On Oct 8, 4:24 am, [EMAIL PROTECTED] (Alex Martelli) wrote: > Licheng Fang <[EMAIL PROTECTED]> wrote: > > ... > > > Python Tutorial says an empty class can be used to do this. But if > > namespaces are implemented as dicts, wouldn't it incur much overhead > > if one defines empty classes as such for some very frequently used > > data structures of the program? > > Just measure: > > $ python -mtimeit -s'class A(object):pass' -s'a=A()' 'a.zop=23' > 1000000 loops, best of 3: 0.241 usec per loop > > $ python -mtimeit -s'a=[None]' 'a[0]=23' > 10000000 loops, best of 3: 0.156 usec per loop > > So, the difference, on my 18-months-old laptop, is about 85 nanoseconds > per write-access; if you have a million such accesses in a typical run > of your program, it will slow the program down by about 85 milliseconds. > Is that "much overhead"? If your program does nothing else except those > accesses, maybe, but then why are your writing that program AT ALL?-) > > And yes, you CAN save about 1/3 of those 85 nanoseconds by having > '__slots__=["zop"]' in your class A(object)... but that's the kind of > thing one normally does only to tiny parts of one's program that have > been identified by profiling as dramatic bottlenecks, to shave off the > last few nanoseconds in the very last stages of micro-optimization of a > program that's ALMOST, but not QUITE, fast enough... knowing about such > "extreme last-ditch optimization tricks" is of very doubtful value (and > I think I'm qualified to say that, since I _do_ know many of them...:-). > There ARE important performance things to know about Python, but those > worth a few nanoseconds don't matter much. > > Alex
This is enlightening. Surely I shouldn't have worried too much about performance before doing some measurement. -- http://mail.python.org/mailman/listinfo/python-list
