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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<kenaan> arigo default 937d78fe0a37 /rpython/rlib/rposix_environ.py: Issue #2840 Fix multithreading issues in calls to setenv()
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<arigato> plan_rich (for the logs): you have a runaway twistd process on baroquesoftware.com, gobbling all the memory. I killed it
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<kenaan> wlav cppyy-packaging 068d5604f6e9 /pypy/module/_cppyy/interp_cppyy.py: method template improvements
<kenaan> wlav cppyy-packaging c68cd6b1c308 /pypy/module/_cppyy/: further support for templated methods and for sfinae
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<kenaan> mattip default d246497b019e /pypy/module/cpyext/include/pyconfig.h: add missing defines and typedefs for numpy, pandas on MSVC
<kenaan> mattip default 109e417f3057 /pypy/doc/windows.rst: try to describe setting up a current MSVC build env for py3, until it changes
<kenaan> mattip py3.5 2e791fab4895 /: merge default into branch
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<tsutsumi> Hey there, I'm trying out running pypy3 in production, and I've noticed that both memory and CPU consumption have increased with the change
<tsutsumi> to give some background, my application basically polls messages from zmq (via pyzmq), parses a json object, matches against a list of regexes, then renders a string and sends that to a tcp socket
<tsutsumi> the increase in memory isn't really surprising to me because, as I understand it, the GC isn't reference counted so collection doesn't happen as aggressively for short-lives objects, and there's probably a JIT component there.
<tsutsumi> the cpu is a little surprising. What I see is CPU usage increase in a sawtooth pattern, until hitting 100% cpu utilization on the box
<tsutsumi> to note, I found an issue where we're not really allocating enough memory for pypy: it starts to consume swap pretty heavily after an hour or two
<tsutsumi> what's a good way to understand this better? and is this expected?
<simpson> Once you start swapping, you're going to have a bad time.
<simpson> I don't know enough about PyPy3 to suggest where to start looking. I'd probably look for some sort of heap analysis; I don't know if meliae works on PyPy3 though.
<tsutsumi> actually, I took another look, and it looks like the cpu increase maxes out at 100% before we start eating swap.
<tsutsumi> this further confuses me then. In python2.7 we have solid cpu utilization across the board
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<simpson> That is a little interesting.
<tsutsumi> I'm thinking at this point the benefit of pypy is reduced because it does a lot of work on the c and kernel layer already, pulling from tcp sockets and zmq being written in c
<tsutsumi> but I'm wondering if the CPU increase has something to do with GC: we create a lot of garbage quickly (since we're reading data, processing it, and not using it afterward)
<simpson> You can play with the GC configuration: http://doc.pypy.org/en/latest/gc_info.html
<tsutsumi> thanks! I've seen that, and we've tweaked a couple things. I was just hoping someone's encountered this before and could help guide on what a good next step might be, before we start tweaking a bunch
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