On Thu, May 29, 2008 at 9:39 AM, Jesus Cea <[EMAIL PROTECTED]> wrote: > -----BEGIN PGP SIGNED MESSAGE----- > Hash: SHA1 > > Could you possibly extend the PEP to also document performance when, for > instance, passing "big" objects via a queue, or sending "Events" back, > testing "thread.isAlive()", and stuff like that?. What about mutexes? > (not to protect shared objects, but files, for example). > > A share-nothing without data-passing doesn't need a new module :). I'm > interesting in an almost direct conversion from thread module, and so > I'm interested in knowing performance data outside "pyprocessing" sweet > point (that is, "fire and forget" code, with little communication). > > How is implemented "thread.setDaemon()"?.
Alec Thomas sent me a bit of code to benchmark Queue-based object passing performance which I will incorporate when I get a chance. As for the provided examples/benchmarks - I can work on adding more, or if you want - as linked in the PEP, Oudkerk already has some of those outlined in a benchmark script here: http://pyprocessing.berlios.de/examples/benchmarks.py I chose not to recreate his tests directly, rather I chose to link to them. I will work on adding Queue-based numbers. I also wouldn't say I picked the "sweet spot" for the module - rather I picked the poor-spot for the threading module (parallel, python-based crunching). I do again want to point out that the goal is not to pick on threading, but to offer an API which mimics the existing threading API that allows for actual multi-processor/core usage. -jesse _______________________________________________ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
