methodmemoize.py

import functools

class memoize(object):
    def __init__(self, func):
        self.func = func
        self.cache = {}
    def __call__(self, *args):
        return self.cache_get(args, lambda: self.func(*args))
    def __get__(self, obj, objtype):
        return self.cache_get(obj, lambda: self.__class__(functools.partial(self.func, obj)))
    def cache_get(self, key, gen_callback):
        try:
            return self.cache[key]
        except KeyError:
            self.cache[key] = gen_callback()
            return self.cache[key]

class Adder(object):
    @memoize
    def add(self, arg1, arg2):
        print 'CALCULATING', arg1, '+', arg2
        return arg1 + arg2


@memoize
def subtract(arg1, arg2):
    print 'CALCULATING', arg1, '-', arg2
    return arg1 - arg2

def main():
    print subtract(10, 5)
    print subtract(10, 5)

    adder1 = Adder()
    adder2 = Adder()
    print adder1.add(5, 5)
    print adder1.add(5, 5)
    print adder2.add(5, 5)
    print adder2.add(5, 5)

if __name__ == '__main__':
    main()

I can't remember, to be honest. I'm pretty sure that the more well-known memoizer in the Python decorator library was hitting the TypeError exception a lot when I tried it. It may have been because I was passing lists in (which are uncacheable). If you're curious, I'd modify the TypeError to print out the exception rather than just call the function and pretend that nothing happened. I think that it's possibly better behaviour to re-raise the TypeError in that case... if some code assumes that a function is memoized and is therefore O(1), performance can degrade by orders of magnitude if memoization is failing, to the point where the program does not function as expected. There's arguments leaning both ways on this matter, of course, but I think it's a policy question, and should be customizable (e.g. via a decorator argument).

…

On Sep 16, 2011, at 6:09 AM, Dominique wrote: I'm trying to understand your memoize example. From the point of view of being able to wrap both plain functions and class methods, what exactly does it do that http://wiki.python.org/moin/PythonDecoratorLibrary#Memoize doesn't? (I'm still learning decorators and descriptors, so please bear with me.) ## Reply to this email directly or view it on GitHub: https://gist.github.com/267733

Thanks for the response. While trying to work this out I wrote my own, pieced together from various sources and my understanding of how things work. One thing I wanted to do is cache numpy arrays by computing their sha1 digest. My code is at https://gist.github.com/1222577. I'd be interested in any comments.