Discover the Secrets of Method Overriding in Python!

Method overriding in Python allows a subclass to implement a method already defined in its superclass, enabling polymorphism. It works by redefining a method in the subclass with the same signature as the parent class, ensuring dynamic method dispatch. Method overriding is widely used in GUI frameworks like Tkinter, game engines like Pygame, and web frameworks like Django.

In this blog, you’ll explore method overriding in Python, learn how to override methods with varying parameters, and understand its benefits in Python object-oriented programming.

How Method Overriding in Python Works: A Detailed Overview

Method overriding in Python occurs when a subclass provides its own implementation of a method that is already defined in its superclass. The method in the subclass has the same name, parameters, and signature as the method in the parent class.

When the method is called on an instance of the subclass, the subclass’s version of the method is executed, not the superclass's version. This allows subclasses to customize or extend the behavior of inherited methods, supporting the concept of polymorphism in OOP.

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Now let's understand the key features of method overriding in Python and how they contribute to creating flexible, dynamic, and maintainable object-oriented systems.

1. Same Method Signature

To override a method, the subclass must define a method with the exact same name, parameter list, and signature as the one in the parent class. This ensures that when the method is called on a subclass object, Python knows to replace the parent method with the subclass version.

Code Example:

class Animal:
    def speak(self):
        print("Animal speaks")

class Dog(Animal):
    def speak(self):
        print("Dog barks")

# Creating an instance of Dog
dog = Dog()
dog.speak()

Explanation:

• Animal is the superclass with a method speak.
• Dog is a subclass of Animal that overrides the speak method.
• The method signature (name speak and no parameters) is the same in both the parent and subclass.

Output: Even though the speak method is defined in the Animal class, the method from the Dog subclass is invoked because of method overriding. This demonstrates that the method in the subclass replaces the parent method when invoked on an object of the subclass.

Dog barks

2. Dynamic Method Dispatch

Python uses dynamic method dispatch (also known as late binding), meaning the method to be invoked is determined at runtime based on the type of object, not the type of reference. This allows the method in the subclass to be called even if the object is referred to by a variable of the parent class type.

Code Example:

class Animal:
    def speak(self):
        print("Animal speaks")

class Dog(Animal):
    def speak(self):
        print("Dog barks")

# Creating an instance of Dog
animal = Dog()
animal.speak()

Explanation:

• Even though the reference variable animal is of type Animal, the method from the Dog class is called due to dynamic method dispatch.
• Python determines the actual class (Dog) of the object at runtime and calls the speak method from that class.

Output: The output is Dog barks because Python calls the speak method from the Dog class, demonstrating dynamic method dispatch.

Dog barks

Also Read: Polymorphism in OOP: What is It, Its Types, Examples, Benefits, & More

3. No Need for Explicit Declaration

Unlike some other programming languages, Python doesn’t require a special keyword like "override" to explicitly mark a method as overridden. As long as the method signatures match, it’s considered an override.

Code Example:

class Animal:
    def speak(self):
        print("Animal speaks")

class Cat(Animal):
    def speak(self):
        print("Cat meows")

# Creating an instance of Cat
cat = Cat()
cat.speak()

Explanation:

• In Python, there is no need to explicitly mark the method as override. You simply redefine the method in the subclass with the same signature.
• The method in Cat overrides the one in Animal.

Output: Even though the speak method is defined in Animal, Python calls the speak method from the Cat class without any need for special annotations or keywords. This shows Python’s flexibility with method overriding.

Cat meows

Also Read: Argument vs Parameter: Difference Between Argument and Parameter [With Example]

4. Access to Parent Method

The subclass can still access the parent class method through super(). This is particularly useful when you want to extend or modify the behavior of the inherited method rather than completely replacing it.

Code Example:

class Animal:
    def speak(self):
        print("Animal speaks")

class Bird(Animal):
    def speak(self):
        super().speak()  # Calls the parent class method
        print("Bird chirps")

# Creating an instance of Bird
bird = Bird()
bird.speak()

Explanation:

• Bird overrides the speak method, but it also calls the speak method of the parent class Animal using super().
• super().speak() invokes the parent method before adding additional behavior in the Bird class.

Output: The output first prints the result of the parent method (Animal speaks) and then the subclass method (Bird chirps). This shows how we can extend the functionality of the inherited method by calling the parent method via super().

Animal speaks
Bird chirps

Also Read: Understanding the Differences Between Inheritance and Polymorphism in Java

5. Polymorphism

Method overriding is a key feature of polymorphism, allowing objects of different classes to be treated as objects of a common superclass. The correct method is called based on the actual object type, enabling different behaviors depending on the class.

Code Example:

class Animal:
    def speak(self):
        print("Animal speaks")

class Dog(Animal):
    def speak(self):
        print("Dog barks")

class Cat(Animal):
    def speak(self):
        print("Cat meows")

# Function demonstrating polymorphism
def animal_speak(animal: Animal):
    animal.speak()

# Creating instances of Dog and Cat
dog = Dog()
cat = Cat()

# Polymorphism in action
animal_speak(dog)  # Calls Dog's speak
animal_speak(cat)  # Calls Cat's speak

Code Explanation:

• The function animal_speak() takes an Animal object and calls its speak method.
• Since both Dog and Cat are subclasses of Animal, the correct method is invoked based on the actual object type at runtime, demonstrating polymorphism.

Output: The output shows that the animal_speak() function calls the overridden method from both Dog and Cat. This demonstrates polymorphism, where the method invoked depends on the actual object type.c

Dog barks
Cat meows

Also Read: Top 70 Python Interview Questions & Answers: Ultimate Guide 2025

6. Improved Flexibility and Customization

By overriding methods, subclasses can customize inherited behavior to suit specific needs, improving flexibility and the reusability of the code. This also reduces redundancy, as common behavior can be placed in a superclass while specialized behavior is implemented in subclasses.

Code Example:

class Vehicle:
    def start(self):
        print("Vehicle starting")

class ElectricCar(Vehicle):
    def start(self):
        print("Electric Car starting silently")

class GasCar(Vehicle):
    def start(self):
        print("Gas Car starting with noise")

# Creating instances of ElectricCar and GasCar
electric_car = ElectricCar()
gas_car = GasCar()

# Demonstrating overridden start methods
electric_car.start()
gas_car.start()

Code Explanation:

• Vehicle defines a general method start, but ElectricCar and GasCar override it to provide customized behavior for each type of vehicle.
• The flexibility to customize behavior based on the subclass is a major advantage of method overriding.

Output: The output shows how method overriding allows each subclass to have its own specific behavior for the start method, improving flexibility and customization.

Electric Car starting silently
Gas Car starting with noise

7. Access Control

Python does not enforce access control modifiers like public or private. However, method overriding can still be used to control the visibility and behavior of inherited methods by using naming conventions (e.g., prefacing a method with an underscore to indicate it is intended for internal use).

Code Example:

class Vehicle:
    def start(self):
        print("Vehicle starting")

class Truck(Vehicle):
    def _start(self):  # Protected method intended to be overridden
        print("Truck starting with a heavy load")

# Creating an instance of Truck
truck = Truck()
truck._start()  # Direct access to the overridden method

Explanation:

• In this case, _start() is a "protected" method (by convention, indicated with a leading underscore) in the subclass Truck.
• Even though it’s intended to be used only within the class or subclass, it can still be accessed directly.

Output: This demonstrates that while Python does not enforce access control like private or protected methods, it is still possible to indicate method visibility through naming conventions (e.g., _start as protected).

Truck starting with a heavy load

Also Read: Python Cheat Sheet: From Fundamentals to Advanced Concepts for 2025

Let’s see how Python developers work around the lack of traditional overloading by using flexible techniques to override methods with varying parameters.

Techniques to Override Methods with Different Parameters

Python lacks traditional method overloading as seen in Java or C++, where methods can share a name but differ by signature. Instead, it permits only one method per name in a class. To support varying arguments in overridden methods, developers use dynamic parameters like default values, *args, **kwargs, and runtime type checks.

Below are three core approaches to enable method overriding in Python when handling different sets of parameters:

Approach 1: Use Default Arguments

Default arguments let methods define parameters with fallback values, allowing them to be called with fewer arguments. In method overriding, a subclass can redefine the method using different default values without altering the method name. This enables argument flexibility while preserving method compatibility.

Code Example:

class Animal:
    def speak(self, sound="Generic Sound"):
        print(f"Animal says: {sound}")

class Dog(Animal):
    def speak(self, sound="Bark"):
        print(f"Dog says: {sound}")

Explanation:

• speak() in both classes accepts one parameter with a default value.
• The subclass Dog overrides the method but alters the default value, showcasing how behavior can be customized.
• Since both signatures remain compatible, dynamic dispatch calls the correct version based on the object.

Output:

• a.speak() uses the default from the Animal class.
• d.speak() uses the overridden default in Dog.
• Passing "Woof" overrides the default at runtime, demonstrating how parameter values can be customized per call.

Animal says: Generic Sound
Dog says: Bark
Dog says: Woof

Approach 2: Use Variable-Length Arguments (*args, kwargs)

Python's *args and **kwargs allow methods to accept arbitrary positional and keyword arguments. This supports flexible method signatures without explicit parameter declarations. In method overriding, the base class can define a generic interface, while subclasses override it with specific parameters as needed. This ensures compatibility and extensibility across inheritance hierarchies.

Code Example:

class Shape:
    def area(self, *args):
        print("Shape area not defined")

class Rectangle(Shape):
    def area(self, length, width):
        print(f"Rectangle area: {length * width}")

Explanation:

• Shape.area() accepts any number of arguments using *args, but doesn't perform any logic.
• Rectangle.area() overrides this method with explicitly defined parameters length and width.
• This allows the subclass to specialize while the superclass remains general-purpose.

Output:

• The base class provides a fallback method for any parameter count.
• The subclass adds a strict definition for the rectangle area formula.
• The overridden method in the subclass is invoked due to dynamic dispatch and method resolution.

Shape area not defined
Rectangle area: 20

Approach 3: Use Function Dispatch with singledispatchmethod

The @singledispatchmethod decorator from Python’s functools module enables method dispatch based on the type of the first argument. It defines a generic method and routes calls to registered implementations according to argument types. This simulates method overloading found in statically typed languages and supports runtime polymorphism through type-based resolution.

Code Example:

from functools import singledispatchmethod

class Printer:
    @singledispatchmethod
    def print_data(self, data):
        print("Default print: ", data)

    @print_data.register
    def _(self, data: str):
        print("Printing string:", data)

    @print_data.register
    def _(self, data: int):
        print("Printing integer:", data)

Explanation:

• The print_data() method becomes a generic dispatcher.
• Each registered function handles a specific type (str, int).
• The dispatching happens based on the runtime type of the first argument.

Output:

• "Hello" triggers the str-based handler.
• 123 invokes the int version.
• [1, 2] does not match any registered type and falls back to the default.

Printing string: Hello
Printing integer: 123
Default print: [1, 2]

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Let’s explore how different inheritance types influence method overriding behavior and what Python’s method resolution order means in each case.

Method Overriding in Python Across Various Inheritance Types

Method Overriding in Python plays a crucial role in OOP by allowing subclasses to customize or extend the behavior of inherited methods. Understanding how method overriding works across different inheritance types is vital, especially when dealing with more complex scenarios involving multiple inheritance and method resolution order.

Below, we explore how method overriding works across various inheritance in Python:

1. Method Overriding in Single Inheritance

In single inheritance, a subclass derives from one parent class. This structure allows the subclass to override methods from the parent to implement specialized behavior. If a method with the same name is defined in both classes, the subclass version takes precedence at runtime. This is resolved using Python’s dynamic method dispatch mechanism.

Code Example:

class Animal:
    def speak(self):
        print("Animal makes a sound")

class Dog(Animal):
    def speak(self):
        print("Dog barks")

# Creating an instance of Dog
dog = Dog()
dog.speak()  # Calls the overridden method in Dog

Explanation:

• The Dog class inherits from Animal and overrides the speak() method.
• The speak() method in Dog is called instead of the one in Animal when invoked on an instance of Dog.

Output: Since Dog overrides the speak() method, the speak() method in the Dog class is executed, which prints "Dog barks". This shows that overriding in single inheritance allows you to modify or replace inherited methods in a straightforward way.

Dog barks

2. Method Overriding in Multiple Inheritance

In multiple inheritance, a subclass inherits from more than one parent class. If multiple parents define the same method, Python uses Method Resolution Order (MRO) to determine which version to execute. MRO follows the C3 linearization algorithm to create a consistent and deterministic method lookup path. The first matching method in the MRO is invoked at runtime.

Code Example:

class Animal:
    def speak(self):
        print("Animal makes a sound")

class Mammal:
    def walk(self):
        print("Mammal walks on land")

class Dog(Animal, Mammal):
    def speak(self):
        print("Dog barks")

# Creating an instance of Dog
dog = Dog()
dog.speak()  # Calls the overridden method in Dog
dog.walk()   # Calls the method from Mammal

Code Explanation:

• The Dog class inherits from both Animal and Mammal.
• The speak() method is overridden in Dog to change the behavior inherited from Animal.
• The walk() method is inherited from Mammal and is called directly without overriding.

Output:

• The speak() method from Dog is called because it overrides the one from Animal.
• The walk() method is inherited from Mammal, and hence when dog.walk() is called, it executes the method from Mammal. This demonstrates how MRO works in multiple inheritance to resolve which method is executed.

Dog barks
Mammal walks on land

3. Method Overriding in Multilevel Inheritance

In multilevel inheritance, a subclass inherits from a parent class, which itself inherits from another class. Overriding can occur at any level, allowing subclasses to redefine methods from both direct and indirect ancestors. Python resolves the method call using the method resolution order (MRO), ensuring the most specific implementation is executed.

Code Example:

class Animal:
    def speak(self):
        print("Animal makes a sound")

class Dog(Animal):
    def speak(self):
        print("Dog barks")

class Puppy(Dog):
    def speak(self):
        print("Puppy whines")

# Creating an instance of Puppy
puppy = Puppy()
puppy.speak()  # Calls the overridden method in Puppy

Explanation:

• The Puppy class inherits from Dog, which in turn inherits from Animal.
• The speak() method is overridden in Puppy, and this version is called when puppy.speak() is executed.
• The method from Dog and Animal is ignored as the Puppy class provides its own speak() method.

Output: Although both Dog and Animal override the speak() method, the Puppy class provides its own implementation. As a result, calling puppy.speak() invokes the method defined in Puppy.

Puppy whines

This demonstrates that in multilevel inheritance, the most derived class's method takes precedence due to Python’s MRO.

4. Method Overriding in Hierarchical Inheritance

In hierarchical inheritance, multiple subclasses inherit from a single parent class. Each subclass can override parent methods to implement class-specific behavior. While the parent defines shared functionality, overriding allows each subclass to customize behavior independently.

Code Example:

class Animal:
    def speak(self):
        print("Animal makes a sound")

class Dog(Animal):
    def speak(self):
        print("Dog barks")

class Cat(Animal):
    def speak(self):
        print("Cat meows")

# Creating instances of Dog and Cat
dog = Dog()
cat = Cat()

dog.speak()  # Calls the method in Dog
cat.speak()  # Calls the method in Cat

Code Explanation:

• Both Dog and Cat inherit from Animal, but they each override the speak() method.
• When dog.speak() is called, it invokes the speak() method from Dog, and when cat.speak() is called, it invokes the speak() method from Cat.
• Python determines the method to invoke based on the subclass instance at runtime.

Output: The speak() method from Dog is executed when called on a Dog object, and similarly, the speak() method from Cat is executed when called on a Cat object. 

Dog barks
Cat meows

This demonstrates how hierarchical inheritance allows each subclass to provide its own specific method implementation while inheriting common functionality from the parent class.

5. Method Overriding in Hybrid Inheritance

Hybrid inheritance combines multiple inheritance patterns, such as multiple, multilevel, and hierarchical inheritance, into a single class hierarchy. If multiple base classes define the same method, Python uses Method Resolution Order (MRO) to resolve conflicts.

MRO follows the C3 linearization algorithm to determine the method lookup path. This ensures correct method execution in complex class structures.

Code Example:

class Mammal(Animal):
    def walk(self):
        print("Mammal walks on land")

class Bird(Animal):
    def fly(self):
        print("Bird flies")

class Bat(Mammal, Bird):
    def speak(self):
        print("Bat screeches")

# Creating an instance of Bat
bat = Bat()
bat.speak()  # Calls the overridden method in Bat
bat.walk()   # Calls the method from Mammal
bat.fly()    # Calls the method from Bird

Code Explanation:

• Bat inherits from both Mammal and Bird, and both of those inherit from Animal.
• Bat overrides the speak() method, but inherits the walk() method from Mammal and the fly() method from Bird.
• Python's MRO ensures that the correct method is executed based on the inheritance order.

Output: The speak() method from Bat is executed because it overrides the one in Animal. The walk() method comes from Mammal, and the fly() method comes from Bird.

Bat screeches
Mammal walks on land
Bird flies

This demonstrates how hybrid inheritance works in Python, allowing for the combination of different inheritance types while ensuring method resolution remains clear and consistent.

Also Read: Inheritance in Python | Python Inheritance [With Example]

Let’s now explore how method overloading compares to method overriding in Python, and why the two concepts behave so differently in practice.

Method Overloading Vs Method Overriding in Python: Explained

Python treats method overriding as a native object-oriented programming feature, while method overloading requires creative workarounds due to the language’s dynamic nature. This comparison highlights how each behaves in Python's runtime model, inheritance structure, and method resolution.

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Also Read: Career Opportunities in Python: Everything You Need To Know [2025]

Let’s look at how method overriding in Python contributes to solving practical software design challenges through maintainable and scalable solutions.

Key Benefits of Method Overriding in Practical Applications

Method overriding in Python is not just a syntactic feature; it enables clean, modular designs customized to specific behaviors. In practical systems, it drives flexibility, reusability, and maintainability across diverse application domains.

Here are a few key benefits of method overriding in Python that demonstrate its practical value in building scalable and adaptable Python applications.

1. Enables Runtime Polymorphism

Method overriding in Python enables runtime decision-making about which method to execute. The method invoked depends on the actual object type rather than the reference type, a concept known as dynamic dispatch.

Use Case:  In GUI frameworks (e.g., Tkinter, PyQt), base widget classes like Widget may define a generic render() method, which is overridden by subclasses (Button, Label, Checkbox) to provide component-specific rendering logic.

2. Promotes Code Reuse with Customization

Overriding lets subclasses reuse the structure and interface of parent classes while replacing only the parts of logic that need to change.

Use Case: In web development frameworks like Django, base View classes provide a default get() or post() method, and developers override these to implement request-specific logic without rewriting the entire view mechanism.

3. Supports Open/Closed Principle (SOLID)

Method overriding in Python allows classes to be open for extension (via subclassing and overriding) but closed for modification, promoting safer and more maintainable code evolution.

Use Case: When implementing payment gateways, a base PaymentProcessor class can be extended via subclasses like StripeProcessor, PayPalProcessor, which override a process_payment() method without altering the base implementation.

4. Enables Framework Extensibility and Hook Mechanisms

Overriding is the foundation for hook methods or extension points in frameworks, where users can override predefined methods to inject custom behavior at specific lifecycle stages.

Use Case: In Flask, developers can subclass Flask or related base classes to override lifecycle hooks like before_request() or after_request() to add custom authentication, logging, or request tracking.

5. Simplifies Testing and Mocking

Overriding methods in test-specific subclasses or mocks allows controlled behavior injection for isolated unit testing.

Use Case: In unit tests, developers often override methods of real services (like Database.fetch_data()) with mocks or stubs to simulate specific behavior or failure conditions without touching the actual implementation.

6. Supports Plug-in Architectures

Override-based design allows plug-in components to implement common interfaces and inject custom logic via overridden methods.

Use Case: In ML pipelines or ETL systems, base classes like Transformer or Processor may define methods like transform() or clean(), which are overridden in each plug-in to handle different file types or processing steps.

Here’s a table highlighting how each benefit of method overriding in Python contributes to extensibility, maintainability, and modularity in practical Python applications.

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Also Read: Python Challenges for Beginners

Let’s explore how upGrad can help you advance your Python skills by applying method overriding in practical projects through structured learning and expert mentorship.

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Method overriding allows subclasses to redefine methods inherited from parent classes, enabling runtime polymorphism. It works through dynamic dispatch, where the method executed depends on the object’s actual type at runtime. This makes method overriding essential for writing reusable and extensible code in practical Python applications.

As you strengthen your understanding of OOP concepts like method overriding, applying them in structured, project-based settings is essential. That’s where upGrad comes in, with hands-on courses and expert guidance, it helps you build job-ready expertise.

• Object Oriented Analysis and Design for Beginners
• Core Java Basics
• Java Object-oriented Programming

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References:
https://www.actian.com/glossary/python
https://www.pickl.ai/blog/method-overriding-method-overloading-in-python/