Python Multiline Comment: Syntax, Techniques, and Best Practices

Understanding how to write a Python multiline comment is essential for maintaining code clarity, documenting complex sections, and making your projects more readable for others—and for your future self. While Python doesn't have a dedicated syntax for block comments like some other languages, it provides several practical workarounds that developers commonly use.

What Is a Python Multiline Comment?

A multiline comment in Python refers to a block of text intended for explanation or documentation purposes. This comment spans more than one line. Unlike single-line comments, which use the # symbol, multiline comments require either multiple # symbols or a workaround involving triple-quoted strings.

Since Python doesn’t have an official multiline comment syntax, the term typically refers to one of these methods:

• Repeated # symbols on each line
• Triple-quoted strings (''' or """) that are not assigned or executed

Why Use Multiline Comments?

Multiline comments are particularly useful in the following situations:

• Documenting the logic of a function
• Explaining algorithm steps
• Annotating configuration blocks
• Adding notes during debugging or development
• Providing examples or references for future contributors

A Python multiline comment enhances the maintainability of code by providing context that may not be obvious from the code alone.

How to Do a Multiline Comment in Python

There are two primary ways to implement a multiline comment in Python:

1. Using Multiple # Symbols

This is the most direct and widely accepted method:

# This function calculates the average
# of a list of numbers, and returns
# the result rounded to two decimal places.
def average(nums):
    return round(sum(nums) / len(nums), 2)

Each line must begin with a # character. Code editors usually make it easy to add or remove these from selected lines.

2. Using Triple-Quoted Strings

Python allows you to use triple-quoted strings to create multiline strings. These strings are usually used for docstrings, but they can also be used as pseudo-comments if they are not assigned or executed:

'''
This block of text is treated as a string,
but since it's not assigned to any variable,
it is effectively ignored during execution.
'''
print("Hello, world!")

This technique is readable, but it’s worth noting that these strings still exist at runtime unless they appear in places where Python ignores them, such as before a function or module.

Docstrings vs Multiline Comments

Docstrings are triple-quoted strings placed directly below a function, class, or module definition. They are a form of inline documentation and can be accessed using Python’s built-in help() function.

def greet(name):
    """
    Greets the user by name.
    This function demonstrates a docstring.
    """
    return f"Hello, {name}!"

While docstrings look like multiline comments, their intent is different—they document the API rather than comment out logic or provide implementation details.

Choosing the Right Approach

Use multiple # lines when:

• You want clear, non-runtime-impacting comments
• You need to toggle them on/off during development
• You're working with linters that might flag unused strings

Use triple-quoted strings when:

• Adding temporary blocks of explanation
• Working in notebooks or scripts where readability is key
• Commenting out large blocks of code during debugging

Examples of Python Multiline Comments

Example 1: Algorithm Documentation

# Step 1: Sort the list
# Step 2: Remove duplicates
# Step 3: Return the cleaned list
def clean_data(data):
    return list(set(sorted(data)))

Example 2: Using Triple Quotes

'''
Initialize variables for the simulation:
- position: starting point
- velocity: initial speed
'''
position = 0
velocity = 10

Example 3: Temporarily Commenting Out Code

'''
def old_function():
    print("This is deprecated")
'''

This allows developers to retain code for reference while removing it from execution.

Python Multiline Comment Inside Functions

Multiline comments inside functions are useful for describing internal logic.

def calculate_total(price, tax_rate):
    # Apply tax to price
    # Then round to two decimal places
    return round(price * (1 + tax_rate), 2)

Or:

def simulate():
    '''
    Simulate one iteration:
    - Update position
    - Adjust velocity
    - Store result
    '''
    pass

Editor Shortcuts for Multiline Comments

Many modern editors like VS Code, PyCharm, and Sublime Text offer shortcuts:

• VS Code: Ctrl + / or Cmd + /
• PyCharm: Ctrl + / for line, Ctrl + Shift + / for block (Windows)
• Jupyter Notebooks: Ctrl + / to toggle line comments

These shortcuts streamline the process of writing and editing a Python multiline comment.

Best Practices for Multiline Comments

1. Keep comments meaningful: Don’t state the obvious. Write comments that provide insight.
2. Avoid excessive commenting: Trust your code structure and function names to speak for themselves.
3. Update comments with code: Don’t let them become outdated.
4. Use docstrings for public APIs: Reserve docstrings for user-facing documentation.
5. Choose consistency: Use the same style throughout your codebase.

Commenting Large Blocks of Code

Sometimes, you may want to comment out a large block of code for debugging. In these cases, triple-quoted strings or IDE shortcuts are practical.

'''
for i in range(10):
    print(i)
'''

This method helps you isolate and remove functionality without deleting it.

Limitations of Python Multiline Comments

• Triple-quoted strings aren’t truly comments—they are strings that occupy memory if not ignored properly.
• Using them indiscriminately can lead to issues with linters or code analysis tools.
• They can affect the readability of your code when used excessively.

Summary

A Python multiline comment is a powerful way to document, clarify, and manage code behavior. While Python doesn’t have a dedicated multiline comment syntax, the language offers several flexible techniques, including multiple # symbols and triple-quoted strings.

You’ve seen how to do a multiline comment in Python, how each method works, and when to use each style. From quick algorithm annotations to large block explanations, choosing the right commenting approach makes your code more maintainable, understandable, and professional.

As your projects grow, using a consistent commenting strategy—especially for multiline comments—will help both you and your collaborators understand the purpose and intent behind each line of code. Python’s simplicity encourages clear, concise documentation, and mastering these comment techniques is an important step in writing quality Python code.