Hi Nathaniel - this if this solution can be made performant, than I would be more than satisfied.
I think this would require removing "func" from the "task tuple", and storing the "func" "once per worker" somewhere globally (maybe a class attribute set post-fork?). This also has the beneficial outcome of increasing general performance of Pool.map and friends. I've seen MANY folks across the interwebs doing things like passing instance methods to map, resulting in "big" tasks, and slower-than-sequential parallelized code. Parallelizing "instance methods" by passing them to map, w/o needing to wrangle with staticmethods and globals, would be a GREAT feature! It'd just be as easy as: Pool.map(self.func, ls) What do you think about this idea? This is something I'd be able to take on, assuming I get a few core dev blessings... On Thu, Oct 4, 2018 at 6:15 AM Nathaniel Smith <n...@pobox.com> wrote: > On Wed, Oct 3, 2018 at 6:30 PM, Sean Harrington <seanhar...@gmail.com> > wrote: > > with Pool(func_kwargs={"big_cache": big_cache}) as pool: > > pool.map(func, ls) > > I feel like it would be nicer to spell this: > > with Pool() as pool: > pool.map(functools.partial(func, big_cache=big_cache), ls) > > And this might also solve your problem, if pool.map is clever enough > to only send the function object once to each worker? > > -n > > -- > Nathaniel J. Smith -- https://vorpus.org >
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