Python Code Refactoring Tutorial – Complete Guide

Welcome to this enlightening tutorial on Python Code Refactoring. This vital coding practice improves the efficiency and readability of your Python programs, cementing your status as a skilled programmer. Let’s embark on this journey that will elevate your coding proficiency.

What is Python Code Refactoring?

Python code refactoring encompasses the process of revising and improving your Python source code to enhance its readability, efficiency, or maintainability without altering its core functionality. This practice allows you to sculpt your code into a cleaner, more efficient, and well-documented masterpiece.

Why Should You Learn Python Code Refactoring?

Code refactoring holds significant importance in Python development. Here’s why:

• It makes your code easier to understand and debug, thereby improving productivity.
• It can help to optimize your code, resulting in efficient execution and resources management.
• It cultivates good coding habits, as you’ll naturally begin writing cleaner, more readable code as part of your development process.
• High-quality refactored code can make collaboration easier as others can easily understand and modify your code.

Without a doubt, Python Code Refactoring is a fantastic skill to possess, making it an essential learning point for both beginner and experienced coders.

FREE COURSES AT ZENVA

LEARN GAME DEVELOPMENT, PYTHON AND MORE

ACCESS FOR FREE

AVAILABLE FOR A LIMITED TIME ONLY

Basics of Python Code Refactoring

In this section, let’s discuss some fundamental ways to refactor your Python code. These basic techniques primarily involve code simplification and improving code readability.

1. Extract Variable

One way of refactoring code is by extracting complex expressions or frequently used values into variables. This improves readability.

# Before Refactoring
print('Hello, ' + 'John' + '. You are ' + '25' + ' years old.')

# After Refactoring
name = 'John'
age = '25'
print(f'Hello, {name}. You are {age} years old.')

2. Use of List Comprehensions

List comprehensions can replace loops and make your code much cleaner and efficient.

# Before Refactoring
squares = []
for i in range(10):
    squares.append(i**2)

# After Refactoring
squares = [i**2 for i in range(10)]

3. Simplify If Statements

If statements can be simplified to improve readability and efficiency.

# Before Refactoring
x = 10
if x % 2 == 0:
    is_even = True
else:
    is_even = False

# After Refactoring
x = 10
is_even = (x % 2 == 0)

These techniques can go a long way in improving the quality and readability of your Python code. Now, let’s delve deeper.

Intermediate Python Code Refactoring Techniques

Now, let’s look at some more intermediate-level refactoring techniques. These techniques involve the use of Python’s advanced features and revolve around simplifying complex code structures.

1. Replace Temp with Query

Replacing temps with direct queries can reduce the number of lines of code and avoid unnecessary variables.

# Before Refactoring
x = some_complex_function()
y = x * 5

# After Refactoring
y = some_complex_function() * 5

2. Decompose Conditional

Conditional logic can often be complex and hard to understand. Decompose them to create simpler, more readable code.

# Before Refactoring
if (temperature>30 and humidity>80):
    return 'Too hot and humid'

# After Refactoring
def is_hot_and_humid(temperature, humidity):
    return temperature>30 and humidity>80

if is_hot_and_humid(temperature, humidity):
    return 'Too hot and humid'

3. Replace Magic Number with Symbolic Constant

Magic numbers in the code can be confusing. Replace them with symbolic constants for better readability.

# Before Refactoring
area = 3.14 * radius**2

# After Refactoring
PI = 3.14
area = PI * radius**2

4. Remove Dead Code

Any code that isn’t being used should be removed.

# Before Refactoring
def calculate_area(radius):
    PI = 3.14
    unused_variable = 100 # This variable is not used anywhere.
    area = PI * radius**2
    return area

# After Refactoring
def calculate_area(radius):
    PI = 3.14
    area = PI * radius**2
    return area

Refactoring is not just about cleaning up code. It’s also an integral part of the software development cycle. Understanding and implementing these techniques will undoubtedly make your Python programs more efficient and readable. Experiment with your code and try combining and reusing these techniques!

Advanced Python Code Refactoring Techniques

In this section, we will delve into some advanced techniques to refactor your Python code. Here, we will explore the implementation of some common design patterns which can enhance the structure and maintainability of your code.

1. Extract Method

This refactoring technique involves breaking down a large function into smaller, reusable functions.

# Before Refactoring
def print_details():
    name = 'John'
    age = 25
    print(f'Hello, {name}. You are {age} years old.')

# After Refactoring
def print_name(name):
    print(f'Hello, {name}.')

def print_age(age):
    print(f'You are {age} years old.')

def print_details():
    name = 'John'
    age = 25
    print_name(name)
    print_age(age)

2. Replace Nested Conditional with Guard Clauses

This involves replacing complex nested conditionals with simpler guard clauses.

# Before Refactoring
def adjust_marks(marks):
    if marks  -10:
            return 0
        else:
            return 'Invalid'
    else:
        return marks

# After Refactoring
def adjust_marks(marks):
    if marks > -10 and marks < 0:
        return 0
    if marks <= -10:
        return 'Invalid'
    return marks

3. Apply Decorators

Decorators can be used to modify the functions’ behavior neatly and efficiently.

# Before Refactoring
def call_twice(func, arg):
    return func(func(arg))

def add_five(x):
    return x + 5

result = call_twice(add_five, 5)

# After Refactoring
def call_twice(func):
    def wrapper(x):
        return func(func(x))
    return wrapper

@call_twice
def add_five(x):
    return x + 5

result = add_five(5)

4. Refactor Long Parameter Lists

Long parameter lists make your code more complex and harder to read. Hence, they should be refactored.

# Before Refactoring
def print_details(name, age, country, city, postcode):
    print(f'Hello, {name}. You are {age} years old.')
    print(f'You live in {city}, {country}, {postcode}.')

# After Refactoring
def print_details(name, age, address):
    print(f'Hello, {name}. You are {age} years old.')
    print(f'You live in {address["city"]}, {address["country"]}, {address["postcode"]}.')

address = {"country": "USA", "city": "New York", "postcode": "10001"}
print_details('John', 25, address)

5. Refactor Global Variables

Global variables should be avoided if possible and refactored into class variables or passed as function parameters.

# Before Refactoring
global_var = "I'm global!"

def print_global():
    print(global_var)

# After Refactoring
def print_var(a_var):
    print(a_var)

a_var = "I'm local!"
print_var(a_var)

Remember, the main goal of refactoring is to make your code more readable and maintainable. It’s always crucial to have effective structuring and clear code as part of your professional coding strategy.

Where To Go Next?

Congratulations! Having armed yourself with the invaluable knowledge of Python code refactoring, you’ve taken a significant leap forward in your development journey. But remember, becoming a programming master requires constant learning and practice.

As you continue your journey, we would like to guide you through a look at our Python Mini-Degree program. This is an all-encompassing collection of courses, offering a mix of Python programming essentials, algorithms, object-oriented programming, game and app development, and more.

All the courses included in the Python Mini-Degree are designed for both beginners and more experienced learners. You’ll tackle project-based assignments that give you hands-on experience and help you build a dynamic portfolio. Not to mention that all of our courses offer certificates upon completion.

Through these courses, you will gain a deeper understanding of Python, build on the knowledge you have already acquired, learn new Python libraries and frameworks, and work on real-world projects that enhance your portfolio. You can explore our Python course catalogue here.

Conclusion

Code refactoring is an essential skill that can elevate your programming proficiency to new heights and help you stand out in the tech industry. Python, being an intuitive and powerful language, offers you numerous ways to refactor your code. Remember, it’s all about making your code more readable, efficient, and manageable without changing its behavior. With the techniques you’ve learned in this guide, you’re well on your way to writing cleaner and more efficient Python code.

Whether you’re just stepping onto the Python train or polishing your advanced programming skills, Zenva’s comprehensive Python Mini-Degree program is designed to facilitate all levels of learners. It covers everything from basic syntax to advanced Python libraries, providing hands-on projects and certification upon completion. Embark on this journey to become a pro Python programmer with Zenva today!

Did you come across any errors in this tutorial? Please let us know by completing this form and we’ll look into it!

FREE COURSES

FINAL DAYS: Unlock coding courses in Unity, Godot, Unreal, Python and more.

ACCESS FOR FREE