence, in this case, the second class will perform as both the Base and the Child class.

The example for the multilevel inheritance is as follows:-

class Addition:

       t = 20

       s = 40

       def add(self):

              sum = self.t + self.s

class Subtraction(Addition):

       def sub(self):

              sub = self.s-self.t         

class Multiplication(Subtraction):

      def mul(self):

             multi = self.t * self.s           

ob = Multiplication ()

ob.add()

ob.sub()

ob.mul()

Output: The output for the above syntax is as follows-

Addition (Sum)of “t and s” is: 60

Subtraction of “t and s” is: 20

Multiplying “t and s” is: 800

Code explanation

The above example defines that the class ‘Subtraction’ takes over the ‘Addition’ class properties. And class ‘Multiplication’ will take over the properties of the ‘Subtraction’ class. Hence, the class ‘Subtraction’ will perform both as the parent and derived class for it.

Hierarchical inheritance

This level of inheritance allows more than a single derived/child class to take over the properties from a parent class.

Multiple Inheritance

The Multiple inheritance levels allow a single derived class to inherit/take over properties from more than one parent class. Thus, this class named multiple level inheritance for this cause. 

Other than the above, there are two more methods in this series such as Method overriding and method overloading. The method overloading refers to various methods having the same name but with different parameters. Similarly, method overriding refers to when a subclass has the same name as the superclass includes. 

We can define these methods using the following example syntax;-

Overloading method

def product(c, d):

       p = c*d

 Print- print(p)

def product(c, d, e):

       p = c*d*e

  Print- print(p)

Overriding method

class Car:

       def sayHiuser():

              print(“I am in Car ”)

class Bus(Car):

       def sayHiuser():

              print(“I am in bus”)

ob = Bus()

ob.sayHiUser()

In between, there is another concept here that exists.

Constructor in Python

A concept of “Constructor in Python OOPs” is a special method that is useful to start the members of a class while run-time when an object is built.

In this language, we have some extra-ordinary built-in class methods that begin with a double underscore (_ _). Also, they include a special meaning within the Python language.

Polymorphism

The term Polymorphism includes two words "poly" and "morphs". Here, the word “Poly” refers to many, and “morph” means shape. By this term, we can understand that one task/job can be performed in many different ways. For instance - you have a class of parrots, and all parrots speak. But all of them speak differently in various voices. Here, the behavior "speak" is polymorphic and it depends on the parrot. So, the abstract "parrot" concept does not "speak" in real, but particular parrots (like any other bread of parrot) have a strong application of the action - ”speak”.

There are two different types of Polymorphism- Compile-time polymorphism, and runtime polymorphism. 

Compile-time polymorphism

A compile-time polymorphism is also known as static polymorphism within Python OOPs. This polymorphism gets solved while the compilation time of the program. Moreover, one common instance of this type of polymorphism is “method overloading”. Already we discussed it in the above sentences.

Run-time Polymorphism

A run-time Polymorphism is also, known as dynamic polymorphism within the Python OOPs concept. Here, it is solved within the run time. We can define this type of polymorphism as “method overriding”. The same concept has been discussed above for your reference.

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Encapsulation

The term “Encapsulation” within Python OOPs is also an important aspect. And the same is used to control the access to other methods and variables within this system. Within the encapsulation concept, code and data are combined in a single unit from being changed accidentally. Besides, in this context, Python programming doesn’t have a private key like Java language.

The example syntax for this Python OOPs concept is as follows;-

class student(object):

def __init__(self):   

self.name = Abcd

self._class = Abcd

self.__section = Abcd

object1 = student()

print(object1.name)

print(object1._class)

print(object1.__section)

The output will be

Abcd

Abstraction

The terms data abstraction (hiding) and encapsulation are often used as synonyms in the concepts of Python OOPs. Moreover, the abstraction method is useful for hiding internal details and show only functionalities by making data private. Abstracting something refers to provide names to things so that it captures the main theme of what a function or an entire program performs.

End Notes

Thus, I am concluding the topic of Python OOPs concepts here. I hope you have got a basic idea of these concepts in detail. Python OOPs is a great concept within this programming language. Moreover, it is very simple to learn a language among other coding languages. To learn more concepts including Python OOPs, go through the Python Online Training and get real-time experience. Hence, learn to grow with the latest editions and concepts in this regard.