Implementing a Python decorator for argument validation

Last update on April 21 2025 12:58:30 (UTC/GMT +8 hours)

5. Implement a Decorator to Validate Function Arguments

Write a Python program that implements a decorator to validate function arguments based on a given condition.

Sample Solution:

Python Code:

def validate_arguments(condition):
    def decorator(func):
        def wrapper(*args, **kwargs):
            if condition(*args, **kwargs):
                return func(*args, **kwargs)
            else:
                raise ValueError("Invalid arguments passed to the function")
        return wrapper
    return decorator

@validate_arguments(lambda x: x > 0)
def calculate_cube(x):
    return x ** 3

print(calculate_cube(5))  # Output: 125
print(calculate_cube(-2))  # Raises ValueError: Invalid arguments passed to the function

Sample Output:

125
Traceback (most recent call last):
.........
print(calculate_cube(-2))  # Raises ValueError: Invalid arguments passed to the function
........................
raise ValueError("Invalid arguments passed to the function")
ValueError: Invalid arguments passed to the function

Explanation:

In the above exercise, the "calculate_cube()" function is decorated with @validate_arguments. The validation condition is specified as a lambda function lambda x: x > 0, which checks if the argument x is greater than 0. When "calculate_cube()" is called with a positive number, it executes normally and returns the square of the input. However, if it's called with a negative number, it raises a ValueError indicating invalid arguments were passed.

Flowchart:

For more Practice: Solve these Related Problems:

Write a Python decorator that checks if all arguments passed to a function are positive integers and raises a ValueError otherwise.
Write a Python decorator that uses a user-defined predicate function to validate the input arguments before function execution.
Write a Python decorator that verifies that the number of arguments passed to a function is within a specified range.
Write a Python decorator that asserts the type of each argument, and if any mismatch occurs, logs the error and raises a TypeError.

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