What 10 Years of Writing Python Taught Me About Writing Less Code

Less is more. Especially when it comes to Python.

What 10 Years of Writing Python Taught Me About Writing Less Code

After a decade of solving real-world problems with Python, I’ve learned that writing less code often leads to better software. Here’s why — and how you can do it too.

I Used to Think More Code Meant More Value

I still remember my early Python scripts. Verbose. Manual. Explicit to a fault. I thought the more lines I wrote, the more I was contributing. After all, isn’t writing code what programmers do?

Ten years later, I know better.

Now, my default approach is: write as little code as possible to solve the problem clearly. The less I write, the less I maintain. The fewer bugs I introduce. The more elegant the result.

This mindset shift didn’t happen overnight. It was earned through late-night debugging, endless refactoring, and painful lessons learned on real projects.

In this article, I’ll share the 7 most important lessons I’ve learned about writing less — and better — Python code.

1. Embrace Pythonic Idioms Early

Early on, I avoided Python-specific idioms because I misunderstood them as “clever hacks.” But Python’s beauty lies in its clarity through idiom.

Instead of:

names = [] 
for person in people: 
    names.append(person.name)

Do:

names = [p.name for p in people]

Or instead of:

if status == True: 
    ...

Do:

if status: 
    ...

Pythonic doesn’t mean obscure — it means readable to other Pythonistas.

Learn to read other people’s idiomatic Python and absorb the patterns that make the language feel elegant.

2. The Zen of Python Is a Cheat Sheet

Run this in your terminal:

python -m this

You’ll get The Zen of Python — a set of guiding principles by Tim Peters. It’s poetic, sure, but incredibly practical.

Two lines that changed how I write:

• “Simple is better than complex.”
• “There should be one — and preferably only one — obvious way to do it.”

Whenever I’m writing something that feels convoluted, I ask: Is there a simpler, more obvious way to express this? Often, the answer is yes.

Revisit The Zen of Python regularly. Let it guide your refactors.

3. You Don’t Need a Class for Everything

I used to wrap every idea in a class. Even simple things.

class TemperatureConverter: 
    def to_celsius(self, f): 
        return (f - 32) * 5 / 9

Overkill.

Here’s the better version:

def to_celsius(f): 
    return (f - 32) * 5 / 9

Unless you’re modeling behavior with state, functions are often enough. Python’s functional capabilities (lambdas, partials, higher-order functions) are powerful and underused.

Reach for functions first. Only introduce classes when you need them.

4. The Standard Library Is Underrated

After a decade with Python, I still find gems in the standard library that replace 50 lines of custom code.

Some of my favorites:

• collections.Counter – Count anything in a single line.
• itertools.groupby – Group sorted data efficiently.
• pathlib – Treat paths as objects (and stop using string concatenation!).
• dataclasses – Lightweight, readable alternatives to full-blown classes.
• functools.lru_cache – Add caching with a decorator.

Before reaching for a third-party package, I ask: Can the standard library solve this?

Master the standard library — it’s like having a toolbox full of power tools.

5. Avoid Over-Engineering with Premature Abstractions

One of my early mistakes: generalizing too early. I’d write frameworks for problems that barely existed yet.

Here’s a painful truth: Most code doesn’t need to be reusable. It needs to be clear.

Abstractions add weight. They should be earned, not preemptively added.

The best abstraction often comes after you’ve duplicated code once or twice and clearly see the pattern.

Delay abstractions until the duplication is painful. Start concrete, refactor later.

6. Use Libraries That Let You Write Less

Some libraries are built to let you do more with less. Over the years, I’ve come to love these:

• Typer for CLIs — build command-line apps with almost zero boilerplate.
• Pydantic for data validation — parse & validate data with clarity.
• Rich for beautiful terminal output — stop printing ugly logs
• SQLModel or Peewee — ORM without the weight of Django.

These tools don’t just make code shorter — they make it more expressive.

Choose tools that reduce boilerplate and align with Pythonic design.

7. Your Future Self Is Your #1 User

Here’s a truth only time teaches: You’ll be the one maintaining your own code months later.

Write for your future self. The version of you who forgot what this function does. Who’s scanning the code at 2 AM. Who’s debugging a production bug under pressure.

That means:

• Use meaningful variable names.
• Add why comments, not what comments.
• Avoid clever tricks that aren’t obvious.

Here’s my favorite principle:

“Code is read more often than it is written.” — Guido van Rossum

Prioritize readability over cleverness. You’ll thank yourself later.

Final Thoughts: Less Code, More Clarity

Writing less code isn’t about being lazy. It’s about being deliberate.

Less code means:

• Fewer bugs
• Easier maintenance
• Faster onboarding for teammates
• Clearer thinking

After ten years with Python, the best compliment I can get isn’t “that’s clever,” but “that’s obvious.”

Let your code whisper, not shout.

If You Take One Thing Away…

Don’t obsess over writing more code. Obsess over writing the right code.

The goal isn’t to be the hero with 1,000 lines — it’s to solve the problem with the least friction.

That’s real mastery.