Multiline Comment in Python

Programming is like communication, where each line uttered is a part of the story. At times it is necessary to interject with what is going on by writing side remarks in the script. In Python, these notes are called comments. But what happens when a single line isn’t enough to convey your thoughts? That’s where multiline comments come in! This guide will walk you through everything you need to know about multiline comments in Python, complete with examples, definitions, and practical tips.

Learning Objectives

• Understand the purpose and use of comments in Python.
• Learn how to create multiline comments in Python using different techniques.
• Recognize the differences between multiline comments and docstrings.
• Explore examples to implement multiline comments effectively in Python scripts.

Comments are lines in your code that the Python interpreter ignores during execution. They serve as notes for programmers to explain code functionality, logic, or provide additional context.

Why Use Comments?

• Improves readability: Makes your code easier to understand.
• Facilitates collaboration: Helps others quickly grasp the intent of your code.
• Assists debugging: Offers context for why certain approaches were taken.

Types of Comments in Python

• Single-Line Comments: Start with the # symbol and span a single line.
• Multiline Comments: Extend across multiple lines and are useful for lengthy explanations.

A multiline comment in Python is a commenting system used to write comment on multiple lines of code to explain or give details about algorithms, or even use in the process of manipulating code during debugging.

However, like most languages Python does not have a specific comment symbol for block comments like /* */ of Java for example. Instead, Python programmers use:

• Consecutive single-line comments.
• Multi-line strings (enclosed in triple quotes) as a workaround.

We will explore methods below to write multiline comments in Python:

Using Consecutive Single-Line Comments (#)

The most common way to write multiline comments is to use the hash symbol (#) at the beginning of each line.

Example:

# This function calculates the factorial of a number.
# It takes an integer input and returns the factorial.
def factorial(n):
    if n == 0:
        return 1
    return n * factorial(n - 1)

Explanation: Each line of the comment begins with #. This approach is explicit and widely used.

Using Multi-Line Strings (''' or """)

Python’s triple quotes, used for string literals, can also serve as multiline comments. However, these are not true comments; Python treats them as string literals, ignores them during execution, and does not assign them to a variable.

Example:

'''
This is an example of a multiline comment.
It spans across multiple lines
and explains the logic of the code below.
'''
def add_numbers(a, b):
    return a + b

Explanation: The text inside the triple quotes is treated as a string literal but ignored by Python if not assigned to a variable.

Temporarily Commenting Out Code Blocks

Multiline comments are often used to disable large blocks of code during debugging or testing.

Example:

# Uncomment the block below to test the function.
# def test_function():
#     print("This is a test.")

Explanation: Each line of the code block is prefixed with # to prevent execution. This technique is practical during iterative development.

Below table shows the key differences between multiline comments and docstrings for your better undertstanding:

When to Use

• Use multiline comments for internal notes that help developers understand the logic behind the code.
• Use docstrings to describe what a module, class, or function does and how to use it.

Let us understand the best practices for writing multiline comments in Python.

• Keep Comments Relevant: Make sure the comments help and explain why the code has been written, not what it is doing.
• Avoid Over-Commenting: Very often, comments may confuse and overpopulate the code. Aim for clarity and brevity.
• Use Docstrings for Documentation: For functions, classes and modules, use docstrings instead of multiline comments for documenting your application.
• Maintain Consistency: Make sure everyone comments code with multiline comments in the same way throughout the codebase.
• Update Comments: Regularly update comments to reflect code changes.

Below are the examples of where we can use multiline comments:

Example1: Documenting a Complex Algorithm

# This function implements the binary search algorithm.
# It returns the index of the target element if found.
# If the target is not found, it returns -1.
def binary_search(arr, target):
    left, right = 0, len(arr) - 1
    while left <= right:
        mid = (left + right) // 2
        if arr[mid] == target:
            return mid
        elif arr[mid] < target:
            left = mid + 1
        else:
            right = mid - 1
    return -1

Example2: Providing Context for an Entire Module

'''
This module contains utility functions for data processing.
Functions included:
- clean_data(): Cleans the raw dataset.
- transform_data(): Transforms data into the desired format.
- visualize_data(): Creates visual representations of the dataset.
'''
def clean_data(data):
    # Implementation here
    pass

Conclusion

Python multiline comments are a very useful resource to help make your code more comprehensible and sustainable. No matter whether you put # symbols one after another or use triple quotes, the purpose is to make the comments you put informative enough in the context of the code you put.

Key Takeaways

• Multiline comments enhance code readability and maintainability.
• Use consecutive
• Triple quotes can be used but are better suited for documentation.
• Keep your comments concise, relevant, and updated.

Frequently Asked Questions

My name is Ayushi Trivedi. I am a B. Tech graduate. I have 3 years of experience working as an educator and content editor. I have worked with various python libraries, like numpy, pandas, seaborn, matplotlib, scikit, imblearn, linear regression and many more. I am also an author. My first book named #turning25 has been published and is available on amazon and flipkart. Here, I am technical content editor at Analytics Vidhya. I feel proud and happy to be AVian. I have a great team to work with. I love building the bridge between the technology and the learner.