Why Your Obsession with Code Modularity is Overrated

Let me tell you a secret: your codebase isn’t a Russian nesting doll. Those 47 layers of abstraction you’ve created aren’t making you look smart - they’re making future-you want to cry into their overpriced artisanal coffee. Modularity is like hot sauce: a little enhances the flavor, but drown your burrito in it and you’ll be praying to the porcelain gods at 3 AM.

The Modularity Mirage

We’ve all been there. You start with good intentions:

def calculate_order_total(items):
    return sum(item['price'] * item['quantity'] for item in items)

Then the “best practices” demon whispers: “What if we need multiple pricing strategies? Let’s future-proof this!” Suddenly you’re staring at:

class AbstractPricingStrategy(metaclass=ABCMeta):
    @abstractmethod
    def calculate(self, items: List[ItemProtocol]) -> Decimal:
        pass
class DefaultPricingStrategy(AbstractPricingStrategy):
    def __init__(self, tax_adapter: TaxServiceInterface):
        self._tax_adapter = tax_adapter
    def calculate(self, items) -> Decimal:
        # 42 lines of enterprise-grade pattern matching

Now your simple calculation needs dependency injection, 3 interfaces, and a partridge in a pear tree. Congratulations - you’ve just created framework-driven development!

See that Rube Goldberg machine? That’s the moment your CEO asks “Why does changing the $5 discount take 3 weeks?”

When Modularity Met Reality

Let’s play spot-the-issue in this Java snippet:

public interface UserService {
    User createUser(UserDTO userDTO);
}
public class UserServiceImpl implements UserService {
    private final UserValidator validator;
    private final UserRepository repo;
    private final EmailService emailService;
    // 15 constructor parameters later...
}

You’ve created:

1. A maintenance nightmare
2. A testability paradox (mocking 10 dependencies just to test one method)
3. Job security (but only if you plan to never quit) The bitter truth? Most projects don’t live long enough to justify their architecture. I’ve seen codebuses (code-buses? Codebuses.) that were over-engineered for scale they never achieved. It’s like building a particle accelerator to crack walnuts.

Practical Countermeasures

The 3-Question Filter before creating a new module:

1. “Will this change independently of other components?”
2. “Does this abstraction reduce cognitive load?”
3. “Am I doing this because of actual needs or architecture astronaut fantasies?” Try this refactoring workout:
4. Find a “manager” class coordinating 5+ dependencies
5. Inline methods until it screams
6. Watch hidden duplication emerge like magic

# Before: 8 files, 3 patterns
result = PriceCalculatorFactory.get_instance().calculate(order)
# After: 1 file, 0 factory patterns
result = sum(item.price * item.quantity for item in order.items)

When Modularity Actually Works

There’s a sweet spot - like your grandma’s meatloaf recipe. It works when:

• Different teams own components
• You’re building actual distributed systems
• You need to support multiple concrete implementations (real ones, not “might need someday”) Even then, remember Jeff Atwood’s law: “The best code is no code at all.” Sometimes the most modular solution is deleting the feature.

Survival Kit for Pragmatists

1. Write delete-friendly code
   • Can you remove features without bloodshed?
2. Embrace the humble function
   • Not every concept needs its own namespace
3. Implement YAGNI-driven development
   • Future requirements make terrible crystal balls
4. Optimize for reading, not writing
   • Code is read 10x more than written. Stop showing off. Next time you reach for the AbstractFactoryProxyDecorator, ask yourself: “Is this making the problem simpler, or just my code more ‘professional-looking’?” Your teammates (and production servers) will thank you. Final thought: If programming were carpentry, over-modularization would be using 1000 toothpicks to build a chair. It might look impressive, but good luck sitting on it.