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Python24 introduces the function decorator that lends itself nicely to the timing of a function. As a sample function we are using the ever popular and rather stodgy prime number generator. The prime number generator seems to exist only to fluster students and to make niggling comparisons of the speed of computer languages.

``````# time a function using time.time() and the a @ function decorator
# tested with Python24    vegaseat    21aug2005

import time

def print_timing(func):
def wrapper(*arg):
t1 = time.time()
res = func(*arg)
t2 = time.time()
print '%s took %0.3f ms' % (func.func_name, (t2-t1)*1000.0)
return res
return wrapper

# declare the @ decorator just before the function, invokes print_timing()
@print_timing
def getPrimeList(n):
""" returns a list of prime numbers from 2 to < n using a sieve algorithm"""
if n < 2:  return []
if n == 2: return [2]
# do only odd numbers starting at 3
s = range(3, n+1, 2)
# n**0.5 may be slightly faster than math.sqrt(n)
mroot = n ** 0.5
half = len(s)
i = 0
m = 3
while m <= mroot:
if s[i]:
j = (m*m-3)//2
s[j] = 0
while j < half:
s[j] = 0
j += m
i = i+1
m = 2*i+3
return [2]+[x for x in s if x]

if __name__ == "__main__":
print "prime numbers from 2 to <10,000,000 using a sieve algorithm"
primeList = getPrimeList(10000000)
time.sleep(2.5)

"""
my output -->
prime numbers from 2 to <10,000,000 using a sieve algorithm
getPrimeList took 4750.000 ms
"""``````

Note: If you have Windows, it is better to use the time.clock() function (updates 1000 times per second) rather than time.time() (updates 18.2 times per second).

Vegaseat, to keep primes from going over n, replace line
s = range(3, n+2, 2)
with
s = range(3, n+1, 2)

Henri

Oh thanks Henri, I corrected this oversight.

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