Python Tutorial: Object-Oriented Programming system (OOPs) – Part 1

Harika Bonthu 24 Aug, 2021 • 7 min read
This article was published as a part of the Data Science Blogathon
In this article, we will try to help you understand/brush up on the basic OOP concepts.

Table of Contents:

  1. OOP and its importance
  2. Class, Instance/Object, __init__ method
  3. Creating Classes and Objects
  4. Accessing Attributes and Calling methods
  5. Variable Types
  6. Method Types

OOP and its importance

Object-oriented programming (OOP) is a notion that depends on the concept of objects. In OOP, objects are defined with their own set of attributes/properties.

It is important because it helps the developers in writing clean, modular code that can be reused throughout the development. . With modular coding, we get control of functions and modules.

It comes in handy primarily in the case of large application development.

 

Class, Instance/Object, __init__method

If you are a beginner, pay a good amount of time to understand the terminology explained below.

Class: It is a user-defined blueprint of an object with a predefined set of attributes common to all the objects.

Instance/Object: It is an individual entity that is created from a class.

__init__ method: __init__ method in OOP is nothing but a special function. Special functions are the functions that are used to enrich the class. These can be easily identified as they have double underscores on either side. __init__ method is used to initialize the attributes. It is called a constructor in other programming languages.

Creating Classes and Objects

Creating a class: The class statement creates a new class with a given ClassName.

creating class
Image by Author

The name of the class in Python follows Pascal Case. It is a naming convention where each word starts with a capital letter without any special characters used.

Initializing the attributes/variables: We are initializing the object with n attributes namely attr1, attr2,…., attrn.

inittializing variables | Python Object-Oriented Programming
Image by Author

Creating Methods: Method is nothing but a function with a set of rules based on which objects behave. Created two methods names method1, method2. Choose the method inputs based on the requirement. Here, method1 does not take any inputs other than the object. Whereas, method2 takes self.attr2 and does something to it.

creating methods | Python Object-Oriented Programming
Image by Author

Complete Syntax of creating a class:

class ClassName:




def __init__(self, attr1, attr2):

self.attr1 = attr1

self.attr2 = attr2




def method1(self):

pass




def method2(self, attr2):

pass


Example Class

Let’s create a class that represents the authors at Analytics Vidhya. The main attributes of authors are their names and the number of articles that are published.

Then create two methods – one that prints the author’s details and another that updates the number of articles written by an author and are published.

class BlogathonAuthors:




def __init__(self, author_name, num_articles):

self.author_name = author_name

self.num_articles = num_articles

print("Created new author object")




def show(self):

"""This method prints the details of the author"""

print("In show method")

print(f"Author Name: {self.author_name}nNum of published articles: {self.num_articles}")




def update(self, num_articles):

"""This method updates the number of published articles"""

print("In update method")

self.num_articles = num_articles

Creating Instances/Objects:

The process of creating an instance or object from a class is called Instantiation. While creating an object, we should pass the arguments that are defined in the __init__ method.

Syntax: object = ClassName(arguments)

author1 = BlogathonAuthors("Harika", 10)

The above code creates an object named “author1” whose name is “Harika” and has written 10 articles.

Similarly, we can create any number of objects required.

author2 = BlogathonAuthors("Joey", 23)

 

Accessing attributes and Calling methods

The syntax for accessing the attributes is object.attribute

The author’s name is accessed using author1.author_name, and the number of articles is accessed using author1.num_articles.

accessing attributes | Python Object-Oriented Programming

Rather than just displaying we can also change the values.

author1.num_articles = 9

Calling Methods: The two ways of calling methods are ClassName.method(object) or object.method()

Calling the show method to display the information about author1.

BlogathonAuthors.show(author1)
calling methods | Python Object-Oriented Programming

author1.show()

method calling

Wait, if you are familiar with functions in Python, you may get a doubt that the “show” method accepts one argument but we didn’t pass any.

Think of a minute about what’s happening here and continue reading further to know the answer.

show(self) method accepts one argument that is the object itself. The self keyword here points to the instance/object of the class. So when we call object.method(), it is nothing but we are passing the object as an argument.

Now, calling the update method and changing the number of articles.

author1.update(20)

After the update, if we see the details of author1, the number of articles will be 20.

calling update method | Python Object-Oriented Programming

Variable Types

The three different types of variables in OOP in Python are:

Instance Variables: Variables that are defined inside __init__ are called instance variables and these are of object level.

Class/Static Variables: Variables that are defined outside the __init__ method are called class variables and these are of class level.

Local variables: Variables that are confined to a method are called local variables and these are of method level.

To better understand the variables, create a variable that holds the type of authors’ work. All the blogathon authors are freelancers.

Also, let us create another method “total_articles” that takes the number of articles drafted, and stores the sum of published, drafted articles to a variable called “total

so, here “type” is a class variable, and “total” is a local variable.

class BlogathonAuthors:

 

type ="freelancer"

 

def __init__(self, author_name, num_articles):
self.author_name = author_name
self.num_articles = num_articles
print("Created new author object")

 

def show(self):
"""This method prints the details of the author"""
print("In show method")
print(f"Author Name: {self.author_name}nNum of published articles: {self.num_articles}nType of Work: {BlogathonAuthors.type}")

 

def update(self, num_articles):
"""This method updates the number of published articles"""
print("In update method")
self.num_articles = num_articles

 

def total_articles(self, draft):
total = self.num_articles + draft
print(f"Total articles are: {total}")

 

variable types | Python Object-Oriented Programming
Image by Author

Accessing class variables: can be accessed using ClassName.variable or object.variable

author3 = BlogathonAuthors("Karl", 3)
author3.type
class variable || Python Object-Oriented Programming

Accessing instance variables: object.variable

object variable

Accessing local variables:

Upon calling the total_articles function, it prints the total articles.

local variable | Python Object-Oriented Programming

But it throws an error if we try to access the “total” variable outside the total_articles method.

error

Method Types

The three types of Methods in OOP are:

  1. Instance methods
  2. Class methods
  3. Static methods

Instance methods: These are the methods used to get or set object attributes. These methods are also known as accessor methods (gets the details), mutator methods (sets the details). In our example, the “show” method is the getter/accessor method and the “update” method is the setter/mutator method.

Class methods: To work with class/static variables we need to use the class methods.

Syntax: 

@classmethod 
def methodName(cls):
    # update staticvariable
    # return staticvariable

@classmethod is a decorator that is used to declare a class as a class method.

Static Methods: Any method that is neither related to class or object is a Static method.

Syntax:

@staticmethod 
def methodName():
    # code

@staticmethod is a decorator that is used to declare a method as a static method.

For example, let’s add a class method to our existing class that returns the type of authors’ work, and a static method that prints some text.

class BlogathonAuthors:




type ="freelancer"




def __init__(self, author_name, num_articles):

self.author_name = author_name

self.num_articles = num_articles

print("Created new author object")




def show(self):

"""This method prints the details of the author"""

print("In show method")

print(f"Author Name: {self.author_name}nNum of published articles: {self.num_articles}nType of Work: {BlogathonAuthors.type}")




def update(self, num_articles):

"""This method updates the number of published articles"""

print("In update method")

self.num_articles = num_articles




def total_articles(self, draft):

total = self.num_articles + draft

print(f"Total articles are: {total}")




@classmethod

def return_type(cls):

return cls.type




@staticmethod

def stat_method():

print("I am a static method")

Calling Class method: ClassName.method()

BlogathonAuthors.return_type()
calling class method | Python Object-Oriented Programming

Calling Static method: ClassName.method()

BlogathonAuthors.stat_method()
calling stat method

End Notes:

Thank you for being patient till the conclusion. By the end of this article, we are familiar with the basic concepts of OOP in Python. Stay tuned to my next article on some other OOP concepts.

I hope this article is informative. Feel free to share it with your study buddies.

Other Blog Posts by me

Feel free to check out my other blog posts from my Analytics Vidhya Profile.

You can find me on LinkedIn, Twitter in case you would want to connect. I would be glad to connect with you.

For immediate exchange of thoughts, please write to me at [email protected].

Happy Learning!

The media shown in this article are not owned by Analytics Vidhya and are used at the Author’s discretion. 

Harika Bonthu 24 Aug 2021

Frequently Asked Questions

Lorem ipsum dolor sit amet, consectetur adipiscing elit,

Responses From Readers

Clear

Giaki
Giaki 05 May, 2022

Compliments to Harika! Well done and very clear explanations. Giaki - Italy

Python
Become a full stack data scientist