Memoized fibonacci in Python

memoized.py

# https://dbader.org/blog/python-memoization
# Example learned from there

def memoize(func):

    cache = dict()

    def memoized_func(*args):
        if args in cache:
            return cache[args]
        result = func(*args)
        cache[args] = result
        return result

    return memoized_func



def fibonacci(N):
    if N == 0:
        return 0
    elif N == 1:
        return 1
    return  fibonacci(N-1) + fibonacci(N-2)


import timeit


print("Standard Fibonacci -")

print(timeit.timeit('fibonacci(35)',globals=globals(), number=1))

print("Memoized Fibonacci -")
memoized_fib = memoize(fibonacci)

# not much speed gain first time.
print(timeit.timeit('memoized_fib(35)',globals=globals(), number=1))
print("Again -  Memoized Fibonacci -")

# huge speedup with cache use
print(memoized_fib.__closure__[0].cell_contents)
print(timeit.timeit('memoized_fib(35)',globals=globals(), number=1))