How to Preserve Signatures of Decorated Functions

Preserving Signatures of Decorated Functions

The issue arises when decorating a function with a generic decorator that alters the function's arguments, such as type conversion, logging, or memoization. The decorated function fails to inherit the original function's documentation and signature, making it challenging to understand its behavior.

To address this problem, multiple workarounds have been proposed:

Method 1: Using the 'Decorator' Module

Install the 'decorator' module using pip and modify the decorator definition to include the decorator.decorator annotation. This ensures that the decorator remains generic while preserving the function's signature:

<code class="python">import decorator

@decorator.decorator
def args_as_ints(f, *args, **kwargs):
    # Perform argument conversion
    return f(*args, **kwargs)</code>

Method 2: Using 'functools.wraps()'

For Python 3.4 and above, 'functools.wraps()' offers an alternative solution that automatically preserves both the function's signature and documentation:

<code class="python">import functools

def args_as_ints(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        # Perform argument conversion
        return func(*args, **kwargs)
    return wrapper</code>

Conclusion

Both methods effectively preserve the original function's signature and documentation. The 'decorator' module is suitable for Python 2 and 3, while 'functools.wraps()' is only available in Python 3.4 and above.

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