Python Comments FAQ: Everything You Need to Know (Beginner to Advanced)

Introduction: Python Comments FAQ

This Python Comments FAQ guide is designed as the final companion lesson for
Chapter 3 – Python Comments and Code Documentation Basics on PyCoderHub.

If you’ve completed the chapter lessons but still feel confusion around how Python comments work—when to use single-line vs multi-line comments, how docstrings differ from regular comments, or what best practices and common mistakes to avoid are—this guide is built for you. The questions below are drawn from common learner doubts and real-world coding scenarios, carefully grouped into clear categories.

Each answer is written in a medium-length, practical, and beginner-friendly style, focusing on how Python behaves in real code, with examples included only when they genuinely improve understanding.

Category 1: Python Comments – Basics

Q – What are comments in Python?

A: Comments are lines in your Python code that don’t execute. They exist solely to explain your code, share reasoning, or leave helpful notes for other developers. Python ignores comments at runtime, so they don’t affect performance or behavior. Use them to make your code more readable and maintainable.

Q – How do I write a single-line comment in Python?

A: Single-line comments begin with the # symbol. Everything after # on that line is ignored by Python.

# This is a single-line comment
x = 10  # This is an inline comment explaining the variable

Single-line comments are perfect for quick notes or explaining small pieces of logic.

Q – Does Python support multi-line comments?

A: Python doesn’t have an official multi-line comment syntax like some other languages. Instead, you can use:

1. Multiple single-line comments (recommended by PEP 8):

# This is a block comment
# explaining multiple lines of code
# in detail

2. Multiline strings as pseudo-comments:

"""
This is a multiline string
used as a comment.
"""

However, PEP 8 recommends using multiple # lines for readability and consistency.

Q – What is the difference between a comment and a docstring?

A: The key difference lies in purpose and accessibility:

• Comments: Explain how code works internally (implementation details). Ignored by Python and not accessible at runtime.
• Docstrings: Document modules, classes, or functions, describing what they do. Enclosed in triple quotes ("""...""") and stored in the object’s __doc__ attribute, making them accessible via help() or tools like Pydoc.

Category 2: Types of Python Comments

Q – What are inline comments?

A: Inline comments are comments written on the same line as a statement, usually after the code itself. They are placed after at least two spaces and start with the # symbol.

initial_counter_value = 5  # Set initial counter value

Inline comments should be used sparingly and only when the intent of the code isn’t immediately clear. Overusing them can reduce readability rather than improve it.

Q – What are block comments?

A: Block comments are multiple single-line comments grouped together to explain a larger section of code. Each line starts with #, and the comments are typically written above the related code block.

# Step 1: Read the file
# Step 2: Process the data
# Step 3: Output the results

Block comments are ideal for describing high-level logic, workflows, or complex operations that span multiple lines of code.

Q – What are pseudo multi-line comments?

A: Pseudo multi-line comments use unassigned triple-quoted strings (""" ... """) to span multiple lines. Although they look like comments, Python actually treats them as string literals, not true comments.

"""
This is a pseudo multi-line comment.
Python creates a string object here,
but it is not assigned to any variable.
"""

While this approach works, it’s not recommended for commenting. According to PEP 8, you should prefer block comments using # for clarity, consistency, and better tool support.

Category 3: Best Practices & Style

Q – What does PEP 8 say about writing comments?

A: According to PEP 8, well-written comments should follow these core principles:

• Be written as complete, meaningful sentences
• Start with a capital letter (unless the comment begins with code or an identifier)
• Focus on explaining why something is done, not what the code already shows
• Stay updated whenever the related code changes
• Avoid obvious, redundant, or restated code logic

Following these guidelines significantly improves code readability, maintainability, and long-term clarity.

Q – Should comments explain “what the code does”?

A: Preferably, no. Clean, well-named code should already communicate what it does.
Comments are most valuable when they explain reasoning, intent, or context that isn’t obvious from the code alone.

Weak comment:

value = value + 1  # adds 1 to value

Good comment:

value = value + 1  # adds 1 to value

The second comment adds insight that the code itself cannot express.

Q – How long should comments be?

A: Comments should be concise but informative.
A simple rule to follow: one short sentence that clearly explains the purpose or reasoning behind the code.

Long explanations usually signal that the code itself needs better structure or clearer naming.

Q – Why should I use comments if “self-documenting code” is better?

A: Writing self-documenting code is the goal—but it doesn’t eliminate the need for comments.

Well-named variables and functions explain what the code does.
Comments are still essential for explaining why a decision was made or what context influenced it.

Avoid obvious comments:

counter_value += 1  # Increment counter_value

Prefer intent-based comments:

counter_value += 1  # Apply 1ms offset to prevent race condition

Good comments complement clean code by capturing reasoning, constraints, and trade-offs that code alone cannot express.

Category 4: TODO / FIXME / NOTE / HACK Tags

Que – What is a TODO comment?

A: A TODO comment marks something that needs future work, improvement, or refactoring. It helps developers track pending tasks directly in the code.

# TODO: Replace hardcoded paths with environment variables

TODO comments are great for planning enhancements and ensuring unfinished work doesn’t get forgotten.

Q – What is a FIXME comment?

A: A FIXME comment highlights a known bug or broken behavior that must be corrected.

# FIXME: This fails on Python 3.12; update regex.

Use FIXME to clearly flag problematic code that requires immediate or high-priority attention.

Q – What is a HACK comment?

A: A HACK comment signals a temporary or non-ideal workaround used to make something function.

# HACK: Using sleep() to wait for server startup; replace with proper health check.

It warns maintainers that the solution is fragile, technical debt exists, and a cleaner approach should replace it.

Q – What is a NOTE comment?

A: A NOTE comment is used to highlight important context, constraints, or special behavior that may not be obvious from the code alone.

# NOTE: The API rate limits to 100 requests per minute.

NOTE comments are useful for clarifying assumptions, limitations, or usage details.

Category 5: Comments in Large and Open-Source Projects

Q – How should comments be handled in large codebases?

A: Large projects benefit greatly from disciplined and consistent commenting. Best practices include:

• A consistent commenting style across the entire project
• Clear and descriptive block comments for complex sections
• Proper explanation of non-obvious or critical logic
• Use of automated documentation tools
• Standardized tracking for TODO and FIXME comments

Strong commenting discipline directly improves long-term maintainability and collaboration.

Q – How should comments be written in open-source projects?

A: Open-source comments should be:

• Clear and beginner-friendly
• Respectful and professional
• Written with diverse contributors in mind
• Aligned with the project’s community guidelines

Good comments significantly reduce onboarding time and help new contributors understand the codebase faster.

Category 6: Tools & Automation

Q – Can comments be used for generating documentation?

A: Regular comments cannot. However, docstrings can be parsed by documentation tools such as:

• Sphinx
• MkDocs
• pdoc
• pydoc

Some frameworks (like Django or FastAPI) support special docstring tags, but standard comments are not available at runtime and cannot be extracted for documentation.

Q – Are there tools that help check comment quality?

A: Yes. Static analysis tools can flag issues related to comments and documentation:

• pylint
• flake8
• ruff

These tools help detect missing docstrings, formatting problems, and poor commenting practices.

Q – Can I use a shortcut to comment out multiple lines in my IDE?

A: Yes. While Python syntax requires a # on each line, modern IDEs and editors make this easy.

Most editors support a toggle comment shortcut:

• Windows / Linux: Ctrl + /
• macOS: Cmd + /

This shortcut automatically adds or removes # at the start of each selected line.
It’s especially useful for temporary debugging, but commented-out code should not remain permanently.

Category 7: Behavior & Execution

Q – Do comments affect performance?

A: No. Comments are completely ignored by the Python interpreter and have zero impact on runtime speed or memory usage.

Q – Can comments be accessed during program execution?

A: No. Unlike docstrings, comments are removed during compilation and cannot be accessed at runtime.

# This comment cannot be accessed
def calculate_total_price():
    """Return the total price including tax."""
    pass

print(calculate_total_price.__doc__)

Category 8: Common Mistakes

Q – What is a smelly comment?

A: A smelly comment indicates poor commenting practices, such as:

• Being outdated
• Being overly long
• Explaining obvious logic
• Simply repeating the code

Smelly comments reduce clarity and should be removed or rewritten.

Q – What are W.E.T. comments?

A: W.E.T. stands for Write Everything Twice. These comments repeat exactly what the code already shows, adding no value.

maximum_limit = 10  # Set maximum_limit to 10

This comment is unnecessary and harder to maintain over time.

Q – Why should rude or sarcastic comments be avoided?

A: Rude comments create toxic environments and confuse or discourage other developers. Codebases—especially open-source ones—should remain professional, inclusive, and welcoming.

Q – What are common mistakes developers make with comments?

A: Some of the most frequent commenting mistakes include:

• Writing comments instead of using clear variable or function names
• Commenting obvious operations
• Leaving outdated or misleading comments
• Writing long explanations instead of refactoring into smaller functions
• Using triple-quoted strings (""" ... """) for regular comments
• Adding type details in comments instead of using Python type hints

Poor comments reduce clarity. When in doubt, improve the code first, then add comments only where reasoning still isn’t obvious.

Q – Can I put comments inside data structures or expressions?

A: No. Comments must appear on their own line or at the end of a statement.

Invalid:

result = (first_value +
          # This adds second_value
          second_value)

Valid:

# Add second_value to first_value
result = first_value + second_value

Category 9: Advanced Concepts

Q – Can comments be used to disable code?

A: Yes. Developers often comment out lines during debugging:

# print(processed_data)

This should be temporary, not a permanent solution.

Q – Are comments stored in bytecode?

A: No. Python strips comments before compiling code into .pyc bytecode files.

Q – Can comments contain Unicode or emojis?

A: Yes, Python 3 supports Unicode in source files. However, emojis should be avoided in production code, as they may break tooling or formatting.

Q – Can I nest comments?

A: No. Python doesn’t support nested comments. Everything after the first # is treated as a comment.

# This is a # valid comment

Category 10: Practical Questions

Q – When should I avoid commenting?

A: Avoid comments when:

• The code is already self-explanatory
• The comment repeats the code
• The comment is likely to become outdated quickly

Prefer clear naming and clean structure instead.

Q – Should I comment every function, class, or module?

A: No—but you should be intentional.

• Public functions, classes, and modules → Use docstrings
• Private or simple helpers → Comment only if the logic isn’t obvious
• Complex logic or business rules → Add comments explaining why

If a function needs excessive commenting, it’s often a sign that it should be simplified or refactored.

Q – Should I comment every function?

A: Not necessarily.

• Use docstrings for public functions, classes, and modules
• Use comments only when extra explanation is truly needed

Q – How often should comments be updated?

A: Whenever the code changes.
Outdated comments are worse than no comments because they actively mislead developers.

Q – Is deleting a bad comment better than keeping it?

A: Absolutely. If a comment no longer reflects reality, delete or rewrite it immediately. Code evolves—comments must evolve with it.

Q – When should I add comments to my code?

A: Add comments when you need to:

• Explain why a decision was made
• Clarify complex algorithms or business logic
• Provide context that code alone cannot show
• Mark future work using TODO / FIXME
• Warn about side effects or pitfalls

Avoid explaining obvious operations—good code should explain what, comments should explain why.

Q – What makes a good comment?

A: A good comment is:

• Clear and concise
• Accurate and honest
• Helpful to other developers and your future self
• Focused on reasoning, not repetition
• Consistent with the rest of the codebase

Good comments complement code instead of cluttering it.

Q – My comment is long. How should I format it?

A: Use multiple single-line comments and keep line length reasonable (typically 79–99 characters, per PEP 8).

# This function uses a complex regularization technique to prevent
# overfitting in the model. The chosen algorithm performs better
# with sparse datasets than the available alternatives.
# See JIRA ticket DATA-42 for detailed discussion.

Final Thoughts

This Python Comments FAQ is designed to clear confusion, reinforce best practices, and help you build the right mindset around why comments matter—not just how to write them. By completing Chapter 3, you now understand comments as tools for clarity, communication, and long-term maintainability, rather than mere explanations of obvious code.

With this foundation, you’re ready to write Python code that speaks for itself and supports future readers through thoughtful comments and meaningful docstrings. As you move forward into more complex programs, clean commenting will play a crucial role in collaboration, debugging, and professional-quality code.

Happy coding with PyCoderHub.