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Python Indentation, Comments and Variables
Object Oriented Programming in Python
Exception Handling in Python
Sending emails with Python
Unit test in python programming
Python programming (zero to advance!!!)
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Object-Oriented Programming (OOP) in Python

In this section, we’ll dive into the powerful world of Object-Oriented Programming (OOP) in Python.

What is Object-Oriented Programming?

Object-Oriented Programming (OOP) is a programming paradigm that revolves around the concept of objects. Objects are instances of classes, which act as blueprints for creating these objects. OOP promotes code reusability, modularity, and easier maintenance by organizing code into objects that interact with each other.

Classes and Objects

In Python, classes are defined using the `class` keyword. Let’s define a simple class called `Person`:

class Person:
def __init__(self, name, age): = name
    self.age = age

def greet(self):
     return f”Hello, my name is {} and I am {self.age} years old.”

Here, `Person` is a class with two attributes (`name` and `age`) and a method (`greet`). To create an object (instance) of this class, we use the class constructor:

# Creating an object of the Person class
person1 = Person(“Alice”, 30)

Attributes and Methods

Attributes are variables that belong to objects, while methods are functions that belong to objects. We can access attributes and call methods using dot notation:

print( # Output: Alice
print(person1.age) # Output: 30
print(person1.greet()) # Output: Hello, my name is Alice and I am 30 years old.


Inheritance is a key feature of OOP that allows a class to inherit attributes and methods from another class. This promotes code reuse and allows for creating hierarchical relationships between classes. Here’s an example of inheritance:
Certainly! Here’s an example demonstrating inheritance in Python:

class Animal:
def __init__(self, name): = name

def speak(self):
     raise NotImplementedError(“Subclass must implement abstract method”)

class Dog(Animal):
def speak(self):
     return f”{} says Woof!”

class Cat(Animal):
def speak(self):
      return f”{} says Meow!”

class Cow(Animal):
def speak(self):
     return f”{} says Moo!”

# Create instances of each subclass
dog = Dog(“Buddy”)
cat = Cat(“Whiskers”)
cow = Cow(“Bessie”)

# Call the speak method on each instance
print(dog.speak()) # Output: Buddy says Woof!
print(cat.speak()) # Output: Whiskers says Meow!
print(cow.speak()) # Output: Bessie says Moo!

In this example:
– We define a base class `Animal` with an abstract method `speak()`.
– Subclasses `Dog`, `Cat`, and `Cow` inherit from the `Animal` class and implement the `speak()` method.
– Each subclass provides its own implementation of the `speak()` method.
– We create instances of each subclass and call the `speak()` method on them to demonstrate polymorphism.


Encapsulation is the practice of bundling the data (attributes) and methods that operate on the data together within a class. It helps in hiding the internal state of objects and only exposing necessary functionalities.
Encapsulation in Python refers to the concept of bundling the data (attributes) and methods (functions) that operate on the data into a single unit known as a class. It helps in hiding the internal state and implementation details of an object from the outside world, and only exposes the necessary functionalities through methods.
In Python, private and public variables differ in terms of their accessibility and visibility:

1. Public Variables:
– Public variables in Python are accessible from outside the class.
– They are not prefixed with underscores (`_` or `__`).
– Public variables can be accessed and modified directly by instances of the class.

2. Private Variables:
– Private variables in Python are intended to be accessed only within the class where they are defined.
– They are prefixed with double underscores (`__`).
– Private variables cannot be accessed or modified directly from outside the class.
– Accessing or modifying private variables from outside the class will result in an `AttributeError`.

Here’s a comparison of public and private variables in Python using an example:

class Car:
def __init__(self, make, model, year):
       self.make = make # Public variable
      self.model = model # Public variable
      self.year = year # Public variable

      self.__mileage = 0 # Private variable

def drive(self, miles):
      self.__mileage += miles

def get_mileage(self):
     return self.__mileage

# Create an instance of the Car class
my_car = Car(“Toyota”, “Corolla”, 2022)

# Access public variables directly
print(“Make:”, my_car.make) # Output: Toyota
print(“Model:”, my_car.model) # Output: Corolla
print(“Year:”, my_car.year) # Output: 2022

# Attempting to access private variable directly (will result in an AttributeError)
# print(“Mileage:”, my_car.__mileage) # This will raise an AttributeError

# Accessing private variable using a method
print(“Mileage:”, my_car.get_mileage()) # Output: 100

In this example:
– `make`, `model`, and `year` are public variables accessible directly from outside the class.
– `__mileage` is a private variable prefixed with double underscores (`__`). It can only be accessed or modified within the `Car` class, not from outside.
– A method `drive()` is used to modify the private variable `__mileage`.
– The method `get_mileage()` allows access to the private variable `__mileage` indirectly from outside the class.


Polymorphism allows objects of different classes to be treated as objects of a common superclass. It enables flexibility and extensibility in the code by allowing methods to be overridden in subclasses.
Polymorphism in Python refers to the ability of different objects to respond to the same method or function in different ways. It allows objects of different classes to be treated as objects of a common superclass.

There are two main types of polymorphism:

1. Method Overriding:
Method overriding occurs when a subclass provides a specific implementation of a method that is already defined in its superclass. The method in the subclass overrides the implementation of the method in the superclass.

2. Operator Overloading:
Operator overloading allows operators to be used with objects of user-defined classes. By defining special methods in a class, such as `__add__()` for addition or `__mul__()` for multiplication, you can customize the behavior of operators when applied to objects of that class.

Here’s an example demonstrating method overriding:

class Animal:
def speak(self):
     return “Animal speaks”

class Dog(Animal):
def speak(self):
     return “Dog barks”

class Cat(Animal):
def speak(self):
     return “Cat meows”

# Polymorphism in action
animals = [Animal(), Dog(), Cat()]

for animal in animals:

Animal speaks
Dog barks
Cat meows

In this example:
– The `Animal` class defines a method `speak()` that returns a generic message.
– The `Dog` and `Cat` classes inherit from the `Animal` class and override the `speak()` method with their own implementations.
– When the `speak()` method is called on objects of different classes (`Animal`, `Dog`, `Cat`), each object responds according to its own implementation, demonstrating polymorphic behavior.
Operator overloading in Python allows user-defined classes to redefine the behavior of operators such as `+`, `-`, `*`, `/`, and many others. By defining special methods within a class, you can customize the behavior of these operators when applied to objects of that class.

Here’s an example demonstrating operator overloading for addition (`+` operator):

class Vector:
def __init__(self, x, y):
      self.x = x
      self.y = y

def __add__(self, other):
     return Vector(self.x + other.x, self.y + other.y)

def __str__(self):
    return f”Vector({self.x}, {self.y})”

# Create two Vector objects
v1 = Vector(2, 3)
v2 = Vector(5, 7)

# Add the two vectors using the ‘+’ operator
result = v1 + v2

# Display the result
print(result) # Output: Vector(7, 10)

In this example:
– We define a `Vector` class representing a 2D vector with `x` and `y` components.
– We override the `__add__()` special method, which allows us to use the `+` operator with objects of the `Vector` class.
– When the `+` operator is applied to two `Vector` objects (`v1 + v2`), Python internally calls the `__add__()` method of the left operand (`v1`) and passes the right operand (`v2`) as an argument.
– The `__add__()` method returns a new `Vector` object whose `x` component is the sum of the `x` components of the operands, and similarly for the `y` component.

Similarly, you can overload other operators such as `-`, `*`, `/`, `==`, `<`, `>`, and more by defining corresponding special methods (`__sub__()`, `__mul__()`, `__truediv__()`, `__eq__()`, `__lt__()`, `__gt__()`, etc.) within your class. This flexibility allows you to define custom behaviors for operators based on the semantics of your class.
Polymorphism allows for more flexible and modular code, as it enables the same interface to be used with different types of objects.

By leveraging the power of classes and objects, you can create robust, modular, and maintainable code for a wide range of applications.

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