Mailman 3 May 2014 - pypy-dev

Cross-post from python-ideas: Compressing the stack on the fly
by Ram Rachum 28 Jul '14

28 Jul '14

Hi guys, I made a post on the Python-ideas mailing list that I was told might be relevant to Pypy. I've reproduced the original email below. Here is the thread on Python-ideas with all the discussion.<https://groups.google.com/forum/?fromgroups#!topic/python-ideas/hteGSNTyC_4> -------------- Hi everybody, Here's an idea I had a while ago. Now, I'm an ignoramus when it comes to how programming languages are implemented, so this idea will most likely be either (a) completely impossible or (b) trivial knowledge. I was thinking about the implementation of the factorial in Python. I was comparing in my mind 2 different solutions: The recursive one, and the one that uses a loop. Here are example implementations for them: def factorial_recursive(n): if n == 1: return 1 return n * factorial_recursive(n - 1) def factorial_loop(n): result = 1 for i in range(1, n + 1): result *= i return result I know that the recursive one is problematic, because it's putting a lot of items on the stack. In fact it's using the stack as if it was a loop variable. The stack wasn't meant to be used like that. Then the question came to me, why? Maybe the stack could be built to handle this kind of (ab)use? I read about tail-call optimization on Wikipedia. If I understand correctly, the gist of it is that the interpreter tries to recognize, on a frame-by-frame basis, which frames could be completely eliminated, and then it eliminates those. Then I read Guido's blog post explaining why he doesn't want it in Python. In that post he outlined 4 different reasons why TCO shouldn't be implemented in Python. But then I thought, maybe you could do something smarter than eliminating individual stack frames. Maybe we could create something that is to the current implementation of the stack what `xrange` is to the old-style `range`. A smart object that allows access to any of a long list of items in it, without actually having to store those items. This would solve the first argument that Guido raises in his post, which I found to be the most substantial one. What I'm saying is: Imagine the stack of the interpreter when it runs the factorial example above for n=1000. It has around 1000 items in it and it's just about to explode. But then, if you'd look at the contents of that stack, you'd see it's embarrassingly regular, a compression algorithm's wet dream. It's just the same code location over and over again, with a different value for `n`. So what I'm suggesting is an algorithm to compress that stack on the fly. An algorithm that would detect regularities in the stack and instead of saving each individual frame, save just the pattern. Then, there wouldn't be any problem with showing informative stack trace: Despite not storing every individual frame, each individual frame could still be accessed, similarly to how `xrange` allow access to each individual member without having to store each of them. Then, the stack could store a lot more items, and tasks that currently require recursion (like pickling using the standard library) will be able to handle much deeper recursions. What do you think? Ram.

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europython sprints?
by Martin Matusiak 01 Jul '14

01 Jul '14

Hi, I'm wondering if there will be pypy sprints at Europython this year (?) And if so, which are the principal topics (I assume stm is one of them..)? Thanks, Martin

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Getting involved
by Travis Jensen 03 Jun '14

03 Jun '14

Hi, I've been following pypy for a while and have thought it would be fun to get involved. Recently, I've been wondering what python with tail call optimization would look like (I'm disgruntled by GVR's decision :), and realized this might be a good way for me to get involved in pypy. So a few questions: First, is this within the realms of (reasonable) possibility? I don't want to dive into something that is not realistically possible. Given I'm a noob in the pypy world, where would be a good place to start getting my feet wet on this? Thanks. tj

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Issue #1783: 50x higher memory usage with array.array (compared to CPython) (pypy/pypy)
by Konstantin Lopuhin 31 May '14

31 May '14

New issue 1783: 50x higher memory usage with array.array (compared to CPython) https://bitbucket.org/pypy/pypy/issue/1783/50x-higher-memory-usage-with-arr… Konstantin Lopuhin: I am trying to initialize a large array with an iterator (for example, where all values are zero initially), and PyPy consumes much more memory than CPython: ``` #!bash $ python Python 2.7.6 (v2.7.6:3a1db0d2747e, Nov 10 2013, 00:42:54) [GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin $ /usr/bin/time -l python -c "from array import array; array('b', (0 for _ in xrange(10000000)))" 1.52 real 1.50 user 0.01 sys 14954496 maximum resident set size 0 average shared memory size 0 average unshared data size 0 average unshared stack size 4131 page reclaims 0 page faults 0 swaps 0 block input operations 0 block output operations 0 messages sent 0 messages received 0 signals received 0 voluntary context switches 7 involuntary context switches $ pypy Python 2.7.6 (394146e9bb67, May 08 2014, 16:45:59) [PyPy 2.3.0 with GCC 4.2.1 Compatible Apple LLVM 5.0 (clang-500.2.79)] on darwin $ /usr/bin/time -l pypy -c "from array import array; array('b', (0 for _ in xrange(10000000)))" 1.47 real 1.13 user 0.32 sys 736083968 maximum resident set size 0 average shared memory size 0 average unshared data size 0 average unshared stack size 223518 page reclaims 1 page faults 0 swaps 0 block input operations 20 block output operations 0 messages sent 0 messages received 0 signals received 0 voluntary context switches 4 involuntary context switches ```

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hunting for reason of a failing test (rpython/memory/test/)
by Gregor Wegberg 29 May '14

29 May '14

Hi, I'm working on an object pinning feature for incminimark right now. There is always one failing test (depending on the platform) in rpython/memory/test/test_incminimark_gc.py which I just can't solve. I'd appreciate any form of help. Even if it is just a "I may imagine that it is connected to X and Y" :-) Basic resources: - all my changes are in the following fork & branch: https://bitbucket.org/groggi/pypy/branch/gc-incminimark-pinning - my `gc-incminimark-pinning` branch is based on PyPy's `release-2.3.x` branch - pinning should work for "simple" objects, i.e. basically RPython strings. GC cards are not supported. More tests are needed of course. - I am "gregor_w" in #pypy, so feel free to ping me The following test results I get on the three major platforms running pytest on /rpython/memory/test: - Windows (Visual Studio 2013 native tools): http://paste.pound-python.org/show/LPw4eCHE1EsfFTykQkWA/ => failing test: test_print_leak - OS X (clang): http://paste.pound-python.org/show/l85sUl56UCMDVxu1vrSS/ => failing test: test_tagged_id - Ubuntu (gcc): http://paste.pound-python.org/show/oAYctWSzF3OpqLtlBlUX/ => failing tests: test_tagged_id I have no idea why on Windows I get an other test to fail and test_tagged_id passes. However, maybe this gives you a hint. I imagine that one of the following three reasons are responsible for the failing tests: 1.) I did some address calculations wrong inside incminimark. However, I'd expect to see way more failing tests in this case. 2.) My changes to get the GC transformation working with pin()/unpin() or the translation for the same two functions is wrong, so there is some error in rpython/memory/gctransform/framework.py, rpython/memory/gctransform/transform.py, rpython/rtyper/llinterp.py or rpython/rtyper/lltypesystem/lloperation.py. On the other hand I can translate PyPy with a PyPy binary containing my changes -- so this seems also somehow impossible?! 3.) It is some side effect as a result of the following changeset (llarena and lltype modification): https://bitbucket.org/groggi/pypy/commits/84898085a09814d1ec4f6b2b0d4202c7a… I tried my best to check all three explanations and some more. However, I just can't see what is going wrong. What I observed (only on OS X right now): - changing `taggedpointers` to False solves the problem, i.e. test passes - splitting both `print` statements inside the `fn` function into six prints with only one parameter (`print a, b, c` -> `print a\n print b\n print c`) leads to an error while executing the `print x` - splitting the `print` statements again as before *and* setting `taggedpointers` to False leads to the same error as the original version of the test without modifications. After 13-15 work hours trying to solve the bug I'm just lost. I have the feeling that it is something stupid and/or simple but my lack of PyPy knowledge stops me from seeing it. Any help is very much appreciated. Cheers and thank you in advance, Gregor

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Issue #1782: Test case where pypy is more than 4x slower than CPython (pypy/pypy)
by estama 29 May '14

29 May '14

New issue 1782: Test case where pypy is more than 4x slower than CPython https://bitbucket.org/pypy/pypy/issue/1782/test-case-where-pypy-is-more-tha… estama: I've found a small example where PyPy is slower (more than 4x) than CPython. The example calculates all the possible groupings of a list of values. I've attached the example's code. Timings: time python allgroups.py 20.75s user 0.04s system 99% cpu 20.820 total time pypy allgroups.py 97.31s user 1.07s system 99% cpu 1:38.55 total

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Issue #1781: pip install cython interferes pip install wheezy.web (pypy/pypy)
by jackychaowang 28 May '14

28 May '14

New issue 1781: pip install cython interferes pip install wheezy.web https://bitbucket.org/pypy/pypy/issue/1781/pip-install-cython-interferes-pi… jackychaowang: This works: ``` #!bash pip install wheezy.web pip install cython ``` But once we change the order, it stop working: ``` #!bash pip install cython pip install wheezy.web src/wheezy/web/middleware/errors.c: In function ‘__Pyx_PyBytes_Join’: src/wheezy/web/middleware/errors.c:2955:1: error: expected ‘;’ before ‘}’ token } ```

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Issue #1780: pip install gevent doesn't work on pypy (pypy/pypy)
by jackychaowang 28 May '14

28 May '14

New issue 1780: pip install gevent doesn't work on pypy https://bitbucket.org/pypy/pypy/issue/1780/pip-install-gevent-doesnt-work-o… jackychaowang: Build error: * gevent/callbacks.c: 8:18: error: ‘PyThreadState’ has no member named ‘curexc_type’ * gevent/callbacks.c:11:19: error: ‘PyThreadState’ has no member named ‘curexc_value’ * gevent/callbacks.c:12:23: error: ‘PyThreadState’ has no member named ‘curexc_traceback’ ``` #!bash In file included from gevent/gevent.core.c:47210:0: gevent/callbacks.c: In function ‘gevent_handle_error’: gevent/callbacks.c:8:18: error: ‘PyThreadState’ has no member named ‘curexc_type’ type = tstate->curexc_type; ^ gevent/callbacks.c:11:19: error: ‘PyThreadState’ has no member named ‘curexc_value’ value = tstate->curexc_value; ^ gevent/callbacks.c:12:23: error: ‘PyThreadState’ has no member named ‘curexc_traceback’ traceback = tstate->curexc_traceback; ^ ```

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Issue #1779: im.point() 4000x slower than CPython (pypy/pypy)
by hugovk 28 May '14

28 May '14

New issue 1779: im.point() 4000x slower than CPython https://bitbucket.org/pypy/pypy/issue/1779/impoint-4000x-slower-than-cpython hugovk: The following code takes nearly 4000 times longer on PyPy 2.2.1 compared with CPython. It takes less than a second with CPython compared with over 5 minutes on PyPy: ``` #!/usr/bin/env python from PIL import Image im = Image.open("lena.ppm") im.point(list(range(256))*3) im.point(lambda x: x) im = im.convert("I") im.point(lambda x: x*1) im.point(lambda x: x+1) im.point(lambda x: x*1+1) im.point(list(range(256))*256, 'L') ``` Test code: https://github.com/hugovk/test/tree/484 ``` 2.6 0m0.098s 2.7 0m0.042s 3.2 0m0.106s 3.3 0m0.094s 3.4 0m0.069s PyPy 5m16.867s ``` PyPy time / average CPython time = 3873.6797066 Timings from: https://travis-ci.org/hugovk/test/builds/26190010 The code is a simplified form of a Pillow test. At the moment it is skipped for PyPy as it takes too long. No coverage is involved. I've not tested on PyPy 2.3.

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Issue #1778: PyGILState_Ensure should not deadlock if GIL already held (pypy/pypy)
by Nick Williams 26 May '14

26 May '14

New issue 1778: PyGILState_Ensure should not deadlock if GIL already held https://bitbucket.org/pypy/pypy/issue/1778/pygilstate_ensure-should-not-dea… Nick Williams: PyGILState_Ensure is documented as "(ensuring) that the current thread is ready to call the Python C API regardless of the current state of Python, or of the global interpreter lock". However, in PyPy, code which calls PyGILState_Ensure while already holding the GIL will deadlock. This does not happen in CPython and does not seem consistent with the Python documentation.

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Deadlock in cpyext callback
by Nick Williams 26 May '14

26 May '14

We have an extension module which works fine with CPython but deadlocks every time in PyPy. The problem is induced when the C++ code in the module (having been invoked from a Python thread) prepares to call back into Python again by calling PyGILState_Ensure. It seems at this point we try to acquire the GIL mutex while already (presumably) holding it - any other threads at this point are also waiting on the mutex so it isn't held elsewhere. This seems to occur from a call to rffi.aroundstate.after() - I assume that the invariant here is that the before() has already executed but that seems not to be the case here. What is supposed to trigger that? Thanks for any assistance in advance. Nick

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Issue #1777: Unable to create proper numpy array from cffi buffer (pypy/pypy)
by Yichao Yu 25 May '14

25 May '14

New issue 1777: Unable to create proper numpy array from cffi buffer https://bitbucket.org/pypy/pypy/issue/1777/unable-to-create-proper-numpy-ar… Yichao Yu: I am writing something that need to convert a c buffer from cffi to a numpy array with arbitrary shape and strides. Besides the fact that [`as_strided`](https://bitbucket.org/pypy/numpy/issue/9/numpylibstride_tricksas_strided-is-not) is not really working, another problem is that the c buffer is maintained by the underlaying c/c++ library (OpenCL in this case). Therefore it is necessary to let the numpy ndarray hold a reference of the object which manage the memory. In CPython, this is done by [setting the base on the ndarray](https://github.com/pyopencl/pyopencl/blob/master/src/wrapper/wrap_…. However, there doesn't seem to be a way to do the same in (num)pypy. In pypy, although I can pass the buffer to `np.frombuffer` and call `reshape` to get an array roughly correct, the array is only holding a reference to the buffer returned by cffi but not the (c++) object (or the python delegate of it) which manages the memory. Furthermore, the base property of the result array cannot be used to access the underlying object (which is currently a PyOpenCL API that I would love not to break.) (The problem can probably be solved along with the [`as_strided` support bug](https://bitbucket.org/pypy/numpy/issue/9/numpylibstride_tricksas_strid… by allowing creating arrays from object with a proper array interface)

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Issue #1776: Creating instances of a namedtuple is inexplicably very slow (pypy/pypy)
by Alex Gaynor 23 May '14

23 May '14

New issue 1776: Creating instances of a namedtuple is inexplicably very slow https://bitbucket.org/pypy/pypy/issue/1776/creating-instances-of-a-namedtup… Alex Gaynor: Compare: ``` $ pypy -mtimeit -s "from collections import namedtuple; pos = namedtuple('pos', ['x', 'y'])" "p = (1, 2)" 1000000000 loops, best of 3: 0.000867 usec per loop $ pypy -mtimeit -s "from collections import namedtuple; pos = namedtuple('pos', ['x', 'y'])" "p = (1, 2)" 1000000000 loops, best of 3: 0.000867 usec per loop $ pypy -mtimeit -s "from collections import namedtuple; pos = namedtuple('pos', ['x', 'y'])" "p = (1, 2)" 1000000000 loops, best of 3: 0.00087 usec per loop $ $ $ pypy -mtimeit -s "from collections import namedtuple; pos = namedtuple('pos', ['x', 'y'])" "p = pos(1, 2)" 100000000 loops, best of 3: 0.026 usec per loop $ pypy -mtimeit -s "from collections import namedtuple; pos = namedtuple('pos', ['x', 'y'])" "p = pos(1, 2)" 100000000 loops, best of 3: 0.0264 usec per loop $ pypy -mtimeit -s "from collections import namedtuple; pos = namedtuple('pos', ['x', 'y'])" "p = pos(1, 2)" 100000000 loops, best of 3: 0.0268 usec per loop ``` Looking at the traces, I don't see anything that explains the difference in the `jit-log-opt-loop` section, however looking at `jit-summary`, I see that the namedtuple version compiles many many more bridges, we should figure out why.

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PyPy current status
by Antonio Cuni 23 May '14

23 May '14

Hi all, I am preparing the usual "PyPy status talk" which I'll give to the upcoming Pycon Italy, which is going to cover what happened in the last two years of PyPy. If you are interested, the draft slides are here: https://bitbucket.org/pypy/extradoc/src/tip/talk/pycon-italy-2014/talk.rst?… In the talk, I will to give an overview of the current status of the various subprojects, so I'd be glad if you could help because you surely know better than me the status of the area of your competence :) David: what is the current status of PyPy on ARM? Should I say "it just works" or there is something more to add? What about performance? Matti, Brian: what about numpy? Since people like numbers, what percentage of numpy we can consider completed? Philip: same question for py3k. Is it still considered beta quality or we can say it's stable? Alex, Maciej: I'll also briefly talk about other frontends, so Topaz and Hippy. How much complete are they? What are the performance? I know that hippy is still actively developed, but what about Topaz? Other than what I asked, I'll also highlight CFFI and STM. If anyone has ideas for other cool things which happened in PyPy since 2012, suggestions are welcome :) thank you very much! Anto

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Issue #1775: imp.lock_held isn't quite right (pypy/pypy)
by eevee 22 May '14

22 May '14

New issue 1775: imp.lock_held isn't quite right https://bitbucket.org/pypy/pypy/issue/1775/implock_held-isnt-quite-right eevee: PyPy's `lock_held()` returns whether the lock is held by the current thread: https://bitbucket.org/pypy/pypy/src/6e9376d22e0ecc83bfcdda81d0e37e695b435dd… But CPython returns whether the lock is held _at all_: http://hg.python.org/cpython/file/3a1db0d2747e/Python/import.c#l348

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Where is pypy.org?
by Laura Creighton 21 May '14

21 May '14

I am getting a ton of spam as 'contracts(a)pypy.org'. Somewhere that is a mail alias for me. I'd like to remove that alias, or have it removed if it isn't something I can do. This brings up the larger question as to whether that whole address is needed at all, or if it should just bounce. Laura

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Issue #1774: Pypy not translating with gcc 4.9 on Arch Linux x86_64 (pypy/pypy)
by Aidan Epstein 17 May '14

17 May '14

New issue 1774: Pypy not translating with gcc 4.9 on Arch Linux x86_64 https://bitbucket.org/pypy/pypy/issue/1774/pypy-not-translating-with-gcc-49… Aidan Epstein: I am trying to translate the latest version of pypy from the mercurial repositories using the copy of pypy included in the Arch Linux repos. The arch linux version fails after a short amount of time with the attached stack trace. The official version from pypy.org (or rather the portable binaries from https://github.com/squeaky-pl/portable-pypy) works without a hiccup, however, when trying to use the resulting binary to translate, it fails with the same error. I reported it to the Arch Linux bug tracker, and they said that it was probably a gcc 4.9 issue and to report it here.

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Issue #1773: py3k: continuation.test_zpickle test_pickle_continulet_real_subclass triggers a CPython crash (pypy/pypy)
by Philip Jenvey 16 May '14

16 May '14

New issue 1773: py3k: continuation.test_zpickle test_pickle_continulet_real_subclass triggers a CPython crash https://bitbucket.org/pypy/pypy/issue/1773/py3k-continuationtest_zpickle Philip Jenvey: test_pickle_continulet_real_subclass has been disabled on the py3k branch for now as it can trigger a seg fault when running under CPython. It'll crash with a "Fatal Python error: GC object already tracked", or at least on OSX: "malloc: *** error for object 0x109620af0: pointer being realloc'd was not allocated" continulets do some potentially 'evil' low level things but AFAICT nothing pypy's doing is at at fault here. The crash doesn't seem to occur on default even though the continulet implementations/tests are basically identical

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Issue #1772: Complex dtype unhashable. (pypy/pypy)
by Yichao Yu 16 May '14

16 May '14

New issue 1772: Complex dtype unhashable. https://bitbucket.org/pypy/pypy/issue/1772/complex-dtype-unhashable Yichao Yu: In pypy, ``` pypy -c 'import numpy as np; t = np.dtype([("s1", np.int8), ("s2", np.int8)]); print(hash(t))' Traceback (most recent call last): File "app_main.py", line 75, in run_toplevel File "app_main.py", line 581, in run_it File "<string>", line 1, in <module> TypeError: 'dict' objects are unhashable ``` In CPython ``` python2 -c 'import numpy as np; t = np.dtype([("s1", np.int8), ("s2", np.int8)]); print(hash(t))' -5634517127405799957 ```

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Issues moved to Bitbucket
by Sebastian Pawluś 16 May '14

16 May '14

Hi Small announcement. The new location for PyPy's issues/bugs from now on is on Bitbucket https://bitbucket.org/pypy/pypy/issues The old location (bugs.pypy.org) should be working, but only as a redirect to Bitbucket issues page. Fijał is working on it :) Special thanks to Marcus Bertrand (Bitbucket guy) for help. regards, sebastian pawluś

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pypy buildbot hook overall design
by Matti Picus 16 May '14

16 May '14

Hi. I am looking at adding the ability to monitor a bitbucket-hosted git repo to the bbhook module in pypy's buildbot. The current design requires a repo copy to monitor. Couldn't we just use the payload from bitbucket instead of requiring a repo copy? Matti

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remove-globals-in-jit for ppc backend
by David Edelsohn 15 May '14

15 May '14

Hi, David Ivan and Andre from Unicamp and I are trying to update the ppc backend to the current RPython internals API. We're trying to understand the removal of fail_boxes_int, etc. from the backends. It looks like this was done on the remove-globals-in-jit branch. I guess we need to adapt all of that branch and all of jitframe-in-heap branch to PPC. Can you help explain a little more about this patch? https://mail.python.org/pipermail/pypy-commit/2013-January/069022.html Thanks, David

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PyPy download hosting
by Alex Gaynor 14 May '14

14 May '14

Hi all, Right now PyPy binaries for releases are hosted on bitbucket. Unfortunately, recently bitbucket started rate limiting downloads of files, and I've seen many issues in downloading them, both myself, and from user bug reports. I'd like to move these to be hosted somewhere else, I figured the easiest would be to reuse the PSF infrastructure (hence the CC of that list). What do folks think? PyPy folks, does this work for everyone? Infra folks, any problems with this? Cheers, Alex -- "I disapprove of what you say, but I will defend to the death your right to say it." -- Evelyn Beatrice Hall (summarizing Voltaire) "The people's good is the highest law." -- Cicero GPG Key fingerprint: 125F 5C67 DFE9 4084

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ZipImportError using setuptools?
by Isaac Freeman 13 May '14

13 May '14

I have run across a strange error that only happens with Pypy when installing an egg as a zip package. The same does not happen with CPython. Is this a bug? Can anyone help me troubleshoot this? http://dpaste.com/1MYPK9D/ -- Isaac Freeman memotype (at) gmail.com "Few people are capable of expressing with equanimity opinions that differ from the prejudices of their social environment. Most people are even incapable of forming such opinions." -- Albert Einstein

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Virtualenv
by Armin Rigo 13 May '14

13 May '14

Hi all, We talked about making pip and virtualenv available by default on PyPy. I think it's a good idea but we never did it. If anyone feels like doing it and proposing it as a pull request, it would be even greater! A bientôt, Armin.

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cppyy - garbage collecting of foreign objects
by Александр Киранов 12 May '14

12 May '14

Hi all! I have a large C++ application and I want to use functions/classes from it in pypy. I use cppyy. My application has own memory managing policy (references counting). That's why I need to *catch* moment when pypy is deleting foreign C++ objects - all of it should be "released" before pypy exits. Can anybody advice a solution in my case? Some using of gc module or some other? Also I tried to change __del__ method of W_CPPInstance in .../pypy/module/cppyy/interp_cppyy.py. Is it right way? Sorry for my bad english, I hope you can understand me :) --- Best regards, Alexander

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pypy IDLE on windows
by Yaacov Finkelman 11 May '14

11 May '14

Just installed pypy 2.3 on windows 7 32bit. C:\pypy\pypy.exe -i C:\pypy\lib-python\2.7\idlelib\idle.py reterns: ** IDLE can't import Tkinter. Your Python may not be configured for Tk. ** Traceback (most recent call last): File "app_main.py", line 661, in run_command_line File "app_main.py", line 89, in run_toplevel File "app_main.py", line 64, in handle_sys_exit SystemExit: 1 >>>> any advice?

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Heads up, remap_file_pages() possibly slated for removal from Linux
by Jake Edge 09 May '14

09 May '14

Howdy folks, I wrote an article a ways back about PyPy and STM ( https://lwn.net/Articles/587923/ ) that talked PyPy using the remap_file_pages() system call on Linux. So I thought of you folks when I read an article in this week's LWN titled "The possible demise of remap_file_pages()". It is behind the subscription gate for the next week, but this link should allow you to read it: http://lwn.net/SubscriberLink/597632/6f444e69b9931d1a/ If you folks are still using remap_file_pages(), you may want to speak up in the thread on linux-kernel ... jake -- Jake Edge - LWN - jake(a)lwn.net - http://lwn.net

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2.3 release candidates available for download
by Matti Picus 09 May '14

09 May '14

https://bitbucket.org/pypy/pypy/downloads Please try them out, let me know if anything seems wrong. Matti

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PyPy 2.3 is ready to release today
by matti picus 08 May '14

08 May '14

I will try to upload the builds later today and complete the release, unless someone asks me to delay now. We still need a volunteer to build for macos since the buildbot has some problem with the openssl versioning. If anyone can help, please translate and make sure you can run the lib-python/2.7/test directory with no failures. Matti

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GPS tracker with battery life of 1 year与您共享了相册。
by GPS tracker with battery life of 1 year 07 May '14

07 May '14

GPS tracker with battery life of 1 year Dear Sir This is Anna, the sales manager of Redview GPS in China. HE2000 is a GPS container tracker, with internal battery and low power consumption. The internal battery can keep the device working at least 1 year when report each 1 day. What is more, with internal gyroscope, the device can get position even no GPS signal .HE2000 is IP68 waterproof, easily fixed by rope. I would appreciate if you forward this letter to Technical Manager or to other expert responsible for technical integration of new products in your company, or provide me with his contact for we could discuss all the details of our future cooperation. Your early reply is highly appreciated. Best Regards Anna https://picasaweb.google.com/lh/sredir?uname=116591465845358123247&target=A…

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Depressing performance on a cross-correlation benchmark
by Yury V. Zaytsev 06 May '14

06 May '14

Hi folks, Yesterday, I was able to make my simple cross-correlation script to work with PyPy / NumPy at all with the valuable help of bdk, however, I ended up being quite disappointed about the performance. I stripped out everything I could and ended up with something like this: Python 3: $ time python corrbench.py 0 1 2 real 0m2.225s user 0m1.980s sys 0m0.240s PyPy from hg / NumPy from hg (3581f7a906c9+): $ time python corrbench.py 0 1 2 real 1m2.928s user 1m2.460s sys 0m0.270s What this script does, it basically generates two time series of ~5 000 elements and bins them into 3 000 000 buckets, which it then multiples element-wise and sums up the result. I expected a huge performance boost, of course :-) I think I'll be running this with plain Python for now, but I hope that's a valuable benchmark for you guys! -- Sincerely yours, Yury V. Zaytsev

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PyPy 2.3 alpha release
by matti picus 05 May '14

05 May '14

You have been chosen by an advanced algorithm to participate in the alpha release of PyPy 2.3. Well, not so advanced, but please try it out, I want to release over the next few days. The remaining issues are: - rumors of the python 3.4 ensurepip module appearing in pypy - the macos build has a test failure in the openssl app-level version test Please let me know ASAP if your favorite feature is missing http://buildbot.pypy.org/nightly/release-2.3.x I would also appreciate help with the release notice, the name "Easier Than Ever" is as lame as this email but that's the best I could do. http://doc.pypy.org/en/latest/release-2.3.0.html Matti

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bugs.pypy.org / end of may deadline
by holger krekel 02 May '14

02 May '14

Hi Alex, all, any news on moving bugs.pypy.org somewhere else? End of May i plan to move the underlying host machinery to a new setup at which point it would cease to work. best, holger

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release 2.3 and macos stdlib test failure
by Matti Picus 02 May '14

02 May '14

The macos buildbot, names xerses, has a consistent test failure. It appears to be a configuration error of the buildbot. The owner of the buldbot has not responded on IRC. Could someone else build a macos version off the release branch release-2.3.x that does not exhibit this failure and ships the same OpenSSL as cpython on macos? The failing test is in lib-python.2.7.test.test_ssl, http://buildbot.pypy.org/summary/longrepr?testname=unmodified&builder=pypy-… Matti

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