Code Refactoring Best Practices

As a software developer, there‘s always a temptation to move fast, ship features, and never look back. But if you neglect the quality of your code, you‘ll eventually pay the price in the form of hard to maintain systems, bugs, and delays.

One essential habit to counter this is regular code refactoring – restructuring and cleaning up your code without changing its external behavior. Think of it like tidying your home; a small time investment that makes the whole place more livable and functional.

In this post, we‘ll look at code refactoring best practices and techniques, with a focus on Python examples. By the end, you‘ll see how refactoring is a skill every serious programmer needs in their toolbox.

What is Code Refactoring?

Code refactoring is the process of restructuring existing code without changing its external behavior. The goal is to improve the code‘s nonfunctional attributes like readability, maintainability, performance, and extensibility.

It‘s like editing an article – you‘re not changing the overall meaning or flow, just polishing sentences, fixing grammar, and maybe rearranging some paragraphs to get the point across better. The end result still accomplishes the same thing, just in a more refined way.

Why Should You Refactor Code?

You might be thinking "If it ain‘t broke, don‘t fix it!". But there are some compelling reasons to get into the habit of refactoring code:

Improve Code Quality

As code bases grow and evolve, the original design choices and assumptions may no longer hold true. Quick hacks and changed requirements can lead to duplicated code, over-complex logic, and poor performance.

Refactoring forces you to revisit these pain points and apply a fresh perspective to make the code cleaner and clearer. You‘ll end up with code that‘s easier to read, test, and maintain.

Enable Faster Development

While refactoring itself doesn‘t add new features, it makes adding them easier. Well-factored code is easier to extend and modify without breaking existing functionality.

Think of it like organizing your kitchen – having everything in a logical place means you can cook faster without hunting for the spatula every time. Similarly, having clear, modular code means you can quickly locate the right place to make a change.

Reduce Bugs and Debugging Time

Messy code is bug-prone code. Complex logic and hidden dependencies make it easy for subtle errors to slip through unnoticed.

Refactoring simplifies the code and makes the flow of data and control more transparent. This means fewer nasty surprises, and when bugs do crop up, they‘re easier to track down and fix.

Share Knowledge and Bus-Factor

Refactoring is a great way to on-board new team members and spread knowledge. Walking through the process of cleaning up the code with others is an interactive way to explain how the system works and clarify fuzzy areas.

Without refactoring, knowledge of the codebase stays siloed in individual brains, leading to a "bus factor" problem – what happens if the one developer who understands a piece of code wins the lottery and quits on the spot? Refactoring externalizes that knowledge into the code itself.

When Should You Refactor?

Deciding when to refactor is sometimes an art, but here are some tell-tale signs:

Rule of Three

If you‘ve copied and pasted a piece of code three times, it‘s a strong signal it needs refactoring into a reusable function, class, or module. Duplication makes the code harder to maintain, as any changes or fixes have to be made in multiple places.

Code Smells

"Code smells" are surface indications of deeper problems in the code. Some common ones include:

Long functions or classes trying to do too many things
Complex conditional logic with many branches
Too many parameters being passed around
Duplicated code
Uncommunicative or misleading names
Magic numbers and string constants
Tightly coupled modules with circular dependencies

If your nose wrinkles when reading a piece of code, trust your instincts and refactor to address the underlying issue.

Bug Fixes and Feature Changes

Counterintuitively, bug fixing and adding new features are great times to refactor. As you dig into the relevant part of the code, you gain fresh insights into what could be improved.

Of course, it‘s important not to get sidetracked and forget to actually fix the bug! Refactoring should be in service of the task at hand. But often a bit of cleanup makes the change easier in the first place.

Code Refactoring Techniques with Python Examples

Enough theory, let‘s see some real code! Here are some concrete techniques for refactoring Python, with before-and-after examples.

Extracting Reusable Functions

DRY (Don‘t Repeat Yourself) is a key principle of clean code. If you see the same code structure repeated over and over, it‘s time to extract it into a reusable function.

Consider this example of summing the squares of numbers in two lists:

numbers1 = [1, 2, 3, 4, 5] 
numbers2 = [3, 4, 7, 8, 9]
sum1 = 0
for num in numbers1:
sum1 += num**2
sum2 = 0
for num in numbers2: 
sum2 += num**2

The logic to sum the squares is duplicated. Let‘s refactor it into a function:

def sum_squares(numbers):
    total = 0
    for num in numbers:
        total += num**2
    return total
numbers1 = [1, 2, 3, 4, 5]
numbers2 = [3, 4, 7, 8, 9]
sum1 = sum_squares(numbers1)

sum2 = sum_squares(numbers2)

Much cleaner! Now the summing logic can be reused anywhere, and changes only need to be made in one place.

Consolidating Conditional Logic

Complex conditional logic with many branches is a common source of bugs. Often this logic can be consolidated and clarified.

Take a look at this example that classifies a number into different ranges:

  
def classify_number(num):
    if num  0 and num = 10 and num < 100:
        return "medium positive"
    else:
        return "large positive"

The multiple comparisons make the logic hard to follow. Let‘s refactor:

def classify_number(num):  
    if num < 0:
        return "negative"
    if num == 0:
        return "zero"
    if 0 < num < 10:
        return "small positive"
    if 10 <= num < 100:  
        return "medium positive"
    return "large positive"

By consolidating related comparisons and leveraging Python‘s chained comparison operators, the logic becomes much easier to understand at a glance.

Replacing Complex Loops with List Comprehensions

List comprehensions are a powerful feature in Python that let you transform and filter lists in a concise way. They can often replace complex for loops.

Consider this code that filters a list of words to only those starting with a vowel:

words = ["apple", "banana", "cherry", "date"]
vowels = ["a", "e", "i", "o", "u"]
vowel_words = []
for word in words:
if word[0].lower() in vowels:
vowel_words.append(word)

Let‘s refactor this to use a list comprehension:

words = ["apple", "banana", "cherry", "date"] 
vowels = ["a", "e", "i", "o", "u"]
vowel_words = [word for word in words if word[0].lower() in vowels]

The list comprehension condenses the filtering logic into a single line. It‘s more readable once you‘re familiar with the syntax, and often performs better too.

Beyond specific techniques, there are some general principles to keep in mind as you refactor:

Test Before and After

Refactoring without tests is like rock climbing without a rope – it might go okay, but you‘ll eventually fall. Having a robust test suite that exercises the code you‘re refactoring gives you confidence that your changes haven‘t broken anything.

Always run your tests before and after refactoring. If you don‘t have tests, write them first! Refactoring will be much less stressful.

Refactor in Small Steps

Resist the temptation to refactor everything at once in a Herculean effort. Like with most code changes, small, incremental refactors are safer and easier.

Pick one technique or code smell to address at a time. Fully complete that refactor with tests before moving on to the next. It might feel slower, but you‘ll waste less time chasing regressions and going down rabbit holes.

Follow the "Scout Rule"

The Scout Rule states "Always leave the code cleaner than you found it". Whenever you touch a piece of code, look for small opportunities to improve it and leave things better for the next person.

Over time, lots of small improvements compound. You avoid a big scary refactor down the line by giving the code constant TLC.

Communicate and Get Buy-In

Refactoring is often seen as a detour or distraction from "real" work like bugs and features. Developers can be hesitant to do it for fear of looking unproductive.

It‘s important to communicate the value of refactoring to your team and get buy-in from leadership that it‘s an important part of development. Point to the time saved by having cleaner code and use metrics like bugs resolved.

Physically refactoring as a team with pair programming or mob programming sessions can also help spread the refactoring mindset.

Refactoring Tools

While you can refactor with any text editor, some tools can help make the process easier and less error-prone:

IDE refactoring features (e.g. renaming, extracting methods)
Static analysis tools to find code smells (e.g. pylint, flake8)
Test runners and coverage tools (e.g. pytest, coverage.py)
Version control (e.g. git) to make experimental refactors safe

Go Forth and Refactor!

Refactoring is a key practice for every professional developer. By keeping your code clean, you‘ll be able to go faster and with fewer headaches.

Remember – refactoring is not about achieving perfection in one go. Think of it like cleaning as you cook rather than facing a giant pile of dishes later.

Look for small opportunities to leave the code better as you work. Follow the key principles of testing, incrementalism, and communication. With good habits and helpful tools, refactoring will become a natural and rewarding part of your development flow.

Now get out there and make your code better one step at a time!

Code Refactoring Best Practices – with Python Examples