C
Connelly Barnes
I've been avoiding the timeit module because it seems
overly complicated. I finally coded my own function,
which has the following benefits:
1. Simple
2. Figures out how many times to evaluate the
callable passed to it.
Here's the code:
def pytime(f, *args, **kwargs):
"""Calls f many times to determine the average time
to execute f. Usually accurate to within 3%."""
from time import clock
count = 1
while True:
start = clock()
for i in range(count): f(*args, **kwargs)
end = clock()
T = end - start
if T >= 0.5: break
count *= 2
return T / count
Example:
from math import *
def f(x): return x * x - cos(x)
t = pytime(f, 1.0)
print 'Time to execute f: ', t
print 'Calls to f per second: ', 1.0/t
PS: Try repeating this benchmark with psyco. I get a
70x increase in speed.
Connelly Barnes
overly complicated. I finally coded my own function,
which has the following benefits:
1. Simple
2. Figures out how many times to evaluate the
callable passed to it.
Here's the code:
def pytime(f, *args, **kwargs):
"""Calls f many times to determine the average time
to execute f. Usually accurate to within 3%."""
from time import clock
count = 1
while True:
start = clock()
for i in range(count): f(*args, **kwargs)
end = clock()
T = end - start
if T >= 0.5: break
count *= 2
return T / count
Example:
from math import *
def f(x): return x * x - cos(x)
t = pytime(f, 1.0)
print 'Time to execute f: ', t
print 'Calls to f per second: ', 1.0/t
PS: Try repeating this benchmark with psyco. I get a
70x increase in speed.
Connelly Barnes