On Dec 1, 10:08 am, Joshua Kugler <[EMAIL PROTECTED]> wrote: > [I tried googling for this, didn't find anything relevant.] > > We've recently been doing some profiling on a project of ours. It runs > quite fast on Linux but *really* bogs down on Windows 2003. We initially > thought it was the simplejson libraries (we don't use the C extensions) but > profiling proved otherwise. > > We have a function that does some runtime imports via calls to __import__. > We ran 1000 iterations (we used cProfile) of the application (web app). > There were eight calls to __import__ per iteration, so 8000 calls total. > Identical hardware, by the way. > > On Linux (Debian Etch, Python 2.5.1) > Total time was 2.793 CPU seconds, with __import__ using 1.059 seconds of > that. So, 37% of the time was spent in import. Not great, but not a show > stopper. > > On Windows 2003 (R2, Python 2.5.1) > Total time was 18.532 CPU seconds, with __import__ using 16.330 seconds > (88%) of that. > > So, Linux spends 1.734 seconds on non-import activities, and Windows spends > 2.202 seconds on non-import activities. Pretty close. But 16.3 seconds on > import!? > > Is this a known deficiency in Windows' Python import calls, or is there > something deeper going on here? > > Pointers, suggestions, and URLs welcome. > > j
What modules are you __import__ing, and what is platform-dependent in each? -- http://mail.python.org/mailman/listinfo/python-list