Question

Many try/except/finally-clauses not only “uglify” my code, but i find myself often using identical exception-handling for similar tasks. So i was considering reducing redundancy by “outsourcing” them to a … decorator.

Because i was sure not to be the 1st one to come to this conclusion, I googled and found this – imho – ingenious recipe which added the possibility to handle more than one exception.

But i was surprised why this doesn’t seem to be a wide known and used practice per se, so i was wondering if there is maybe an aspect i wasn’t considering?

1. Is it bogus to use the decorator pattern for exception-handling or did i just miss it the whole time? Please enlighten me! What are the pitfalls?

2. Is there maybe even a package/module out there which supports the creation of such exception-handling in a reasonable way?

Answer 1

The biggest reason to keep the try/except/finally blocks in the code itself is that error recovery is usually an integral part of the function.

For example, if we had our own int() function:

def MyInt(text):
    return int(text)

What should we do if text cannot be converted? Return 0? Return None?

If you have many simple cases then I can see a simple decorator being useful, but I think the recipe you linked to tries to do too much: it allows a different function to be activated for each possible exception–in cases such as those (several different exceptions, several different code paths) I would recommend a dedicated wrapper function.

Here’s my take on a simple decorator approach:

class ConvertExceptions(object):

    func = None

    def __init__(self, exceptions, replacement=None):
        self.exceptions = exceptions
        self.replacement = replacement

    def __call__(self, *args, **kwargs):
        if self.func is None:
            self.func = args[0]
            return self
        try:
            return self.func(*args, **kwargs)
        except self.exceptions:
            return self.replacement

and sample usage:

@ConvertExceptions(ValueError, 0)
def my_int(value):
    return int(value)

print my_int('34')      # prints 34
print my_int('one')     # prints 0