Why You Should Rethink How You Use Python Classes

Discover how overusing classes can lead to bloated, rigid code — and why embracing Pythonic alternatives can make your design cleaner, faster, and easier to maintain.

“Just because you can use classes doesn’t mean you should.”
 — Every experienced Python developer ever

Python is a multi-paradigm language. You can write clean, functional-style code, imperative scripts, or full-blown object-oriented architectures — and they’ll all work.

But here’s the problem: too many developers reach for classes out of habit, not necessity.

It’s time to rethink how (and when) we use classes in Python. Because in many cases, they might be doing more harm than good.

Class Overuse: A Quiet Python Anti-Pattern

Walk into a junior Python codebase and you’ll find something like this:

class Calculator: 
    def add(self, a, b): 
        return a + b

Why is this a class?

It doesn’t manage state. It doesn’t benefit from inheritance. It’s just a namespace wrapped in boilerplate. The better approach?

def add(a, b): 
    return a + b

Simple. Pythonic. Readable.

When Classes Make Sense

Let’s be clear: classes aren’t the enemy. They’re extremely powerful when used right.

Use classes when:

• You need to encapsulate state.
• You need to extend behavior via inheritance or composition.
• You’re modeling real-world objects in a domain.
• You’re building a library or API that benefits from structured interfaces.

Here’s a good example of meaningful class use:

class BankAccount: 
    def __init__(self, owner, balance=0): 
        self.owner = owner 
        self.balance = balance 
 
    def deposit(self, amount): 
        self.balance += amount 
 
    def withdraw(self, amount): 
        self.balance -= amount

Here, the class encapsulates state (balance) and behavior (deposit, withdraw). This is a class with purpose.

What to Use Instead of Classes

Here are some common cases where you probably don’t need a class:

1. Data-Only Structures → Use dataclasses

Instead of this:

class Person: 
    def __init__(self, name, age): 
        self.name = name 
        self.age = age

Use this:

from dataclasses import dataclass 
 
@dataclass 
class Person: 
    name: str 
    age: int

You get less boilerplate, automatic __repr__, __eq__, and even __hash__ if needed.

2. Grouping Functions → Use Modules

Instead of:

class FileUtils: 
    def read_file(self, path): 
        ... 
 
    def write_file(self, path, content): 
        ...

Just use a plain module file_utils.py:

def read_file(path): 
    ... 
 
def write_file(path, content): 
    ...

Modules are already namespaces. No need to add another layer.

3. One-Off State Containers → Use namedtuple or dataclass

For immutable data, Python has your back:

from collections import namedtuple 
 
Point = namedtuple('Point', ['x', 'y']) 
p = Point(1, 2)

Or use @dataclass(frozen=True) for a modern touch.

Why Do Developers Overuse Classes?

Several reasons:

1. Coming from Java or C++ backgrounds. These languages force everything into classes.
2. Taught that “OOP is good” in school. But in Python, it’s not the only path.
3. Mistakenly think functions = procedural, classes = professional. Not true.

Python doesn’t punish you for being concise and expressive. Embrace that freedom.

Guidelines to Follow

Here’s a quick checklist to decide if you really need a class:

| Question                                            | If "No", Consider Not Using a Class | 
| --------------------------------------------------- | ----------------------------------- | 
| Is there internal state that changes over time?     | ❌                                   | 
| Do I need inheritance or polymorphism?              | ❌                                   | 
| Am I modeling a complex entity or concept?          | ❌                                   | 
| Will this be reused as a public API or interface?   | ❌                                   | 
| Do I need special methods like `__str__`, `__eq__`? | ❌ (Use `@dataclass`)                |

Final Thoughts

Python gives you the power to choose the right tool for the job — don’t chain yourself to one paradigm. You don’t need to wrap everything in a class to be a “real” developer. In fact, the best Python code is often the simplest.

So the next time you catch yourself typing class Foo:, pause and ask:
“Do I really need this class?”

More often than not, the answer will surprise you.

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