From the example at: http://ujihisa.blogspot.com/2010/11/memoized-recursive-fibonacci-in-python.html How do I access the cache of fibonacci numbers after running the function?

Python Memoization question

def memoize(f):
    cache = {}
    def decorated_function(*args):
        if args in cache:
            return cache[args]
        else:
            cache[args] = f(*args)
            return cache[args]
    return decorated_function

@memoize
def fib(n):
    return n if n < 2 else fib(n-2) + fib(n-1)


SOLUTION: Assign the local variable to an attribute after the function definition before returning it.

def memoize(f):
    cache = {}
    def decorated_function(*args):
        if args in cache:
            return cache[args]
        else:
            cache[args] = f(*args)
            return cache[args]
    decorated_function.cache = cache
    return decorated_function

@memoize
def fib(n):
    return n if n < 2 else fib(n-2) + fib(n-1)



print fib(10)
print fib.cache