The cleanliness and organization of code are essential for maintainability and readability. A project's coding style and naming conventions are designed to ensure consistency and improve code quality. Here are some examples to check whether the code is clean, organized, and follows the project's coding style and naming conventions:

1. Follow Naming Conventions

Unclean (Incorrect):

def calc_area(r): 
    PI_val = 3.14159 
    return PI_val * (r ** 2)

Clean (Correct):

def calculate_circle_area(radius): 
    PI_VALUE = 3.14159 
    return PI_VALUE * (radius ** 2)

Fix Explanation:

• The function name calc_area is changed to calculate_circle_area for better readability and clarity.

• The parameter r is changed to radius to make it more descriptive.

• The constant PI_val is renamed to PI_VALUE to follow the naming convention for constants in Python (all uppercase).

2. Code Formatting

Unclean (Incorrect):

import sys,os
def func():print('Example function')

Clean (Correct):

import os
import sys

def function_example(): 
    print('Example function')

Fix Explanation:

• Import statements are separated into individual lines to improve readability.

• Appropriate spaces and line breaks are added between function definitions and the code inside the function.

3. Avoid Redundant Code

Unclean (Incorrect):

if file_extension == 'jpg' or file_extension == 'jpeg' or file_extension == 'png': 
    process_image(file)

Clean (Correct):

if file_extension in ['jpg', 'jpeg', 'png']: 
    process_image(file)

Fix Explanation:

• The condition is simplified by using the in operator, reducing redundancy and improving readability.

4. Use Appropriate Comments

Unclean (Incorrect):

# Function to do something
def do_something(): pass

Clean (Correct):

def do_something(): 
    # TODO: Implement functionality or explain what the function does
    pass

Fix Explanation:

• Removed unnecessary or obvious comments.

• If the function is not implemented yet, a TODO comment is used to indicate the need for further implementation or to explain what the function is supposed to do.

5. Follow Line Length Conventions

Unclean (Incorrect):

def calculate_area(length, width): return length * width  # This line of code may be too long, exceeding the project’s maximum line length (e.g., 80 or 120 characters).

Clean (Correct):

def calculate_area(length, width):
    # The following code adheres to the project’s maximum line length convention
    return length * width

Fix Explanation:

• The single line of code is broken into multiple lines to comply with line length restrictions.

6. Proper Error Handling

Unclean (Incorrect):

try: 
    result = 10 / 0
except: 
    pass

Clean (Correct):

try: 
    result = 10 / 0
except ZeroDivisionError as e: 
    logging.error("Attempted to divide by zero")
    raise

Fix Explanation:

• Fixed the empty except block by catching the specific ZeroDivisionError.

• Appropriately logs the error and re-raises it for proper error handling and debugging.

7. Avoid Deep Nesting (Continued)

Unclean (Incorrect):

for i in range(len(data)):
    if data[i] > 0:
        # Do some processing
        if data[i] % 2 == 0:
            # More processing
            pass

Clean (Correct):

for value in data:
    if value <= 0:
        continue
    # Do some processing
    if value % 2 != 0:
        continue
    # More processing

Fix Explanation:

• Using continue reduces the level of nesting, making the code more readable.

• Replacing for i in range(len(data)) with for value in data makes the code more concise and Pythonic.

8. Clear and Concise Logic

Unclean (Incorrect):

def is_even(number):
    if number % 2 == 0:
        return True
    else:
        return False

Clean (Correct):

def is_even(number):
    return number % 2 == 0

Fix Explanation:

• Simplified the function by directly returning the result of the condition, instead of using an unnecessary if/else structure.

9. Use Consistent String Quotes

In some projects, it may be a convention to use either single or double quotes for consistency.

Unclean (Incorrect):

name = "Alice"
greeting = 'Hello, ' + name

Clean (Correct):

name = 'Alice'
greeting = 'Hello, ' + name

Or

name = "Alice"
greeting = "Hello, " + name

Fix Explanation:

• Choose one type of quote (single or double) and stick to it for consistency.

10. Avoid Magic Numbers

Unclean (Incorrect):

timeout = 120  # What is this? Why is it 120?

Clean (Correct):

DEFAULT_TIMEOUT_SECONDS = 120
timeout = DEFAULT_TIMEOUT_SECONDS

Fix Explanation:

• Use meaningful constants instead of hardcoding values directly in the code, making it more readable and maintainable.

11. Avoid Long Functions

Unclean (Incorrect):

def process_data(data):
    # Code spanning dozens of lines
    pass

Clean (Correct):

def process_data(data):
    preprocess_data(data)
    calculate_statistics(data)
    postprocess_data(data)

def preprocess_data(data):
    # Preprocessing logic
    pass

def calculate_statistics(data):
    # Statistics calculation
    pass

def postprocess_data(data):
    # Postprocessing logic
    pass

Fix Explanation:

• Break down long functions into smaller functions, each responsible for a part of the logic, making it easier to understand and maintain.

12. Use Blank Lines Appropriately

Using blank lines to separate logical parts of the code can enhance readability.

Unclean (Incorrect):

def complex_function():
    do_first_thing()
    do_second_thing()
    do_third_thing()
    # Missing blank line here, making it hard to distinguish different sections
    do_fourth_thing()

Clean (Correct):

def complex_function():
    do_first_thing()
    do_second_thing()

    do_third_thing()

    do_fourth_thing()

Fix Explanation:

• Added blank lines between logically independent code blocks, making the structure of the code clearer.

13. Avoid Too Many Parameters

The number of parameters in a function or method should be kept to a minimum. Too many parameters can make a function hard to understand and use.

Unclean (Incorrect):

def create_user(name, age, gender, email, phone, address, country, state, city, zip_code):
    pass

Clean (Correct):

class User:
    def __init__(self, name, age, gender, email, phone, address):
        pass

# Alternatively, use a dictionary or other structure to encapsulate parameters
def create_user(user_data):
    pass

Fix Explanation:

• Use classes or data structures to encapsulate related parameters, reducing the complexity of the function signature.

14. Use Descriptive Variable Names

Variable names should clearly describe the purpose of the variable.

Unclean (Incorrect):

a = 3.14  # What is 'a'?
r = 5
area = a * r * r

Clean (Correct):

PI = 3.14
radius = 5
circle_area = PI * radius * radius

Fix Explanation:

• Use descriptive variable names instead of vague single-letter names.

15. Avoid Unnecessary Global Variables

Global variables should be considered a last resort, as they can make code hard to trace and maintain.

Unclean (Incorrect):

# Some global variable
user_count = 0

def increment_user_count():
    global user_count
    user_count += 1

Clean (Correct):

class UserCounter:
    def __init__(self):
        self.count = 0

    def increment(self):
        self.count += 1

Fix Explanation:

• Use classes or other encapsulation methods to manage state that would otherwise be handled by global variables.

16. Use Version Control System Features

Make use of version control systems (such as Git) to handle code changes, rather than leaving old, commented-out code in the codebase.

Unclean (Incorrect):

# def old_function():
#     # Old implementation...
#     pass

def new_function():
    # New implementation...
    pass

Clean (Correct):

def new_function():
    # New implementation...
    pass

Fix Explanation:

• Remove old, unused code. Trust that the version control system will allow you to access previous versions when necessary.