Understand the Key Difference Between Function and Method in Python!

Although functions and methods may appear similar, they both perform specific tasks when called, they serve different purposes in Python. Functions are independent blocks of code designed to perform a specific task, while methods are functions that are associated with objects and classes, making them key components of object-oriented programming (OOP).

In this blog, you'll explore the key difference between function and method in Python. Learning these concepts will help you write cleaner code, follow best practices, and strengthen your object-oriented programming skills.

Difference Between Function and Method in Python

In Python, both functions and methods are used to encapsulate reusable blocks of code, but they serve distinct purposes and follow different usage patterns. Functions are typically used for general-purpose tasks and operate independently of any object, making them ideal for procedural or functional programming styles. 

Methods, however, are functions defined within classes and are tightly bound to the objects they belong to. They are essential in object-oriented programming (OOP), as they enable objects to exhibit behaviors and interact with their own data.

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The following table highlights the key difference between function and method in python across various aspects of Python programming.

Also Read: Is Python Object-Oriented? Exploring Object-Oriented Programming in Python

After discussing the difference between function and method, let’s examine the scenarios where functions shine and are the most effective choice in Python development.

When to Use Functions?

Functions are perfect for tasks that are independent of any object. They promote modularity and reusability, making your code easier to maintain and understand. Functions are especially useful in scenarios where you need to perform specific operations or process data without interacting with an object's state.

For example, a function to sort a list or calculate the square root of a number can work without needing to instantiate any object. These functions simply take inputs and return an output, making them ideal for tasks that don’t require an object’s data.

Consider the following example in a data processing script:

def clean_data(data):
    # Remove unwanted characters or fix data
    return cleaned_data

def sort_data(data):
    # Sort the data in ascending order
    return sorted_data

def summarize_data(data):
    # Summarize the data, e.g., return the mean
    return summary

In this case, each function is independent and can be reused across different parts of your code, improving both readability and maintainability.

Also Read: Built in Functions in Python: Explained with Examples

When you need to keep your code simple and modular, functions are the best choice but methods are crucial for operations linked to an object's state. Let’s take a closer look at when to use methods.

When to Use Methods?

Methods are functions tied to the state of objects, making them essential for object-oriented programming (OOP). They allow you to interact with an object’s attributes, enabling more modular and structured code. Here's why you should consider using methods:

Example 1: Bank Account Class

Consider a BankAccount class. Here, methods like:

• deposit()
• withdraw()
• check_balance()

These methods allow you to manipulate and access the object’s state, such as the account balance, directly. Each method is intimately connected to the object’s data, ensuring that your logic remains object-centric.

Example 2: Student Record Management

In a StudentRecord system, methods like:

• add_student()
• remove_student()

Let you manage student data. For instance, add_student() could append student details to a list, while remove_student() could delete a student's record. These methods interact with the internal data of the object, keeping your code well-organized.

Why Are Methods Crucial?

• Modular & Structured Code: Methods allow objects to manage their own behavior, keeping everything organized.
• Encapsulation: Methods ensure that your logic is tightly coupled with the object’s state, leading to cleaner, easier-to-maintain code.

Types of Methods in Python:

• Instance Methods: Operate on specific object instances and can access the object’s data via self.
• Class Methods: Operate on the class itself and are defined with @classmethod.
• Static Methods: Don’t rely on object or class data and are defined with @staticmethod.

Methods are the backbone of object-oriented programming, ensuring that your objects handle their own data and behaviors. Use them to create well-organized, modular, and reusable code.

But understanding how functions and methods differ isn't enough. It’s essential to see how they impact your code structure.

Also read: 16+ Essential Python String Methods You Should Know (With Examples)

After understanding when to use methods in python, you’re ready to advance your Python skills. Take the next step and become a Python expert with upGrad!

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The difference between function and method in Python allows you to write more efficient, organized code. Functions are great for standalone tasks, while methods are key to interacting with and modifying the state of objects in object-oriented programming. Learning these concepts helps you structure your Python projects more effectively.

To further sharpen your skills and apply these concepts in real-world projects, upGrad’s specialized courses are the ideal choice. With expert-led guidance and practical learning, these courses will help you close any skill gaps and accelerate your career in tech.

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References:
https://www.python.org/downloads/    
https://realpython.com/python-news-april-2025/