Method Overriding in Python: How It Works and Why You Need It

Did you know that Python powers some of the most innovative technologies today and holds a staggering 29.1% market share in the programming world? Whether you're an aspiring developer or a seasoned professional, mastering method overriding in Python is a game-changer.

In object-oriented programming (OOP), classes are thought of as blueprints and objects as the actual buildings made from them. But here’s the twist: inheritance lets subclasses inherit behaviors from parent classes, and method overriding lets you tweak those behaviors to fit your needs. This flexibility makes Python one of the most dynamic and powerful programming languages out there.

In this blog, you will explore method overriding in Python — from what it is and how it works to why it’s essential for creating efficient and future-proof software. Ready to take your Python skills to the next level? 

Let’s dive in!

What is Method Overriding?

Method overriding in Python allows a subclass to provide a specific implementation of a method already defined in its parent class. This core concept in Object-Oriented Programming (OOP) makes your code more flexible and customizable.

When you use method overriding, you redefine a method in the subclass with the same name and parameters as the one in the parent class. This enables you to change the method's behavior in the subclass while preserving the parent class's structure.

The key features of method overriding in Python include:

• Same Method Signature: The method name and parameters in the subclass must match those of the parent class.
• Customization: You can modify the inherited method to perform different actions or return values more suited to the subclass’s needs.
• No Changes to Parent Class: Method overriding allows you to change the behavior of methods in subclasses without altering the parent class.
• Dynamic Polymorphism: It enables polymorphism in Python, where different classes can implement methods in their way. 

But why is it such a powerful tool in object-oriented programming (OOP)? Read ahead!

Purpose of Method Overriding in Python

While it allows you to change the behavior of methods in subclasses, the actual value of method overriding becomes clear when we look at its purpose in real-world programming.

Let’s understand its vital purpose:

1. Customization of Inherited Methods for Specific Needs

• Allows you to customize inherited methods to fit the specific needs of the subclass, giving you more control over how inherited behavior is executed.
• Can change the method’s behavior in a subclass without touching the parent class, making your code more modular and easier to maintain.

2. Achieving Polymorphism

• Different subclasses can implement their versions of a method, achieving polymorphism.
• Can use a uniform interface to handle objects of different types, as each object can define its specific behavior for the same method name.

3. Simplifying Code by Avoiding Duplication

• Allows you to reuse the parent class’s method and extend or modify it instead of writing redundant code from scratch.
• It reduces unnecessary duplication in code, leading to cleaner, more efficient, and easier-to-read and maintain software.

In short, method overriding in Python is all about providing customized real-world solutions, ensuring your code is adaptable, and avoiding redundancy.

Also Read: 12 Amazing Real-World Applications of Python

Understanding Method Overriding in Python

Imagine you're working on a project that involves multiple types of vehicles — cars, trucks, and motorcycles. Each can "drive" but has unique driving behaviors. Instead of rewriting the logic for each vehicle from scratch, you can use method overriding to customize the behavior of the drive() method for each while maintaining a shared interface.

This is exactly how method overriding in Python works: a subclass inherits a method from its parent class and then provides its implementation, adapting it for its specific needs.

Let’s understand it with an example along with its output:

Consider the following code where we have a parent class, Vehicle, and two subclasses, Car and Truck, each overriding the drive() method to provide their specific implementations.

# Parent class
class Vehicle:
    def drive(self):
        print("This vehicle is driving.")

# Child class 1: Car
class Car(Vehicle):
    def drive(self):
        print("The car is driving on the road.")

# Child class 2: Truck
class Truck(Vehicle):
    def drive(self):
        print("The truck is hauling cargo on the highway.")

# Instantiate objects
car = Car()
truck = Truck()

# Calling the overridden methods
car.drive()   # Output: The car is driving on the road.
truck.drive() # Output: The truck is hauling cargo on the highway.

Now that we’ve seen an example, let's take a closer look at how method overriding happens in Python.

How Does Method Overriding Work in Python?

The process involves a few straightforward steps:

1. Define a parent class with a method: The parent class defines a method, like drive(), with general behavior for all vehicles.

2. Create a child class that inherits from the parent class: The child classes, such as Car and Truck, inherit the properties and methods of the parent class Vehicle.

3. Redefine the method in the child class: The child class provides its version of the drive() method, overriding the one in the parent class.

Here’s a simple example of method overriding where a parent class Shape has a method area(), and the child classes Circle and Rectangle override it to calculate their respective areas:

# Parent class
class Shape:
    def area(self):
        pass  # Placeholder for area method

# Child class 1: Circle
class Circle(Shape):
    def __init__(self, radius):
        self.radius = radius
    
    def area(self):
        return 3.14 * (self.radius ** 2)

# Child class 2: Rectangle
class Rectangle(Shape):
    def __init__(self, length, width):
        self.length = length
        self.width = width
    
    def area(self):
        return self.length * self.width

# Instantiate objects
circle = Circle(5)
rectangle = Rectangle(4, 6)

# Calling the overridden methods
print(f"Area of Circle: {circle.area()}")     # Output: Area of Circle: 78.5
print(f"Area of Rectangle: {rectangle.area()}") # Output: Area of Rectangle: 24

Now, let us move on to the key concepts of the method.

Key Concepts of Method Overriding in Python

In Python, the super() function allows you to access methods from the parent class even when overridden in the child class. This can be useful when calling the parent class method inside the overridden method.

Here’s an example of how super() works with method overriding:

# Parent class
class Animal:
    def sound(self):
        print("Some generic animal sound")

# Child class 1: Dog
class Dog(Animal):
    def sound(self):
        super().sound()  # Calling the parent class method
        print("Bark")

# Child class 2: Cat
class Cat(Animal):
    def sound(self):
        super().sound()  # Calling the parent class method
        print("Meow")

# Instantiate objects
dog = Dog()
cat = Cat()

# Calling the overridden methods
dog.sound()  # Output: Some generic animal sound \n Bark
cat.sound()  # Output: Some generic animal sound \n Meow

In this example: 

• The Dog and Cat classes override the sound() method. 
• The super().sound() call in both subclasses calls the sound() method from the parent Animal class before adding their specific sounds.

Now, as you understand the method overriding, knowing when to use it is just as important as knowing how to implement it. Below are a few scenarios:

• Customizing inherited behavior: When you need to modify the behavior of an inherited method without altering the parent class.
• Creating polymorphic behavior: When different objects (of different classes) need to implement the same method but with different functionality.
• Maintaining code flexibility: If you want your code to be adaptable and easily extendable without changing the core structure.

So you've seen what method overriding in Python is, but what about method overloading? While both techniques sound similar, they serve different purposes. 

Let’s unravel the difference between these two!

What is the Difference Between Method Overloading and Method Overriding in Python

Method overloading typically occurs in statically typed languages like Java or C++, where multiple methods with the same name but different parameters can be defined. 

However, in Python, method overloading is not natively supported, and it is simulated using default arguments or variable-length argument lists. Let’s compare the two in a clear, side-by-side table:

Thus, understanding these distinctions is crucial for writing more efficient and maintainable Python code!

Also Read: Top 10 Reasons Why Python is So Popular With Developers in 2025

Method Overriding in Python with Multiple and Multi-level Inheritance

Inheritance is one of the cornerstones of Object-Oriented Programming (OOP). It allows one class to inherit properties and methods from another, fostering reusability, maintainability, and a hierarchical relationship between classes. 

But what happens when we combine multiple inheritance or extend a class over several levels? The dynamic nature of method overriding becomes even more powerful and flexible in such scenarios.

Before we jump into method overriding in the context of multiple and multi-level inheritance, let’s first understand how inheritance works in Python.

Overview of Inheritance in Python

At its core, inheritance in Python allows a class (called the child or subclass) to inherit attributes and methods from another class (called the parent or superclass). This reduces the need for repetitive code.

• Single Inheritance: The subclass inherits from only one parent class.
• Multiple Inheritance: The subclass inherits from more than one parent class.
• Multilevel Inheritance: A class inherits from another class, which in turn inherits from yet another class.

The power of method overriding in inheritance lies in how subclasses can change (override) inherited methods to suit their specific behavior while maintaining the structure defined by the parent class.

Also Read: Types of Inheritance in Python | Python Inheritance [With Examples]

Let’s see how method overriding works in both multiple and multi-level inheritance.

Multiple Inheritance

A class can inherit from multiple parent classes in multiple inheritance. This allows a child class to inherit features from multiple classes and override methods from all parent classes.

However, Python follows the Method Resolution Order (MRO) to determine which method to call when multiple parent classes have a method with the same name. Let’s look at an example:

# Parent Class 1
class Animal:
    def sound(self):
        print("Animal makes a sound")

# Parent Class 2
class Bird:
    def sound(self):
        print("Bird chirps")

# Child Class
class Parrot(Animal, Bird):
    def sound(self):
        print("Parrot squawks")

# Instantiate object
parrot = Parrot()
parrot.sound()  # Output: Parrot squawks

In the example above:

• The Parrot class inherits from both the Animal and Bird classes.
• Even though both parent classes define a sound() method, the Parrot class overrides it to provide its implementation.
• When we call parrot.sound(), the Parrot class’s version of sound() is invoked.

Python uses the MRO to decide which method to execute, but in this case, the child class explicitly overrides the method.

Multilevel Inheritance

In multilevel inheritance, a class inherits from another class, which in turn inherits from another class, forming a chain of inheritance. This adds another layer of complexity but also provides a powerful mechanism for modifying and extending inherited functionality.

Let’s look at how method overriding works in a multilevel inheritance hierarchy.

# Grandparent Class
class Animal:
    def sound(self):
        print("Animal makes a sound")

# Parent Class
class Mammal(Animal):
    def sound(self):
        print("Mammal makes a sound")

# Child Class
class Dog(Mammal):
    def sound(self):
        print("Dog barks")

# Instantiate object
dog = Dog()
dog.sound()  # Output: Dog barks

In the example:

• The Dog class inherits from Mammal, which in turn inherits from Animal.
• Although Animals and Mammals have sound() methods, the Dog class overrides the sound() method to specify its unique behavior.

Thus, when combined with method overriding, both multiple inheritance and multilevel inheritance give you the power to write more dynamic and flexible Python code.

Also, for fun practice, read Perfect Number Program In Python: How to check if a number is perfect or not?

Calling the Parents' Method within the Overridden Method

When you override a method in Python, there are situations where you might still want to call the parent class's version of the method — either before or after executing the custom behavior in the child class.

There are two common ways to achieve this in Python:

1. Using the class name
2. Using the super() function

Both approaches give you the flexibility to call the parent class's method while allowing you to modify or extend it in the child class. Let's explore both in detail.

1. Using the Class Name

One straightforward method is to reference the parent class directly by its name. This is useful when you specify the method you want to call explicitly and know the exact class in the inheritance chain.

Let us grab it with an example:

# Parent Class
class Animal:
    def sound(self):
        print("Some generic animal sound")

# Child Class
class Dog(Animal):
    def sound(self):
        Animal.sound(self)  # Calling the parent class method explicitly
        print("Dog barks")

# Instantiate object
dog = Dog()
dog.sound()

Output:

Some generic animal sound
Dog barks

In this example:

• The Dog class overrides the sound() method.
• The overridden method calls the parent class Animal's sound() method directly using Animal.sound(self).
• This ensures the behavior from the parent class is included alongside the new behavior introduced in the subclass.

2. Using super()

The super() function automatically handles the complexity of MRO in the case of multiple inheritance. This makes it ideal for scenarios where you have numerous parent classes or work with more complex class hierarchies.

Here’s a code example for it:

# Parent Class
class Animal:
    def sound(self):
        print("Some generic animal sound")

# Child Class 1
class Mammal(Animal):
    def sound(self):
        super().sound()  # Calls the parent class method using super()
        print("Mammal makes a sound")

# Child Class 2
class Dog(Mammal):
    def sound(self):
        super().sound()  # Calls the method from the Mammal class
        print("Dog barks")

# Instantiate object
dog = Dog()
dog.sound()

Output:

Some generic animal sound
Mammal makes a sound
Dog barks

In this example:

• The Dog class overrides the sound() method, but it also wants to include the behavior of the Mammal class, which calls the parent class's method via super().
• The call super().sound() first invokes the sound() method of the Mammal class, and Mammal's sound() method, in turn calls the sound() method of the Animal class.
• This results in a chain of method calls, where each class gets a chance to contribute to the behavior of the sound() method.

Also Read: Difference Between Function and Method in Python

Now that we've explored how to call parent methods within overridden methods let's dive into a more nuanced aspect— overriding methods with different parameters. 

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What are the Different Approaches to Override Methods with Different Parameters?

Sometimes, you might need to modify the way parameters are handled, especially when you want to pass a varying number of arguments or want to make certain parameters optional.

Overriding methods with different parameters offers great flexibility in customizing inherited methods. Let’s look at three common approaches of it:

1. Using *args: Variable-Length Positional Arguments

With *args, we can pass any number of positional arguments to a method. This is useful when you don’t know how many arguments might be passed to the method, allowing for flexibility. 

Example:

# Parent Class
class Animal:
    def speak(self, *args):
        for sound in args:
            print(f"Animal makes a {sound} sound")

# Child Class
class Dog(Animal):
    def speak(self, *args):
        print("Dog says:")
        super().speak(*args)  # Calls parent class speak method with *args
        print("Woof!")

# Instantiate object
dog = Dog()
dog.speak("bark", "growl")

Output:

Dog says:
Animal makes a bark sound
Animal makes a growl sound
Woof!

2. Using **kwargs: Variable-Length Keyword Arguments

**kwargs allows you to pass a variable number of keyword arguments to a method. It’s useful to pass named arguments to a method without specifying them upfront. 

Example: 

# Parent Class
class Animal:
    def move(self, **kwargs):
        print(f"Animal is moving {kwargs.get('direction', 'forward')}")

# Child Class
class Dog(Animal):
    def move(self, **kwargs):
        print("Dog is moving:")
        super().move(**kwargs)  # Calls parent class move method with **kwargs
        print(f"Dog is moving {kwargs.get('direction', 'forward')} with speed {kwargs.get('speed', 'normal')}")

# Instantiate object
dog = Dog()
dog.move(direction="left", speed="fast")

Output:

Dog is moving:
Animal is moving left
Dog is moving left with speed fast

3. Optional Parameters with Default Values

You can also override methods with parameters that have default values, making them optional when calling the method. This allows you to provide a more flexible interface while keeping the method signature clean.

Example: 

# Parent Class
class Animal:
    def info(self, name="Unknown", age=0):
        print(f"Animal's name is {name} and age is {age}")

# Child Class
class Dog(Animal):
    def info(self, name="Unknown", age=0, breed="Unknown"):
        super().info(name, age)  # Calls parent class info method
        print(f"Dog's breed is {breed}")

# Instantiate object
dog = Dog()
dog.info("Buddy", 3, "Labrador")

Output:

Animal's name is Buddy and age is 3
Dog's breed is Labrador

These techniques help you customize method behavior in child classes while maintaining flexibility in their acceptable parameters.

What are the Features of Method Overriding in Python?

Method overriding is like the customization tool of object-oriented programming. It allows you to redefine a pre-existing method from a parent class into a child class to suit your needs better. 

This flexibility makes Python a powerful language for building scalable and reusable code. Have a look at the key features of it:

• Customization: Tweak inherited methods to match specific requirements.
• Polymorphism: Same method name, different implementation in different classes.
• Code Reusability: Build on existing methods without duplicating code.
• Dynamic Binding: Python decides the method to call at runtime based on the object.

In data science, where flexibility and customization are key, method overriding is a game-changer. It helps you tailor methods to specific data preprocessing, model training, and evaluation tasks.

• Custom Pipelines: Override methods to create personalized data transformations in your workflow.
• Model Customization: Modify fit() and predict() methods to implement custom algorithms.
• Effortless Integration: Extend libraries like scikit-learn without changing their core code.

Also Read: 5 Reasons to Choose Python for Data Science – How Easy Is It

Now that you understand what method overriding is and how it works, let's explore the real-world advantages it brings to the table.

What are the Benefits of Method Overriding in Python?

Why stick to static, repetitive code when you can make it flexible, reusable, and scalable? Method overriding in Python isn’t just a feature — it’s a strategic tool that boosts your coding efficiency and adaptability. 

Let’s break down how it benefits you as a developer.

• Enhances Code Flexibility and Reusability: Method overriding allows you to tweak inherited methods, making your code more versatile and reusable in different contexts.
• Simplifies Program Design: Following the DRY (Don’t Repeat Yourself) principle, you avoid writing redundant code. Override inherited methods and reduce the need for repetitive logic.
• Facilitates Polymorphism: You can define methods with the same name across different classes but with other behaviors. This enables polymorphism — handling different object types with a single interface.
• Promotes Extensibility and Scalability: Need to add new functionality to a growing project? Overriding methods ensures your code can scale easily without breaking existing functionality.
• Reduces Redundancy: Why write the same method in every class when you can override and adapt inherited methods? It streamlines your code and ensures better management.
• Supports Dynamic Behavior: Method overriding allows your code to change its behavior at runtime. This capability drives polymorphism and allows more dynamic interactions between objects.

In a nutshell, method overriding empowers your Python program code to be more dynamic, flexible, and efficient.

Also Read: Top 30 Python Pattern Programs You Must Know About

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References:
https://www.techspot.com/news/105157-python-most-popular-coding-language-but-challengers-gaining.html