When it comes to clean, maintainable code, comments5 isn’t just a keywordโitโs a philosophy. Writing understandable code is important, but what truly separates good code from great code is how well you comment it.
In this guide, Iโll walk you through how to write better Python comments using 5 proven best practices. Whether you’re a beginner or a seasoned dev, these tips will help you write code that others can read, understand, and build onโwithout frustration.
๐ What Are Python Comments and Why Are They Important?
Before diving into python comments best practices, letโs quickly cover what comments are and why they matter.
Python comments are lines in your code that are ignored by the Python interpreter but are essential for developers. They explain what the code does, making it easier to understand for others and your future self.
There are mainly two types of comments in Python:
Single-line comments using the # symbol
Multi-line comments using triple quotes (''' or """)
python comments
๐น 1. Use Comments to Explain โWhy,โ Not โWhatโ (Tip #1)
Bad comment:
x = x + 1 # Increment x by 1
Good comment:
x = x + 1 # Adjust for 0-based indexing in the dataset
Why it matters:
Anyone can see x + 1. But explaining why you’re doing it adds context.
๐น 2. Keep Comments Short, Simple, and Clear (Tip #2)
Long paragraphs are hard to read and miss the point. Use short, clear sentences.
Example:
# Check if user is logged in before showing profile
๐น 5. Use Docstrings for Functions and Modules (Tip #5)
Use triple-quoted strings right after function definitions to explain what the function does.
Example:
def calculate_tax(amount):
"""Calculate tax at 15% for the given amount."""
return amount * 0.15
๐ง When to Use Comments in Python
Not every line of code needs a comment. In fact, too many comments can clutter your code and make it harder to read. A good rule of thumb is to comment complex logic, assumptions, or business rules that arenโt obvious at first glance.
When to Use Comments in Python
For example, if you’re using a workaround for a known library bug or writing code based on a client-specific requirement, that deserves a comment. But standard assignments or iterations rarely need one unless theyโre doing something non-intuitive.
๐ Bonus Tip: Use Tools to Enforce Commenting Standards
Use linters like Pylint or Flake8 to detect missing or incorrect comments. Tools like Black (code formatter) can help you write cleaner code that’s easier to comment.
def connect_to_server(url):
"""Connects to a remote server via HTTP."""
if not url.startswith("http"):
raise ValueError("Invalid URL")
# Attempting connection with retry logic to handle network issues
response = make_http_request(url)
return response
This function uses both docstrings and an inline comment to give full clarity. A great example of how to write better Python comments.
Data Science Professional with a strong background in analytical modeling and skill development. Experienced in leveraging a wide array of tools, machine learning techniques, and statistical methods to extract meaningful insights. I have authored blogs and technical articles on data automation, visualization, and real-world machine learning applications.