cfbolz changed the topic of #pypy to: PyPy, the flexible snake (IRC logs: https://botbot.me/freenode/pypy/ ) | use cffi for calling C | "nothing compares to the timeshifter, my personal polar expedition in software" - pedronis
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* mattip uploading binary packages
<mattip> it would be nice if we could get ppc binaries built for the release
* mattip bbl
<fijal> mattip: hi matti!
<mattip> hi
<fijal> mattip: I think it's a bit secondary tbh, but we can ask Rh0lite
<fijal> Rhy0lite
<fijal> do you want me to?
<mattip> ok, Armin usually does it
<mattip> that is he usually makes the builds
<fijal> right, maybe we can wait a few days for that?
<fijal> we're at a conference for the next 2 days
<mattip> np
<fijal> (and at a conference sprint for the following two)
<mattip> right, that's why I wanted to push the release out
<fijal> mattip: did I say "thank you for your amazing work" recently?
<fijal> I would say PPC builds can wait a few dats
<fijal> days
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<mattip> comments? ideas?
* fijal looks
<fijal> mattip: I think language and formatting needs work
<fijal> like, start with highlights
<fijal> * 3.5 beta release
<fijal> * 2.7 release
<fijal> * numpy and pandas working
<fijal> and then shuffle the rest, with some edits to the bottoom
<fijal> like cpyext improvements
<fijal> note that there are very serious cpyext improvements which are on trunk, but didn't land in the release
<fijal> and more are coming
<mattip> right, but we should have benchmarks as proof, even like "numpy tests now run x% faster"
<mattip> fijal: do you think we should delay the release to include the improvements?
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<ronan> mattip: we (anto and I) don't think it's worth it
<mattip> cool
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<mattip> pypy.org updated, blog post published
<mattip> congrats to all
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<fijal> yay!
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* squeaky_pl putting portable builds
<fijal> squeaky_pl: thanks!
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<squeaky_pl> Portable PyPy 5.9 for many linux distros is now out: https://github.com/squeaky-pl/portable-pypy
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<tos9> squeaky_pl: Awesome! Thanks as always.
* tos9 rolls it out to QA
<fijal> ok, so what the fuck.....
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<lesshaste> pretty awesome about numpy and pandas!!
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<fijal> lesshaste: I actually wonder how important that is
<lesshaste> fijal, if pypy + numpy runs in the same speed as cpython + numpy I think very
<lesshaste> but if it's many times slower, then not so much
<fijal> it's the usual case of "it depends"
<lesshaste> you mean the speed varies a lot depending on what you are doing?
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<fijal> yeah
<lesshaste> is it still expensive to access individual elements of an array?
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<fijal> I presume so, but it's also heavily discouraged on cpython
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* LarstiQ needs to try again running his pandas based environment on pypy
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