Creating a Python decorator to log function arguments and return value

Last update on December 21 2024 07:28:00 (UTC/GMT +8 hours)

Write a Python program to create a decorator that logs the arguments and return value of a function.

The decorator in this code logs the function name, arguments, and return value whenever the decorated function is called.

Sample Solution:

Python Code:

def decorator(func):
    def wrap(*args, **kwargs):
        # Log the function name and arguments
        print(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}")
        
        # Call the original function
        result = func(*args, **kwargs)
        
        # Log the return value
        print(f"{func.__name__} returned: {result}")
        
        # Return the result
        return result
    return wrap

# Example usage
@decorator
def multiply_numbers(x, y):
    return x * y

# Call the decorated function
result = multiply_numbers(10, 20)
print("Result:", result)

Sample Output:

Calling multiply_numbers with args: (10, 20), kwargs: {}
multiply_numbers returned: 200
Result: 200

Explanation:

In the above exercise -

• The "decorator()" function is defined with a single parameter func, representing the function to be decorated.
• Inside the decorator function, another function called "wrap()" is defined. This "wrap()" function serves as a wrapper function that adds extra functionality to the original function.
• The "wrap()" function accepts any number of positional and keyword arguments (*args and **kwargs), allowing it to handle functions with varying arguments.
• The wrapper function first logs the function name and its arguments using formatted string literals (f"...").
• The original function is then called using func(*args, **kwargs), and the result is stored in the result variable.
• The wrapper function logs the return value after calling the original function.
• Finally, the wrapper function returns the result.

The "@decorator" syntax is used to apply the "decorator" to the "multiply_numbers()" function, indicating that it should be decorated with the functionality provided by the "decorator()" function.

Flowchart:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Python Decorator Exercises Home.
Next: Creating a Python decorator to measure function execution time.