OOP Python 3- Understanding Polymorphism in Python

Polymorphism, a key feature in Python, empowers the language to process different data types and classes in distinct ways. To put it simply, it's the ability to redefine methods and derived classes.

Key Concepts:

• Dynamic Processing: Polymorphism allows Python to dynamically process various data types and classes.
• Method Redefinition: The ability to redefine methods enables flexibility and adaptability in programming.

Benefits of Polymorphism:

• Versatility: Write code that can seamlessly handle different data types and class instances.
• Adaptability: Redefine methods based on specific use cases, enhancing code adaptability.

Example: Shape Class Imagine a "Shape" class; polymorphism allows programmers to determine the areas of different shapes using distinct methods. Regardless of the specific shape, the program will provide the correct area to the user.

class Shape:
    def calculate_area(self):
        pass  # Method to be overridden in derived classes

class Circle(Shape):
    def calculate_area(self, radius):
        return 3.14 * radius * radius

class Square(Shape):
    def calculate_area(self, side_length):
        return side_length * side_length

# Usage
circle_instance = Circle()
square_instance = Square()

print(circle_instance.calculate_area(5))  # Output: 78.5
print(square_instance.calculate_area(4))  # Output: 16

In this example, polymorphism allows each shape (Circle, Square) to define its own method for calculating the area, showcasing the power and adaptability of polymorphic behavior in Python.