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10 Best Practices for your Python code

10 Best Practices for your Python code

Write Efficient and Maintainable Python Code with These 10 Best Practices

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Soumendra kumar sahoo
ยทMar 4, 2023ยท

4 min read

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Table of contents

  • Follow PEP 8 Style Guide
  • Use Descriptive Names
  • Document your Code
  • Use List Comprehension
  • Don't Repeat Yourself (DRY)
  • Use Exceptions
  • Use Enumerate
  • Use Generators
  • Use Context Managers
  • Use Decorators
  • Use Virtual Environments
  • Use version control
  • Conclusion

In this blog post, I will share ten best practices every Python developer should follow. These best practices will help you write better, more efficient, and readable Python code.

Follow PEP 8 Style Guide

  • The Python community has established a style guide, PEP 8, which outlines guidelines for writing Python code. Following these guidelines makes your code more readable and easier to maintain.

  • You can check out the official guide here: https://www.python.org/dev/peps/pep-0008/

Use Descriptive Names

  • Use descriptive names for variables, functions, and classes that describe their purpose. This makes it easier for others to understand what your code is doing. For example:
# Bad Example
x = 'Soumendra Kumar Sahoo'
y = 5

# Good Example
customer_name = 'Soumendra Kumar Sahoo'
number_of_items = 5

Document your Code

  • Document your code using comments and docstrings. This helps other developers understand your code and makes it easier for you to maintain and modify it in the future. For example:

  •         def calculate_total_price(item_prices):
                """
                Calculate the total price of items in a list
    
                :param item_prices: Price of each item 
                :return: total price of all items
                """
                total_price = sum(item_prices)
                return total_price
    

Use List Comprehension

  • Use list comprehension instead of loops when creating new lists. This makes your code more readable and concise. For example:

  •         # Using a for loop
            new_list = []
            for i in range(10):
                new_list.append(i * 2)
    
            # Using list comprehension
            new_list = [i * 2 for i in range(10)]
    

Don't Repeat Yourself (DRY)

  • Avoid duplicating code. Instead, use functions or classes to encapsulate functionality used in multiple places.

Use Exceptions

  • Use exceptions to handle error conditions instead of using if-else statements. This makes your code more readable and easier to maintain. For example:

  •         try:
                result = 10 / 0
            except ZeroDivisionError:
                print("Cannot divide by zero")
    

Use Enumerate

Use enumerate to get the index of each element in a list. This makes your code more readable and concise. For example:

# Without enumerate
for i in range(len(my_list)):
    print(i, my_list[i])

# With enumerate
for i, item in enumerate(my_list):
    print(i, item)

Use Generators

  • Use generators instead of lists when iterating over large data sets. This saves memory and makes your code more efficient. For example:

  •         # Using a list
            my_list = [i * 2 for i in range(100000)]
    
            # Using a generator
            my_generator = (i * 2 for i in range(100000))
    

Use Context Managers

  • Use context managers to ensure that resources are adequately managed and released. This includes file I/O operations and database connections. For example:

  •         # Bad example
            f = open('file.txt', 'r')
            data = f.read()
            f.close()
    
            # Good example
            with open('file.txt', 'r') as f:
                data = f.read()
    

Use Decorators

  • Use decorators to add functionality to functions without modifying the original function. This makes your code more readable and easier to maintain. For example:

  •         def my_decorator(func):
                def wrapper():
                    print("Before the function is called.")
                    func()
                    print("After the function is called.")
                return wrapper
    
            @my_decorator
            def say_hello():
                print("Hello")
    
            say_hello()
    
            # Output
            Before the function is called.
            Hello
            After the function is called.
    

Use Virtual Environments

  • Use virtual environments to create isolated Python environments for your projects. This helps to avoid conflicts between different packages and dependencies.

  • For example:

# Creating a virtual environment
python -m venv myenv

# Activating the virtual environment
source myenv/bin/activate

# if you are using conda then create an venv using
conda create -n <env name>

# activate environment
conda activate <env name>

Use version control

  • Do not manage changes by folders and file management. Instead, use version control to manage your code and collaborate with other developers. This helps to keep track of changes and makes it easier to revert to previous versions if needed.

Conclusion

  • In conclusion, following these best practices will make you a better Python developer and help you write more efficient and maintainable code.

  • Using descriptive names, documenting your code, and following the PEP 8 style guide will make your code more readable and easier to understand.

  • List comprehension, generators, and context managers will make your code more efficient and save memory.

  • Exceptions, assertions, and logging will make your code more robust and easier to debug.

  • Finally, using version control will make it easier to collaborate with other developers and maintain your code over time.

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