Code Refactoring - Python Best Practices and Tips

posted 12 min read

Software normally fails when it becomes so complex that it can no longer provide the additional features needed while remaining error-free. Refactoring is used to improve the code design to make it easier to understand and extensible. If you believe that a feature may be needed and your current code will not easily accommodate it, you can refactor that code. You make it easier to add that feature now, rather than worrying about what you should change in your code to add the feature later.

Importance of Refactoring for Code Maintainability and Readability

Why should you refactor? By removing duplicate code, you reduce the overall codebase, making it easier to modify and understand. Hence, you have less code that is easier to modify and understand, which you are well aware of if you look at huge programs and try to understand how they work.

  1. Writing understandable code will make it easy to modify and maintain the code. By refactoring the code, you will understand the system better. If you know the system better, it would be easier to spot bugs.
  2. Refactoring also helps you write code faster. If you write understandable code, you will spend all your time adding features instead of having to go back and try to understand the code. You have written repetitively to fix bugs and incorporate new features.
  3. Refactoring also makes the code easy to read. Eliminating duplication makes modification easy and minimizes complex conditional logic.

In this article, I will cover the importance of refactoring, its principles and designs, and how you can improve your program readability through refactoring techniques. I will also discuss the best practices for enhancing the performance of your Python code.

Identifying Code Smells and Refactoring Opportunities

Introduction to Code Smells and Their Impact on Code Quality

While refactoring code, you are looking for bad smells, which indicates design problems. A code smell is like detecting in-depth issues and concerns in the application or its logic. These issues are not bugs and errors but deviations from the code design and its fundamentals that negatively impact the code quality. This violation will not affect the code compilation but will make the program performance vulnerable to future security threats. Therefore, these code smells are known as bad smells that require a thorough investigation of the program codebase to take immediate action to enhance the quality.

Common Code Smells in Python Programs

When the developer fails to write the code as per the defined design standard, it leads to code smell. Bad code is the result of hard deadlines, mismanagement, shortcuts, and inexperienced developer skills, which leads developers to make mistakes during the development process. Now, in Python, various types of code smell may differ from project to project. These are:

  1. Duplicate Code: One of the most common code smells is code duplication. It means that a similar block of code is used more than once in the program. Instead of copy-paste, there is also duplication in the code structure and inheritance hierarchies. Therefore, fixing it is easy by extracting the duplicate code into a separate function and then calling it whenever you need to.
  2. Long Methods: Another common code smell is long methods. This occurs when the function is too long and is responsible for many tasks. Breaking the long methods into smaller methods, where each must perform its task independently, will resolve this issue.
  3. Improper Names: Using the proper names of variables, classes, and methods will make the code understandable and clean. If you use character-based names or non-descriptive function names, it leads to code smell that makes it difficult to read and maintain. Therefore, the naming convention should be descriptive.

Some other code smells that need your attention are:

Techniques for Identifying Refactoring Opportunities Using Code Reviews and Analysis Tools

Code review is the process used to detect quality issues in an application. The most common issue that impacts code quality is bad smell. Code refactoring is an effective process for tracing code smell and maintaining software quality. It makes the code cleaner, concise, and effective without modifying its core functionalities. Furthermore, code review and analysis tools will help you identify the areas that benefit from refactoring. Several techniques for identifying refactoring opportunities are as follows:

Note: Some people think that refactoring is related to applying design patterns to your code, which is not true. However, spending a lot of time creating a better design is a simple refactoring goal.
  1. Duplicate Code: Duplicate code is a common issue for refactoring. pylint, and FindBugs are effective tools for analyzing and finding duplicate pieces of code. These tools reduce the risk of inconsistencies and make maintenance easier.
  2. Complexity Analysis: PyCharm is an IDE that provides the features of code analysis and refactoring tools and helps identify areas that would benefit from refactoring. In addition, tools like SonarQube and Code Climate will ensure the complexity analysis of code and provide the necessary tips to make it less complex.
  3. Code Static Analysis: mypy is a tool used to check Python code to identify potential bugs in your code. This tool ensures that your code follows a consistent structure.
  4. Security Analysis: Tools like Bandit will help Python developers identify potential security threats in their code.

Principles and Patterns of Refactoring

Introduction to Refactoring Principles

To write a maintainable and clean code of high quality, there are certain guidelines known as refactoring principles. These principles are the set of instructions proven to work over the years. These popular principles are as follows:

  1. DRY: Known as "Don’t Repeat Yourself.". This principle draws attention to the duplication problem within the code. When a block of code is used repeatedly, it makes the code harder to maintain and update because updating would be required at multiple locations. To implement this principle, developers must create a method containing duplicate content to ensure that logic is written in only one place and that the function can be called when needed.
  2. KISS: Knows as "Keep It Super Simple". This principle focuses on writing the code as simply as possible and in a way that the junior developer can easily understand. It highlights the simplicity of the code design and implementation, which makes the code more maintainable and readable. The main point is to avoid unnecessary complexity that leads to poor code quality and confusion among developers.
  3. SOLID: This principle is further divided into five principles that you can follow as the code passes the prototype phase. These five principles are as follows:
    1. S-Single Responsibility Principle (SRP): This principle emphasizes that each class in the code should have one responsibility or purpose. It ensures that the specific class or module is focused on one task, which makes the code less complex when modification is required.
    2. O-Open/Closed Principle (OCP): This principle emphasizes that each fundamental of code, like classes, modules, and functions, should be open to changes and modification without the need to change their existing behavior. This makes the code more flexible and modular.
    3. L-Liskov Substitution Principle (LSP): This principle's focus is that each derived class should be able to implement or replace the base class without any error. It means that the objects of the superclass are replaceable by subclasses without affecting the program's behavior. It makes the code more extensible and interchangeable.
    4. I-Interface Segregation Principles (ISP): This principle focuses on implementing multiple small interfaces based on client needs instead of one large interface. In this way, clients can interact with a specific interface according to their needs instead of a monolithic interface.
    5. D-Dependency Inversion Principle (DIP): These principles emphasize the use of an abstraction layer instead of the direct interaction between high- and low-level modules. This means that the high-level modules should not directly focus on the low-level module, which makes them highly coupled and difficult to modify.

Exploring Common Refactoring Patterns and Techniques

Let's explore common code refactoring patterns and techniques. These areas follows:

  1. Extract Method: Used to break large methods into separate functions or methods to simplify complex logic and make them more manageable.
  2. Replace Conditional with Polymorphism: Replaces the complex conditional logic with a polymorphism or inheritance concept to make the code easy to understand and modify.
  3. Extract Class: Used to place all related methods and fields in one class. It makes the class more manageable when it becomes large and complex; therefore, handles some responsibilities in a separate class.
  4. Extract Variable: Used to capture all complex expressions and variables and replace their names with descriptive names.
  5. Remove Parameters: Remove all unnecessary parameters used in the method signature to improve readability.
  6. Split Loop: Divide the large loop expression into smaller loops to enhance code clarity.
  7. Introduce Design Patterns: Use design patterns to solve recurring problems instead of writing the code yourself.

Understanding When and How to Apply Each Refactoring Pattern Effectively

Selecting the correct refactoring pattern and techniques and understanding when to use each depends on the code requirements. They require careful consideration and context upon which each is used. Let's explore the requirements of some of them:

1. Extract Method

When to Apply: Having duplicate and large methods that are replaced with a small separate method.
How to Apply: Identify the duplicate code, extract the code into a separate method, and Call the method where needed.

2. Replace Conditional with Polymorphism

When to Apply: Code containing complex conditional logic with object behavior changing on the basis of different states.
How to Apply: Remove all conditional logic and replace them with separate classes, where each class defines a separate state. Each class has its own method and fields.

3. Extract Class

When to Apply: One class performs too many distinct tasks and has many responsibilities. This makes the code logic complex.
How to Apply: Identify the methods and related fields that have similar tasks and group them into separate classes.

4. Extract Variable

When to Apply: When the same expression is used repeatedly within the method. Therefore, it is used to enhance code readability.
How to Apply: Identify all repeated expressions within the method. Then, assign it to a variable with a descriptive name.

5. Remove Parameters

When to Apply: When the parameter used in the method signature is no longer necessary. Furthermore, removing the parameter does not affect the functionality of the method.
How to Apply: Identify the unnecessary parameter and check the method body if it is used within the method. Next, remove the parameter when it is unnecessary and update the caller.

#An Example for removing the unnecessary parameter of middle name 
#which is not used 
def enter_Name(f_Name, m_Name, l_Name):
    return f"{f_Name} {m_Name} {l_Name}"
# Usage
full_name = enter_Name("Harry", "", "Ford")
print(full_name)
#----------------------------------------------------------------!
#After Refactoring
def enter_Name(f_Name, l_Name):
    return f"{f_Name} {l_Name}"
# Usage
full_name = enter_Name("Harry", "Ford")
print(full_name)

Refactoring Techniques for Improved Readability

Breaking Down Long and Complex Functions into Smaller One

One of the most common techniques for code refactoring is the extract method. This technique is used to break down complex and larger methods into smaller ones that are more manageable. Here, the block of code that performs a specific task is extracted into the new function. In addition, if the method is too old and not used frequently, then replacing the function call with method code i.e. inline method is preferable to avoid duplication and reduce complexity. Also, try to use the descriptive names of the methods that specify their task and the variable names within the method.

Caution: Always ensure that the refactored code maintains the same functionality as the original code. Also, thoroughly test to detect any unintended changes in behavior.

Improving Variable Names and Code Comments for Clarity and Understanding

When writing the code, use descriptive names for variables, functions, classes, and all other elements that adhere to industry standards and conventions. The use of a naming convention will improve the readability of code because it properly conveys its purpose and functionality, making it easier for a developer to understand the codebase and logic. In addition, the use of comments within the code will clarify the tasks and responsibilities of the classes and functions. Therefore, to implement the code refactoring, improve the variable name and add comments to clarify the code.

FAQs
Q: What is code refactoring in Python?
A: In Python, it is the process of restructuring Python's existing code without changing its external behavior.
Q: Is it important in Python development?
A: It is important in Python because it enhance readability, code quality, and maintainability and reduces bug risk.
Q: Is there any tool available with the IDE in Python?
A: Tools like PyCharm, Visual Studio Code with Python extensions, Rope, and Black are commonly used for code refactoring in Python.

Wrapping Up

In conclusion, we discussed the importance of code refactoring in the era of programming. Whether you're developing a small application or an enterprise-level application, code quality matters the most. Refactoring is not a magic button that resets the entire code, but it tells you the effective approach for writing maintainable code. It contains many strategies and techniques by which the developer can write perfect code. The perfect code requires fewer upgrades and enhances productivity. I hope this guide is helpful for you. Thank you for reading this. Happy Coding!


Reference

PyCharm Refactoring Documentation
PEP 8 style guide for Python code
Effective Book on Refactoring

If you read this far, tweet to the author to show them you care. Tweet a Thanks
Wow, this is such a good topic and I think this is an advanced python programming topic. I look forward to more.

More Posts

Python Debugging Techniques

Abdul Daim - Apr 29

Data Visualization with Python: Using Matplotlib and Seaborn

Muzzamil Abbas - Jul 6

Multithreading and Multiprocessing Guide in Python

Abdul Daim - Jun 7

Create a python Telegram bot, plain, simple and production-ready

Astra Bertelli - Apr 24

Git and GitHub for Python Developers A Comprehensive Guide

Tejas Vaij - Apr 7
chevron_left