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<cfbolz> njs: btw, did you try to see whether your thread problem also happens with the jit turned off?
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<ELFrederich> What things can I use "..." for in cffi? I think I can use them for #define'd integers and strings right?... what about typedefs?
<Alex_Gaynor> arigato: do you have a clue about the GC+lare amounts of __del__ bug?
<arigato> larGe?
<Alex_Gaynor> yes
<arigato> not so far, no
<arigato> though I guess we can find out the reason just by reasoning
<arigato> something like: say you have N megabytes of objects with __del__ and you run a GC
<arigato> immediately afterwards, the N megabytes are still there, and the dels will be called soon, and the N megabytes will only disappear at the next GC
<arigato> at the next GC, there are 2*N megabytes of objects alive
<arigato> though only N survive
<Alex_Gaynor> this description seems like it'd leave us with a steady state of 2N memory usage, when really we see unbounded growth
<arigato> yes, that's also the conclusion I've reached now
<arigato> something is still unclear, I need to be more awake I guess
<Alex_Gaynor> Hehe, more coffee :-)
<Alex_Gaynor> Err, I guess it's the evening for you, not the morning.
<arigato> yup
<Alex_Gaynor> Do objects with finalizers go to the nursery, or directly to the older genration?
<arigato> the problem might be that, the less often we run major GCs, the largest the amount of surviving objects; and the largest the amount of surviving objects, the less often we run the GC
<arigato> they go directly to the old generation, because they will always survive the next major GC anyway
<arigato> s/largest/larger
<Alex_Gaynor> if I run my program with `PYPYLOG=gc:-` I see lots of gc-minor, but no gc-major
<Alex_Gaynor> also gc-collect-step
<Alex_Gaynor> it's almost entirely gc-minor though
<arigato> gc-collect-step is a major GC (one incremental step)
<Alex_Gaynor> Ok. They seem rare, perhaps they just can't keep up?
<arigato> yes, as expected, for some reason the major GCs don't run often enough and memory grows (it may be the cause or just a symptom)
<Alex_Gaynor> Can you think of an easy example class with a light finalizer, I want to verify if it affects them
<arigato> files, I think
<arigato> ...no
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<Alex_Gaynor> array.array
<arigato> yes
<Alex_Gaynor> ok, light finalizers are fine
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<cfbolz> Alex_Gaynor: I suspect because they don't get resurrected, so they don't make the major GC rarer
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<cfbolz> arigato: I suspects the objects with __del__ that survive another round to get their finalizer called shouldn't count towards one of the limits, or at least shouldn't lead to increased heap sizes
<arigato> cfbolz: likely, but I'd like to understand exactly why
<cfbolz> right
<cfbolz> randomly changing some of the details seems not great
<arigato> ah, I may get it
<arigato> say we run one major GC after the memory usage gets to 2x what it was at the previous GC
<arigato> say there are 1MB of regular long-lived objects around
<arigato> add 1MB of objects with dels
<arigato> gc, there are now 2MB of objects
<arigato> next limit is thus 4MB
<arigato> at next gc, there are thus 2MB of objects with del
<arigato> so 3MB of surviving objects
<arigato> next limit is 6
<arigato> so there are 3MB of new objects with del
<arigato> 4MB survive
<arigato> etc.
<Alex_Gaynor> so we have fibonacci growth :-)
<arigato> no, I think it's linear
<cfbolz> arigato: we should be able to write a direct test for that?
<arigato> the limit grows by 1MB at every major GC
<arigato> (or no, the limit grows by 2MB, and the size immediately after GC grows by 1MB)
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<arigato> cfbolz: I think so, but /me -> away
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<Cheery> I noticed myself worrying about dictionary/object access.
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<Cheery> so I guess it'd be nice time to get introduced to what kind of optimizations can I get on dicts?
<cfbolz> Cheery: mostly dict strategies
<cfbolz> but you need to implement those yourself
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<kenaan> rlamy py3.5 9068d4152e3f /pypy/module/array/: Make slices of array memoryviews usable as writable buffers if contiguous.
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<arigato> Cheery: if you're talking about the JIT, there are a few optimizations that you get---but the easiest is to try it out by looking at, and trying out more examples inspired from, jit/metainterp/test/test_dict.py
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<cfbolz> arigato: I might try to write a test. would write a direct test? or an lltyped one?
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<arigato> probably lltyped, a direct test is messy to write with finalizers
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<cfbolz> yes, seems there is no such thing atm
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<cfbolz> ok, I give up
<cfbolz> too warm to think
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<Cheery> agreed
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<kenaan> rlamy py3.5 51cd15a0c2d6 /extra_tests/test_decimal.py: remove unittest cruft
<ELFrederich> arigato: so if I have in my header file "typedef unsigned int tag_t;" can I do "typedef ... tag_t;"? or do I have to put "int" somewhere in there?
<arigato> ELFrederich: it's explained on that link
<arigato> see the last paragraph
<ELFrederich> arigato: now I'm more confused ;-)
<ELFrederich> first sentence: Currently, it is not supported to find automatically which of the various integer or float types you need at which place.
<ELFrederich> second sentence: If a type is named, and an integer type, then use typedef int... the_type_name;.
<arigato> right, I should add "except in this case:" between the two sentences
<ELFrederich> so at first it says it's not supported to automatically figure out the various integer types... then it says if your type is one of the various integer types you can use int...
<ELFrederich> arigato: still confused, even if you added "except in this case:"... when would a type not be named?
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<kenaan> rlamy py3.5 f2b370578863 /: Use correct implementation for Decimal.compare_total{,_mag}(). Fixes #2586 and #2587
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<kenaan> arigo cffi/cffi 0c3756872e68 /doc/source/cdef.rst: Expand this paragraph
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<arigato> ELFrederich: a "named" type is one that you name with typedef. An "unnamed" type is, well, all other cases
<arigato> e.g. the type of an argument, a return type, the type T in "typedef T *foo;" etc.
<arigato> so, e.g., int[3] or void(*)(int, int)
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<Cheery> I guess I found a bug that was caused by bad coding on my part, and an update in PyPy
<Cheery> this causes a situation that the interface(null) != null
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<Cheery> although it's clearly what I meant.
<Cheery> the logic favors how PyPy handles it now though.
<Cheery> so I added a new class for 'null' and made it wrap from that.
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<njs> cfbolz: it still happens with --jit off
<njs> cfbolz: (assuming I am successfully disabling the jit)
<njs> ...I guess the part where I'm running with coverage gathering enabled probably disables the jit anyway?
<kenaan> arigo pypy.org[extradoc] 99c987848217 /don1.html: update the values
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<kenaan> wlav default a4013f68eff6 /pypy/module/cppyy/backend/create_cppyy_package.py: add script to create PyPI package from cppyy and stripped-down ROOT/Cling sources
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<raynold> ahh it's a wonderful day
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