cfbolz changed the topic of #pypy to: #pypy PyPy, the flexible snake | IRC logs: and | Matti: I made a bit of progress, the tests now only segfault towards the end
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<cfbolz> Woops I broke pickling
<cfbolz> (of course
<cfbolz> )
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<mattip> cfbolz: there is also a newly-failing rpython test on the linux64 buildbot
<mattip> jit.backend.x86.test.test_recursive TestRecursive.().test_inline_trace_limit
<cfbolz> yep, that's a weird one
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<ronan> I've been looking at the pyston benchmark (discussed at ). The (somewhat) good news is that we're eventually faster than CPython and almost as fast as Pyston, the bad news is that it takes ~15000 iterations.
<cfbolz> ronan: oh, wow
<cfbolz> ronan: I had looked at it for like five minutes during the weekend, sqlalchemy is really quite tough for us in some places :-(
<cfbolz> but it sounds like a good goal to work on maybe?
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<f4at> I'm playing with PyPy. I know almost nothing :'(
<f4at> Is It possible to run pypy with jit without recompiling?
<cfbolz> f4at: hey, welcome!
<f4at> hello :)
<cfbolz> f4at: anything that interests you in particular?
<cfbolz> the JIT can unfortunately not be tested without recompiling, only behaviour can
<f4at> Well I want to play with the jit. But I don't think I'm qualified yet. So, I thought about optimising some features Like factorials and decimals because they are pretty slow. And the reason telco and bm_mdp and slower in pypy
<f4at> are*
<ronan> cfbolz: I haven't looked much at the server-side, I was surprised to see that the client side seems to take a significant amount of time and also warms up very slowly
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<cfbolz> f4at: it's possible that the fractions thing is not jit related
<f4at> Oh I think its pure python
<cfbolz> f4at: yes, but it uses huge integers
<f4at> cfbolz: PyPy is pretty fast (big fun) It loses to CPython only when the benchmark uses features that are not well optimised in PyPy. I was suprised when I found out that filter is x30 is slower than list comprehension.
<f4at> cfboltz: any ideas why sort with key is still slower than Cpython?
<f4at> cfboltz: I copied fractions source code from Cpython to PyPy. PyPy is now faster than CPython ¯\_( ͡❛ ͜ʖ ͡❛)_/¯
<cfbolz> f4at: oh what!
<f4at> :)
<cfbolz> f4at: so diff it and see what the difference it
<f4at> cfbolz: okay sure
<cfbolz> f4at: is the python file from a newer python version
<cfbolz> ?
<f4at> cfbolz: yes, Python 3.10
<f4at> I have older versions installed I will test them
<f4at> Well, didn't work with Python 3.7.
<f4at> cfbolz: I guess, Fractions is not the reason the benchmark was slow after all
<cfbolz> f4at: what do you mean "didn't work"?
<cfbolz> to me it sounds like there maybe was an optimization in the file in 3.10 that we could steal
<f4at> Didn't improve performance
<f4at> Yes
<cfbolz> f4at: maybe this is the diff?
<f4at> cfbolz: probably
<cfbolz> f4at: so, sounds like a worthy backport to pypy I would say
<cfbolz> I mean we will probably pick it up when we start working on 3.10 (hopefully later this year)
<cfbolz> but in the meantime, it looks like it's purely an optimization so we can steal it ;-)
<cfbolz> f4at: so, good find
<f4at> cfboltz: Thank you :), Actually the older version is faster in Cpython but the newer version is faster PyPY
<f4at> cfbolz: THe older version is x1.6 faster in CPython, the newer version is x1.4 faster in Python. Atleast in my test case
<f4at> faster in PyPy*
<cfbolz> ok
<cfbolz> f4at: I just sent you a private message, did you see that?
<f4at> ye :)
<ronan> hmm, I guess we should be a bit more willing to modify the stdlib. CPython often write it with a mindset of "every bytecode costs the same", which is quite wrong on CPython and super-wrong on PyPy
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<f4at> cfbolz: I think I found a solution for Deciaml slow performance.
<f4at> There is 2 versions of the decimal library. 1 is pure python the other is built-in switching the built-in one with the pure python versions.
<f4at> Telco benchmark is now 13 times faster than Cpython, it was 1.65 slower than CPython. More than x20 speed up.
<Corbin> !
<f4at> The pure python version is _pydecimal
<f4at> nevermind me, did a mistake forgot to change cpython to decimal :'(
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