Nick Coghlan wrote:
> M.-A. Lemburg wrote:
>> Still, here's the timeit.py measurement of the PythonFunctionCall
>> test (note that I've scaled down the test in terms of number
>> of rounds for timeit.py):
>>
Python 2.5 as of last night:
>> 10 loops, best of 3: 21.9 msec per loop
>> 10 loops, best of 3: 21.8 msec per loop
>> 10 loops, best of 3: 21.8 msec per loop
>> 10 loops, best of 3: 21.9 msec per loop
>> 10 loops, best of 3: 21.9 msec per loop
Python 2.4:
>> 100 loops, best of 3: 18 msec per loop
>> 100 loops, best of 3: 18.4 msec per loop
>> 100 loops, best of 3: 18.4 msec per loop
>> 100 loops, best of 3: 18.2 msec per loop
>>
>> The pybench 2.0 result:
>>
>> PythonFunctionCalls: 130ms 108ms +21.3% 132ms 109ms +20.9%
>>
>> Looks about right, I'd say.
>
> If the pybench result is still 2.5 first, then the two results are
> contradictory - your timeit results are showing Python 2.5 as being
> faster (assuming the headings are on the right blocks of tests).
<sigh> I put the headings for the timeit.py output on the
wrong blocks. Thanks for pointing this out.
Anyway, try for yourself. Just add these lines to pybench/Call.py
at the end and then run Call.py using Python 2.4 vs. 2.5:
### Test to make Fredrik happy...
if __name__ == '__main__':
import timeit
timeit.TestClass = PythonFunctionCalls
timeit.main(['-s', 'test = TestClass(); test.rounds = 1000',
'test.test()'])
--
Marc-Andre Lemburg
eGenix.com
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