On Tue, Apr 2, 2013 at 6:15 AM, jmfauth <wxjmfa...@gmail.com> wrote: > Py32 >>>> import timeit >>>> timeit.repeat("'a' * 1000 + 'ẞ'") > [0.7005365263669056, 0.6810694766790423, 0.6811978680727229] >>>> timeit.repeat("'a' * 1000 + 'z'") > [0.7105829560031083, 0.6904999426964764, 0.6938637184431968] > > Py33 > import timeit > timeit.repeat("'a' * 1000 + 'ẞ'") > [1.1484035160337613, 1.1233738895227505, 1.1215708962703874] > timeit.repeat("'a' * 1000 + 'z'") > [0.6640958193635527, 0.6469043692851528, 0.6458961423900007]
This is what's called a microbenchmark. Can you show me any instance in production code where an operation like this is done repeatedly, in a time-critical place? It's a contrived example, and it's usually possible to find regressions in any system if you fiddle enough with the example. Do you have, for instance, a web server that can handle 1000 tps on 3.2 and only 600 tps on 3.3, all other things being equal? ChrisA -- http://mail.python.org/mailman/listinfo/python-list