Clean Code in Python: 7 Rules I Swear By

Here are 7 battle-tested rules I follow to write clean, readable, and maintainable Python code every single time.

Aashish Kumar

24 May 2025 — 3 min read

CLEAN CODE ISN’T OPTIONAL — IT’S ESSENTIAL.

Clean Code in Python: 7 Rules I Swear By

There’s a moment in every developer’s journey when they open an old project and think, “What the hell was I thinking?” Been there. More than once.

Messy code is inevitable when you’re learning — or moving fast. But if there’s one habit that separates great developers from the rest, it’s writing clean, readable, and maintainable code.

Over the years, I’ve picked up a few non-negotiable rules that I now live by when writing Python. These aren’t theoretical best practices — they’re battle-tested habits that have saved me from spaghetti disasters and late-night bug hunts.

Here are the 7 rules I swear by for writing clean Python code.

1. Use Meaningful Names, Always

Bad:

d = {"a": 1, "b": 2}

Better:

user_ages = {"Aashish": 25, "John": 30}

Variable names should explain themselves. If I need to add a comment to clarify a variable name, it’s a sign I should’ve picked a better name.

Think of your future self — or your teammate — trying to understand what d or temp means. Descriptive names reduce mental overhead and make your code self-documenting.

Pro tip: Avoid abbreviations unless they’re universally understood (id, URL, HTML, etc.)

2. Keep Functions Short and Focused

A function should do one thing, and do it well. If it’s hard to name a function because it does multiple things, that’s your cue to split it.

Bad:

def process_data(data): 
    # Cleans, transforms, and saves data

Better:

def clean_data(data): ... 
def transform_data(data): ... 
def save_data(data): ...

Small, focused functions are easier to test, reuse, and debug. It also encourages composability — building bigger things from smaller, reliable pieces.

3. Avoid Magic Numbers and Strings

“Magic” values are hardcoded numbers or strings that pop up in your code without context. They make code cryptic and fragile.

Bad:

if status == 3: 
    send_email()

Better:

EMAIL_STATUS = 3 
 
if status == EMAIL_STATUS: 
    send_email()

Or even better — use Enum when you have multiple status codes. Your future self will thank you.

4. Utilizing Pythonic Idioms

Python has a beautiful, expressive syntax. Use it.

Instead of:

if len(items) == 0: 
    return

Do:

if not items: 
    return

Instead of:

result = [] 
for item in items: 
    result.append(item.upper())

Do:

result = [item.upper() for item in items]

Being Pythonic isn’t about clever tricks — it’s about writing elegant, readable code that speaks the language of Python.

5. Write for Humans, Not the Machine

The computer doesn’t care if your code is messy — it’ll run it anyway. But your teammates do. You do.

Writing clean code is an act of empathy. It’s about making your code readable and predictable for others (and for future you).

So, prioritize clarity over cleverness. Use comments sparingly — ideally only to explain why, not what.

Bad:

# Loop through users and send email 
for user in users: 
    send_email(user)

Better:

for user in users: 
    send_email(user) 
# Sending onboarding email to each user

Even better? Name the function accordingly so you don’t need a comment at all.

6. Follow PEP 8 (Mostly)

PEP 8 is Python’s style guide. It’s not gospel, but following it helps your code feel familiar to other Python devs.

A few key takeaways:

Use 4 spaces per indentation level
Keep line length under 79 characters
Add two blank lines between top-level functions/classes
Use snake_case for functions and variables, CamelCase for classes

Tools like black, flake8, or pylint can help enforce these standards automatically. Let the robots handle the boring parts.

7. Refactor Relentlessly

Clean code isn’t written — it’s rewritten.

Don’t be afraid to revisit and polish your code. That 200-line function that barely works? Chop it up. The tangled class? Break it into smaller ones. It’s a process.

When in doubt, ask yourself:

Can someone else understand this without context?
Can I make this simpler?
Would I be proud to show this in a code review?

Writing clean code isn’t about perfection — it’s about continuous improvement.

Final Thoughts

Clean code is more than just aesthetics. It’s about building software that’s easier to work on, easier to scale, and easier to love. It’s about craft.

And in Python, clean code feels almost poetic — it flows. When done right, it almost reads like prose.

Whether you’re a junior dev or a seasoned engineer, these seven rules are worth revisiting from time to time. Your teammates, your future self, and your sanity will thank you.