Method much slower than function?

[Gabriel Genellina]

En Thu, 14 Jun 2007 05:54:25 -0300, Francesco Guerrieri  
<f.guerrieri at gmail.com> escribió:

> On 6/14/07, Peter Otten <__peter__ at web.de> wrote:
>> Gabriel Genellina wrote:
>> > ...
>> > py> print timeit.Timer("f2()", "from __main__ import  
>> f2").repeat(number=1)
>> > [0.42673663831576358, 0.42807591467630662, 0.44401481193838876]
>> > py> print timeit.Timer("f1()", "from __main__ import  
>> f1").repeat(number=1)
>> >
>> > ...after a few minutes I aborted the process...
>>
>> I can't confirm this.
>
> [...]
>
>> $ python2.5 -m timeit -s 'from join import f1' 'f1()'
>> 10 loops, best of 3: 212 msec per loop
>> $ python2.5 -m timeit -s 'from join import f2' 'f2()'
>> 10 loops, best of 3: 259 msec per loop
>> $ python2.5 -m timeit -s 'from join import f3' 'f3()'
>> 10 loops, best of 3: 236 msec per loop
>
> On my machine (using python 2.5 under win xp) the results are:
>>>> print timeit.Timer("f2()", "from __main__ import f2").repeat(number =  
>>>> 1)
> [0.19726834822823575, 0.19324697456408974, 0.19474492594212861]
>>>> print timeit.Timer("f1()", "from __main__ import f1").repeat(number =  
>>>> 1)
> [21.982707133304167, 21.905312587963252, 22.843430035622767]
>
> so it seems that there is a rather sensible difference.
> what's the reason of the apparent inconsistency with Peter's test?

I left the test running and went to sleep. Now, the results:

C:\TEMP>python -m timeit -s "from join import f1" "f1()"
10 loops, best of 3: 47.7 sec per loop

C:\TEMP>python -m timeit -s "from join import f2" "f2()"
10 loops, best of 3: 317 msec per loop

C:\TEMP>python -m timeit -s "from join import f3" "f3()"
10 loops, best of 3: 297 msec per loop

Yes, 47.7 *seconds* to build the string using the += operator.
I don't know what's the difference: python version (this is not 2.5.1  
final), hardware, OS... but certainly in this PC it is *very* important.
Memory usage was around 40MB (for a 10MB string) and CPU usage went to 99%  
(!).

-- 
Gabriel Genellina