On Thu, May 29, 2008 at 9:39 AM, Jesus Cea firstname.lastname@example.org wrote:
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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:
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.