On 19 juin, 21:05, Christian Heimes <li...@cheimes.de> wrote: > I've seen a single Python process using the full capacity of up to 8 > CPUs. The application is making heavy use of lxml for large XSL > transformations, a database adapter and my own image processing library > based upon FreeImage.
interesting... > Of course both lxml and my library are written with the GIL in mind. > They release the GIL around every call to C libraries that don't touch > Python objects. PIL releases the lock around ops as well (although it > took me a while to figure it out because PIL uses its own API instead of > the standard macros). reportlab has some optional C libraries that > increase the speed, too. Are you using them? I don't. Or maybe I did, but I have no clue what to test. Do you have a real example, some code snippet to can prove/show activity on multiple core ? I accept your explanation, but I also like experiencing :) > By the way threads are evil > (http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-1.pdf) and > not *the* answer to concurrency. I don't see threads as evil from my little experience on the subject, but we need them. I'm reading what's happening in the java world too, it can be interesting. Olivier -- http://mail.python.org/mailman/listinfo/python-list
