Best Practices in Python

Python is a versatile and powerful programming language that is widely used for various applications, such as web development, data analysis, machine learning, and more. While Python is known for its simplicity and readability, there are several best practices that you should follow to write clean, efficient, and maintainable code. In this guide, we'll explore some of the best practices in Python that will help you become a better Python programmer.

1. Use Descriptive Variable Names

When writing Python code, it's important to use descriptive variable names that convey the purpose of the variable. This makes your code more readable and easier to understand for other developers. Avoid using single-letter variable names or cryptic abbreviations, as they can make your code difficult to follow.

# Bad
x = 5
y = 10
z = x + y
 
# Good
total = 5
tax = 10
final_price = total + tax

2. Follow PEP 8 Style Guide

PEP 8 is the official style guide for Python code, and it provides guidelines on how to format your code for maximum readability. Following the PEP 8 style guide will make your code consistent and easier to read for other developers. Some key points from the PEP 8 style guide include:

Use 4 spaces for indentation
Limit lines to 79 characters
Use snake_case for variable and function names
Use CamelCase for class names

 
# Bad
def calculate_total(price,quantity):
    return price*quantity
 
# Good
def calculate_total(price, quantity):
    return price * quantity

3. Use List Comprehensions

List comprehensions are a concise and efficient way to create lists in Python. They allow you to generate a new list by applying an expression to each item in an existing list. List comprehensions are more readable and faster than traditional for loops, and they can help you write more expressive and compact code.

# Traditional for loop
squares = []
for i in range(1, 6):
    squares.append(i * i)
 
# List comprehension
squares = [i * i for i in range(1, 6)]

4. Avoid Using Global Variables

Global variables can make your code difficult to understand and maintain, as they can be modified from anywhere in your program. Instead of using global variables, consider using function arguments or return values to pass data between functions. This makes your code more modular and easier to test and debug.

# Bad
total = 0
 
def add_to_total(amount):
    global total
    total += amount
 
# Good
def add_to_total(total, amount):
    return total + amount

5. Use Virtual Environments

Virtual environments are isolated environments that allow you to install and manage dependencies for your Python projects. By using virtual environments, you can avoid conflicts between different projects and ensure that your dependencies are consistent across different environments. The venv module is included in the Python standard library and allows you to create virtual environments easily.

# Create a virtual environment
python -m venv myenv
 
# Activate the virtual environment
source myenv/bin/activate

6. Document Your Code

Documenting your code is essential for making it understandable and maintainable. Use comments and docstrings to explain the purpose of your code, how it works, and any important details that other developers should know. Follow the Google Python Style Guide (opens in a new tab) for writing clear and concise comments and docstrings.

def calculate_total(price, quantity):
    """Calculate the total price of an item.
 
    Args:
        price (float): The price of the item.
        quantity (int): The quantity of the item.
 
    Returns:
        float: The total price of the item.
    """
    return price * quantity

7. Refactor Your Code

Refactoring is the process of restructuring your code to improve its readability, maintainability, and efficiency. When refactoring your code, look for opportunities to simplify complex logic, remove duplicate code, and improve naming and organization. Refactoring can help you write cleaner and more maintainable code that is easier to work with in the long run.

# Bad
def calculate_total(price, quantity):
    total = 0
    for i in range(quantity):
        total += price
    return total
 
# Good
def calculate_total(price, quantity):
    return price * quantity

8. Use Built-in Functions and Libraries

Python provides a rich set of built-in functions and libraries that can help you write code more efficiently. Take advantage of built-in functions, such as map, filter, and reduce, to perform common operations on lists and other data structures. Use built-in libraries, such as sys, math, and datetime, to access system functionality and perform specialized tasks.

# Using built-in functions
numbers = [1, 2, 3, 4, 5]
 
# Map
squared_numbers = list(map(lambda x: x * x, numbers))
 
# Filter
even_numbers = list(filter(lambda x: x % 2 == 0, numbers))
 
# Using built-in libraries
import math
 
# Calculate the square root of a number
print(math.sqrt(25))

Use TODO Comments

TODO comments are a useful way to mark sections of your code that need to be completed or improved. Use TODO comments to indicate areas of your code that require further work, such as implementing missing functionality, fixing bugs, or optimizing performance. This can help you keep track of outstanding tasks and prioritize your work effectively.

 
# TODO: Implement error handling
def divide(a, b):
    return a / b

This enables you to quickly identify areas of your code that need attention and ensures that you don't forget about important tasks.

@Override Decorator

The @override decorator is a useful tool for ensuring that you are correctly overriding a method from a superclass. By using the @override decorator, you can indicate that a method in a subclass is intended

class Animal:
    def speak(self):
        print("Animal speaks")
 
class Dog(Animal):
 
    @override
    def speak(self):
        print("Dog barks")

This can help you avoid common errors, such as misspelling method names or failing to override a method correctly.

Conclusion

By following these best practices in Python, you can write clean, efficient, and maintainable code that is easy to read and understand. These practices will help you become a better Python programmer and improve the quality of your code. Remember to always strive for simplicity, readability, and consistency in your code, and don't be afraid to refactor and improve your code as you learn and grow as a developer. Happy coding!

Resources

References

Basic Concepts of Multithreading Check Point #01