import timeit

"""

A stock of varying computational-intensive functions.

"""

def recursive_fib(n):

if n == 0 or n == 1:

return n

else:

return recursive_fib(n-1) + recursive_fib(n-2)

def memoize(f):

cache = {}

def decorated_function(arg):

if arg in cache:

return cache[arg]

else:

cache[arg] = f(arg)

return cache[arg]

return decorated_function

@memoize

def recursive_fib_cached(n):

if n == 0 or n == 1:

return n

else:

return recursive_fib_cached(n-1) + recursive_fib_cached(n-2)

def iterative_fib(n):

a, b = 0, 1

for i in xrange(n):

a, b = b, a + b

return a

def demonstrate_load(n):

print "* Running 3 variants of fibonacci, set to calculate the {}th fibonacci number...".format(

n

)

test_scenarios = [

('naive recursive implementation', recursive_fib),

('recursive implementation with a cache', recursive_fib_cached),

('iterative implementation', iterative_fib)

]

for test_description, fib_test in test_scenarios:

print "#" * 20

print "Running {} ...".format(test_description)

start_time = timeit.default_timer()

fib_test(n)

end_time = timeit.default_timer()

print "{} took {} seconds to complete".format(test_description, end_time-start_time)

# demonstrate_load(37)