How We Can Use the Object-Oriented Programming with Python?

Phyton is the fourth most used programming language among software developers according to Statista. This is due to its simplified syntax and versatility. Let us begin with a summary of object-oriented programming and we will discuss about the concept of object-oriented programming with python.

An object is a component that allows programmers to use methods and variables from inside the class and it usually has behaviour and a specific purpose. Java, GO, C++, C# and Swift are examples of object-oriented programming. The method of implementation in all these programming languages is different and every language is unique and has its own syntax.

What is object-oriented programming?

Object-Oriented Programming is defined as a programming paradigm based on the creation of reusable objects containing their own behaviour and properties that can be acted upon bundled and manipulated. 

Many software developers use OOP because it makes code logical, and reusable and also makes inheritance easier to implement. OOP follows the DRY principle which makes more efficient programs. Every object is defined with its own properties In OOP. For an instance, say our object is an employee. The properties could be their name, role, and age which makes OOP easy to model real-world things and relationships between them.

OOP is best for beginners because it organises the data like how the human brain organises information. OOP follows four major principles such as inheritance, abstraction, polymorphism and encapsulation.  

now let us see about OOP in Python

OOP in Python

Python is considered a multi-paradigm programming language means it supports paradigms along OOPS. The concept of classes is used in python to achieve OOP in python and the language provides all the standard features of object-oriented programming.

Developers choose the python programming language because it makes code reusable and also makes it easier to work with large programs. OOP programs also prevent you from repetitive code because a class can be defined once and can be reused many times which is also known as the "DRY" principle.

Let us see an example of how OOP improves phyton.

sneaker1 = [8, true, "leather", 60]

The values for the properties size, isOnSale, material, and cost are contained in the list sneaker1. This approach does not make use of OOP and can result in a number of issues:

You must remember which index was used to store a specific type of data, for example, sneaker1[0] = size. This is not as obvious as the sneaker1.size object call.

It is not reusable. Instead of simply initialising a new object, you must create a new list for each item.

Creating object-specific behaviour is difficult. Methods cannot be included in lists. To achieve a given behaviour, each list must call the same global function rather than an object-specific method.

Instead, we could use OOP to write this as a Shoe class object to avoid these issues and make our code more useful in the long run.

sneaker1 = Shoe (8, true, "leather", 60)

To avoid these issues, Python developers frequently prefer OOP over other available paradigms. We'll look at how to incorporate OOP into your Python programmes in the sections that follow.

How To Create an Object in Python

We have to first set our initializer method for creating an object. The initializer method is distinct in that it has a predefined name, __init__, and no return value. When a new object of that class is created, the programme automatically calls the initializer method.

An initializer method should accept the special self parameter, followed by all class properties. The self parameter tells the initializer method which objects instance to select.

The initializer method is then filled with one instance variable initialization for each property. Each of these initializations sets the value of the corresponding parameter to a property of the created object.

Consider the first self. size = size sets the created object's size property to the size parameter passed at object creation.

Once the initializer is in place, we can use [objectName] = Shoe() to create an object and pass the necessary parameters. einsteineruploading up to get together with.

We can use this code to create as many Shoe instances as we need.

class Shoe:

    # defines the initializer method

    def __init__(self, size, isOnSale, material, price):

        self.size = size

        self.isOnSale = isOnSale

        self.material = material

        self.price = price

# creates an object of the Shoe class and sets

# each property to an appropriate value

sneaker3 = Shoe(11, 'false', "leather", 81)