Python Object-Oriented Programming: Exploring OOPs Concepts in Python

Updated on May 1, 2024

Article Outline

H2: What is Object-Oriented Programming – OOPs in Python H2: Difference Between Object-Oriented vs. Procedure-Oriented Programming Languages H2: Major Principle of OOPs in Python: Class and Object H2: Differentiating Between Instance Methods, Class Methods, And Static Methods H2: Fundamentals of OOPs in Python H2: Advantages of OOPs in Python H2: Conclusion FAQs

This article shares valuable insight into Object Oriented Programming in Python. Learn the various Python OOPs concepts, the difference between OOPs and POPs, classes and objects in Python, and much more. Let’s start.

Want to brush up on your knowledge of Python? Check this article on Python Functions!

H2: What is Object-Oriented Programming – OOPs in Python

Object-oriented programming is known as OOPs in Python. It is a programming style/technique that emphasizes the creation of programs using objects and classes. A collection of related functions and variables makes up an object.

The four major tenets of OOPs in Python are polymorphism, inheritance, encapsulation, and abstraction. Python programmers can build more modular, adaptable, and upkeep-friendly programs leveraging Python OOPs concepts.

Writing reusable, scalable code is made feasible by Python OOP, which also speeds up code development and decreases overall development time.

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H2: Difference Between Object-Oriented vs. Procedure-Oriented Programming Languages

Here is the difference between python Object-Oriented vs. Procedure-Oriented Programming Languages:

OOP (Object-Oriented Programming)	POP (Procedure-Oriented Programming)
Bottom-up programming technique	Top-down programming technique
Leverages Access modifiers	Doesn’t leverage any Access modifier
The program is categorized into objects	The program is categorized into functions
More secure and protected than POP	Less secure and protected than oops in python
Supports inheritance	Doesn’t support inheritance
Within member functions, objects can move unrestrictedly.	Within programs, data can move unrestrictedly from one function to another.

All the distinctions have now been covered; let’s learn about Python OOPs concepts. Before that, let’s briefly overview the two important principles of OOPs in Python: Object and Class.

H2: Major Principle of OOPs in Python: Class and Object

This section highlights the fundamental principles of object-oriented programming in Python. It comprises insights into classes, objects, methods, inheritance, encapsulation, polymorphism, and data abstraction.

H3: Class in Python

When it comes to Python OOPs concepts, a class serves as a template/basis for building objects. It outlines the details/insights and processes/operations connected to an object. Thanks to classes in Python, programmers can now organize and reuse codes without any hassle.

H3: Objects in Python

The object is an entity with a state and behavior attached to it. Objects in oops in python are any kind of data, dictionaries, texts, floating-point numbers, and arrays. An object is a single string or number. The phrase “Hello, world” is a string, the number 12 is an object, and a list is an item that may house additional objects.

H3: The Python init Method

The constructors in Java and C++ are comparable to the __init__ method. A class object is executed once it gets created. Any initialization you wish to carry out on your object can be done with the method.

H2: Differentiating Between Instance Methods, Class Methods, And Static Methods

Basis	Static Methods	Class Methods	Instance Methods
Scope	Related to the class	Relevant to the class	Relevant to an object
Access	No need for an object of the class	No need for an object of the class	Needs an object of the class
Use Cases	Methods that aren’t necessary to access the object’s current state or the class itself.	Methods that work with the class directly.	Methods that work with an object’s state.
Overriding	Can’t be modified by subclasses	Can’t be modified by subclasses	Can be modified by subclasses

H2: Fundamentals of OOPs in Python

The following principles are covered by approaches for object-oriented programming in Python.

Polymorphism
Encapsulation
Inheritance
Data Abstraction

H3: Polymorphism

“Poly” and “morphs” are two words that comprise polymorphism. The words polymorph and morph both mean many. Here is an example of polymorphism, one of the best Python OOPs concepts.

Class Biriyani:
   
    def intro(self):
        print("There are many types of Biriyani.")
 
    def flight(self):
        print("Most of the biryani are made of chicken.")
 
class mutton biriyani(Food):
   
    def flight(self):
        print("Mutton Biriyani tastes good.")
 
Class Mutton Biriyani (Food):
 
    def flight(self):
        print("Veg biriyani doesn’t take so good.")
 
obj_food = Biriyani()
obj_spr = Non0veg biriyani()
obj_ost = Veg Biriyani ()
 
obj_food.intro()
obj_food.flight()
 
obj_spr.intro()
obj_spr.flight()
 
obj_ost.intro()
obj_ost.flight()

Output:

There are many types of biriyani.
Most types of biriyani may seem tasty; others do not.
There are many types of biriyani.
Mutton biriyani tastes good.

H3: Encapsulation

Encapsulation, one of the most crucial Python OOPs concepts, simply refers to grouping data into a single class in its most basic form. Unlike Java, Python does not provide private keywords. It is best to prefix a class name with an underscore rather than simply access it.

class employee(object):
def __init__(self):  
self.name = 1234
self._age = 1234
self.__salary = 1234
 
object1 = employee()
print(object1.name)
print(object1._age)
print(object1.__salary) 

Output:

1234
Traceback (most recent call last):
1234
File “C:/Users/Harshit_Kant/PycharmProjects/test1/venv/encapsu.py”, line 10, in
print(object1.__salary)
AttributeError: ’employee’ object has no attribute ‘__salary.’

H3: Inheritance

One class’s ability to derive or inherit properties from another class is known as inheritance. To date, programmers consider it a vital concept of OOPs in Python.

# Python code to demonstrate how parent constructors
# are called.
 
# parent class
class Person(object):
 
    # __init__ is known as the constructor
    def __init__(self, name, idnumber):
        self.name = name
        self.idnumber = idnumber
 
    def display(self):
        print(self.name)
        print(self.idnumber)
         
    def details(self):
        print("My name is {}".format(self.name))
        print("IdNumber: {}".format(self.idnumber))
     
# child class
class Employee(Person):
    def __init__(self, name, id number, salary, post):
        self.salary = salary
        self.post = post
 
        # invoking the __init__ of the parent class
        Person.__init__(self, name, idnumber)
         
    def details(self):
        print("My name is {}".format(self.name))
        print("IdNumber: {}".format(self.idnumber))
        print("Post: {}".format(self.post))
 
 
# creation of an object variable or an instance
a = Employee(Rohan,' 112233, 300000, "Intern")
 
# calling a function of the class Person using
# its instance
a.display()
a.details()

Output:

Rohan
886012
My name is Rohan
IdNumber: 112233
Post: Intern

python oops concepts

H3: Data Abstraction

It shields the user from pointless code details. Moreover, this Python object-oriented programming concept was created when we wanted to keep private sensitive portions of our code implementation private. In oops in python, abstract classes can be used to implement data abstraction.

from abc import ABC,abstractmethod
class employee(ABC):
def emp_id(self,id,name,age,salary):	//Abstraction
pass
 
class childemployee1(employee):
def emp_id(self,id):
print("emp_id is 98765")
 
emp1 = childemployee1()
emp1.emp_id(id)

Output: 

emp_id is 98765

H2: Advantages of OOPs in Python

Objects can increase their security and maintainability by isolating their data and methods.
Objects can be reduced to their core components through abstraction, which makes them simpler to comprehend and use.
The ability for objects to inherit from other objects enables polymorphism and code reuse.
According to their type, objects can be used in many ways, known as polymorphism. This makes the code more versatile and flexible.
The ability to divide larger objects into more manageable chunks makes it simpler to comprehend, create, and debug code.

H2: Conclusion

So. the comprehensive guide on “Object-Oriented Programming in Python” ends here. Hopefully, you’ve understood everything there is to know about Python OOPs concepts, classes, and objects. Ensure practicing as much as you can and apply what you learn.

You can read the following articles to learn more about Python:

FAQs

What is the difference between inheritance and composition in OOP?

In inheritance, the child class is dependent upon the parent class. Whereas in composition, both the child class and parent class are independent.

What is the purpose of abstraction in OOP, and how can I achieve it in Python?

Abstraction in Python is defined as handling complexity by hiding unnecessary information from the user. This is one of the core Python OOPs concepts to know about.

How does OOP in Python differ from OOP in other programming languages?

All Python OOPs concepts have the means to store information about the object. Data is kept in attributes in Java and Python, which are variables connected to particular objects. The major difference between the two programming languages—Java and Python—the way they construct and manage class and object characteristics.

Can you explain the concept of polymorphism in OOP and how it is applied in Python?

"Polymorphism" is one of the Python OOPs concepts that signifies techniques, functions, or operators with identical names that can be used to conduct operations on various classes or objects. The word "polymorphism" denotes "a lot of forms" in programming.

Updated on May 1, 2024

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