Data Science

Mastering Multiline Comments in Python: Enhance Code Clarity

Published: 14th July, 2023

Harshini Bhat

Data Science Consultant at almaBetter

Learn how to add extensive explanations, document code, and improve collaboration. Enhance code clarity and maintainability with multiline comments in Python.

Writing code is like crafting a language of its own, complete with its own grammar and syntax. But even the most skilled developers sometimes struggle to decipher the intricacies of their own or someone else's code. That's where comments come to the rescue, acting as friendly guides in the world of programming. In the realm of Python, comments play a crucial role in making code easier to understand and maintain. While single-line comments are common, there are moments when a few sentences just won't cut it.

That's where multiline comments step in, like unsung heroes, offering a spacious canvas for developers to explain their code, document its nuances, and even temporarily mute sections for debugging. In this article, we'll embark on an enlightening journey to explore the wonders of multiline comments in Python. We'll uncover their purpose, discover what makes them special, and equip you with the knowledge of how to write a multiline comment in Python and the skills to use them effectively. So, get ready to bring your code to life with expressive and informative multiline comments in Python as we dive into the world of Python programming.

What are Multiline Comments?

Definition and purpose of multiline comments:

Multiline comments, also known as block comments, allow developers to include extensive explanations or documentation within their Python code. These comments span multiple lines and are not executed by the interpreter. Their purpose goes beyond simple clarification; they enable developers to provide detailed insights into the code's functionality, document design choices, or temporarily disable portions of the code during debugging.

Differentiating multiline comments from single-line comments:

Unlike single-line comments, which consist of a single line preceded by the "#" symbol, multiline comments require a different syntax. In Python, we enclose multiline comments within triple quotes (""") using either single or double quotes. By convention, triple double quotes (""") are commonly used for multiline comments. These comments can span across several lines and are not limited to a specific length. They serve as a versatile tool for

conveying extensive information within the code, making it easier for developers to understand, maintain, and collaborate on projects.

Multiline comments offer a valuable avenue for developers to provide rich explanations and context within their code, enhancing its readability and facilitating effective collaboration.

How to add Multiline Comments

Adding multiline comments in Python is a straightforward process that involves enclosing the desired text within triple quotes (""") using single or double quotes. Let's explore the steps how to add multiline comment in Python and see some examples.

Syntax for multiline comments using triple quotes ("""):

Multiline comments in Python are created by enclosing the text within triple quotes ("""). You can use either single or double quotes for the triple quotes, depending on your preference or coding style. Here's the basic syntax:

This is a multiline comment.

It can span across multiple lines.

These lines will not be executed as part of the code.


Using single or double quotes for multiline comments:

Both single and double quotes can be used for multiline comments. The choice between them is typically a matter of personal preference or adherence to a specific coding style.

Here are examples of using single and double quotes for multiline comments:


This is a multiline comment using single quotes.

It can span across multiple lines.



This is a multiline comment using double quotes.

It can span across multiple lines.


Examples of adding multiline comments in different scenarios:

Multiline comments are versatile and can be added to various parts of your code. Here are a few examples:

a) Documenting a function:


This function calculates the factorial of a given number.

Input: n (integer)

Output: Factorial of n

def factorial(n):

if n == 0:

return 1


return n * factorial(n - 1)

b) Providing an overview of a module or file:


This module contains utility functions for file handling.

The functions include reading, writing, and manipulating files.


c) Explaining complex logic or algorithms:


This algorithm implements a sorting technique called QuickSort.

It recursively divides the list into sublists, sorts them, and then combines them to obtain a sorted list.


Adding multiline comments allows you to provide detailed explanations and documentation within your Python code. They serve as invaluable tools for making your code more understandable, maintainable, and collaborative.

Learn more with our free resources: Python Tutorial and Python Compiler


Multiline comments in Python offer developers a powerful tool to enhance code clarity, maintainability, and collaboration. By enclosing text within triple quotes ("""), developers can provide extensive explanations, document code intricacies, or temporarily disable code sections during debugging. Whether documenting functions, giving overviews of modules or files, or explaining complex algorithms, multiline comments enable developers to create expressive narratives within their code. By following best practices, such as using clear language, updating comments when necessary, and maintaining a consistent style, developers can harness the potential of multiline comments to create code that is not only functional but also understandable and collaborative. So, embrace the use of multiline comments in your Python codes. We have now learned how to make multiline comments in Python to make it more comprehensible and facilitate effective communication with fellow developers.

If you, too, are interested in learning more about the most versatile language, Python programming, and acquiring a certificate in Data Science, enroll for our Full Stack Data Science program that offers a 100% placement guarantee.

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