cfbolz changed the topic of #pypy to: PyPy, the flexible snake (IRC logs: https://botbot.me/freenode/pypy/ ) | use cffi for calling C | the secret reason for us trying to get PyPy users: to test the JIT well enough that we're somewhat confident about it
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<mattip>
lesshaste: np.ndarray.sum is all in c, no python iteration involved
<lesshaste>
cool! (re: release notice)
<lesshaste>
and thanks
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<lesshaste>
distruibute <- typo
<lesshaste>
emissions <- typo
<lesshaste>
"The Matplotlib TkAgg backend now works with PyPy, as do pygame and pygobject." for me matplotlib just works. Maybe make that clear? As I don't have to do anything at all to make it work with pypy
<lesshaste>
not everyone will know what tkagg is and if it is the default
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<exarkun>
is there a pypy-stm-based concurrent programming framework that's well suited to current high-end datacenter servers (perhaps ~32 cores) for I/O-heavy workloads?
<exarkun>
Maybe "I/O-heavy" is somewhat misleading. Perhaps I simply care about CPU-bound processes. I said "I/O-heavy" because I am thinking of the case where you need multiple cores to be able to saturate whatever I/O bus is involved.
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<lesshaste>
lazka, do you mean you have to do something to get matplotlib to work with pypy?
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<lazka>
lesshaste, afaik it only supports specifying one backend atm, so if you have a different one specified in any of the matplotlibrc files or through MPLBACKEND then you have to tell it to use another one
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<lesshaste>
lazka, ok.. all I was saying was that for a normal user it might be helpful just to say "matplotlib works" and put the tkagg detail underneath
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<Rotonen>
exarkun: you'll do more by software architecture allowing for multiprocessing.pool with shared memory workers, pypy-stm is mostly a PoC (and hits dead ends and seeks new approaches - plenty of genuine research effort left there before anything usable for the context you seek in)
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<exarkun>
Rotonen: Yea but multiprocessing.Pool is boring.
<cfbolz>
:-)
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<Rotonen>
exarkun: by what you're doing, you've chosen engineering as a field, at least to some degree, go figure :-)
<arigato>
right now your only choice is to run 32 processes, which costs a lot of RAM with pypy
<arigato>
(potentially)
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<simpson>
Rotonen: 'boring' is maybe a misleading word. Friends don't let friends `import multiprocessing`.
<arigato>
there are some vague thoughts about a solution that looks like independent processes but are actually implemented as theads and share memory
<arigato>
but there is no progress on that
<Rotonen>
'here is a bit of code, here is an input queue, go at it' is a good use case to cater to
<Rotonen>
there is also an undocumented a thread pool in multiprocessing
<Rotonen>
simpson: it's not that bad so long as you have very small intputs and outputs so the IPC-via-pickling does not bite you, or you can design everything to use shared memory
<simpson>
Rotonen: I understand your position. I'm just sticking to the #python party line; I don't want to wish insanity and suffering on anybody.
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<Rotonen>
i've done such things, including but not limited to RPG IV, multiprocessing is fine and fluffy :D
<exarkun>
My choice isn't really between pypy-stm and multiprocessing, anyway. If pypy-stm had made a ton of advances since I last checked in on it, I would be interested in exploring it some more. If not, there's always Haskell.
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<cfbolz>
exarkun: pypy-stm is pretty much dormant at this point, I think
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<lesshaste>
__pv, I already reported that (and others) above :)
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<exarkun>
cfbolz: good to know (though sad), thanks
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<lazka>
lesshaste, agreed, a screenshot/gif might make it even more clear
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<kenaan>
mattip pypy.org[extradoc] a1da300b39d3 /source/download.txt: update sha256 for pypy2.7
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<nanonyme>
Isn't stm-gc mostly dropped at this point in favour or just beating at PyPy until you can rip out the GIL?
<nanonyme>
pypy-stm even
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<arigato>
nobody is doing that
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<nanonyme>
Oh, I must've been misled then
<nanonyme>
That's the impression I got from latest STM-related blog posts
<Rotonen>
nanonyme: i took that more as a noble aim for now as there is no hot lead (or industry desire via funding) on the STM front