Steven D'Aprano wrote: > I have two code snippets to time a function object being executed. I > expected that they should give roughly the same result, but one is more > than an order of magnitude slower than the other. > > Here are the snippets: > > def timer1(): > timer = time.time > func = lambda : None > itr = [None] * 1000000 > t0 = timer() > for _ in itr: > func() > t1 = timer() > return t1 - t0 > > def timer2(): > timer = time.time > func = lambda : None > itr = [None] * 1000000 > t = 0.0 > for _ in itr: > t0 = timer() > func() > t1 = timer() > t += t1 - t0 > return t > > Here are the results: > > >>>>timer1() > > 0.54168200492858887 > >>>>timer2() > > 6.1631934642791748 > > Of course I expect timer2 should take longer to execute in total, > because it is doing a lot more work. But it seems to me that all that > extra work should not affect the time measured, which (I imagine) should > be about the same as timer1. Possibly even less as it isn't timing the > setup of the for loop. > > Any ideas what is causing the difference? I'm running Python 2.3 under > Linux.
You are including the cost of one call to timer() in each loop: The cost of returning the time from the first call to timer() and the the cost of getting the time in the second call. On my computer with Python 2.4: D:\Projects\CB>python -m timeit -s "import time;timer=time.time" "t=timer()" 1000000 loops, best of 3: 0.498 usec per loop which is almost exactly the same as the difference between timer1() and timer2() on my machine: timer1 0.30999994278 timer2 0.812000274658 using Python 2.4.2 on Win2k. Kent -- http://mail.python.org/mailman/listinfo/python-list
