Capstone Chronicles: My Senior Year Journey

Introduction

Writing clean code is not just a skill; it’s a responsibility every programmer should embrace. Clean code makes a codebase easier to read, maintain, and debug, which saves time and prevents headaches. On the other hand, code smells are warning signs that indicate deeper issues in the code, leading to technical debt and maintenance nightmares. After reading “What Is Clean Code?” by Codacy and “Common Code Smells” by 8th Light, I’ve identified one practice I want to adopt more often and one practice I want to avoid at all costs.

What I Want to Start Doing: Writing Short, Single-Purpose Functions

One of the principles of clean code that stood out to me was writing short functions that do only one thing, also known as the Single Responsibility Principle (SRP). Breaking down a function into smaller, purpose-driven chunks makes code more readable, easier to debug, and reusable in different parts of a project.

Here’s an example of bad practice, where a single function is overloaded with multiple responsibilities:

 def process_order(order):
     # Validate order
     if not order.is_valid():
         return "Invalid order"
     # Calculate total price
     total_price = sum(item.price for item in order.items)
     if order.has_discount:
         total_price *= 0.9  # Apply discount
     # Save to database
     database.save_order(order, total_price)
     return "Order processed"

This function is doing too much: validation, calculation, and saving data. It’s a classic code smell, known as Long Methods, as described in the 8th Light article.

Here’s a cleaner, refactored version:

 def validate_order(order):
     if not order.is_valid():
         return False
     return True

 def calculate_total_price(order):
     total = sum(item.price for item in order.items)
     if order.has_discount:
         total *= 0.9
     return total

 def save_order(order, total_price):
     database.save_order(order, total_price)
 
 def process_order(order):
     if not validate_order(order):
         return "Invalid order"
     total_price = calculate_total_price(order)
     save_order(order, total_price)
     return "Order processed"

Each function now has a single purpose, making it easier to read, debug, and test independently. I aim to implement this principle consistently in my future projects.

What I Want to Avoid: Hard-Coded Values

From the Codacy article, I learned about the problems caused by hard-coded values (magic numbers). They reduce readability, make code harder to maintain, and increase the risk of errors when requirements change. For example, imagine encountering this piece of code in a large codebase:

 if user.age > 18:
     discount = order_total * 0.1  # 10% discount
 else:
     discount = 0

While the logic works, it’s unclear why the age is set to 18 or why the discount is 10%. This ambiguity can confuse other developers (or even future me).

A better approach is to use named constants:

 
 MINIMUM_AGE_FOR_DISCOUNT = 18
 DISCOUNT_RATE = 0.1
 
 if user.age > MINIMUM_AGE_FOR_DISCOUNT:
     discount = order_total * DISCOUNT_RATE
 else:
     discount = 0

Now, the code is self-documenting, and any changes (e.g., raising the age threshold to 21) can be made in one place.

The Importance of Clean Code

Clean code isn’t just about aesthetics; it’s about functionality and teamwork. Clean code ensures that:

1. New team members can onboard quickly. They don’t need hours to decipher poorly written code.
2. Debugging becomes easier. Clear code makes it simpler to pinpoint the source of issues.
3. Future changes are painless. Maintainability is a critical aspect of software longevity.

Recognizing and Addressing Code Smells

Code smells are subtle signs of trouble in the codebase. While they don’t always break functionality, they make code harder to maintain and extend. Some common smells I’ll actively look out for include:

• Duplicate Code: It leads to inconsistencies when updates are made to one part of the code but not the duplicate.
• Data Clumps: Repeated groups of parameters are better encapsulated in a class or data structure.
• Refused Bequest: If a subclass doesn’t use methods from its parent class, it’s likely a sign that inheritance is being misused.

Conclusion

By adopting clean code practices, such as writing short, single-purpose functions, and avoiding pitfalls like hard-coded values, I can improve the quality of my code and ensure it remains maintainable and extensible. Recognizing and addressing code smells early will prevent technical debt and promote a collaborative, efficient development process.

Let’s strive to leave every codebase we touch better than we found it!

References:

1. What Is Clean Code? A Guide to Principles and Best Practices – Codacy
2. Common Code Smells – 8th Light