Mailman 3 December 2014 - pypy-dev

Experiments with PyPy and libgccjit
by David Malcolm 16 Dec '14

16 Dec '14

I'm the maintainer of a new feature for the (not-yet-released) GCC 5: libgccjit: a way to build gcc as a shared library, suitable for generating code in-process. See: https://gcc.gnu.org/wiki/JIT I've been experimenting with embedding it within PyPy - my thought was that gcc has great breadth of hardware support, so maybe PyPy could use libgccjit as a fallback backend for targets which don't yet have their own pypy jit backends. I'm attaching the work I've got so far, in patch form; I apologize for the rough work-in-progress nature of the patch. It has: * a toy example of calling libgccjit from cffi, to build and run code in process (see rpython/jit/backend/libgccjit/cffi_bindings.py). * doing the same from rffi (see rpython/jit/backend/libgccjit/rffi_bindings.py and rpython/jit/backend/libgccjit/test/test_rffi_bindings.py) These seem to work: the translator builds binaries that call into my library, which builds machine code "on the fly". Is there a way to do this without going through the translation step? * the beginnings of a JIT backend: I hack up rpython/jit/backend/detect_cpu.py to always use: rpython/jit/backend/libgccjit/runner.py and this merely raises an exception, albeit dumping the operations seen in loops. My thinking is that I ought to be able to use the rffi bindings of libgccjit to implement the backend, and somehow turn the operations I'm seeing into calls into my libgccjit API. Does this sound useful, and am I on the right track here? Is there documentation about the meaning of the various kinds of operations within a to-be-JITted-loop? Thanks Dave

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Ask Pypy within virtualenv of Windows 7/8 for Help ---- bitpeach from china
by 思 13 Dec '14

13 Dec '14

Dear Ms./Mr. Director / Dear Pypy Team: I'm a e-pal named bitpeach. I'm so interested in your work and admire the Pypy. Therefore, I try to install Pypy and pratice with Pypy during my working and studying. But I got a problem, what is worrying me is that there is few versions of Pypy running on the Windows. So the problem comes as follows: (1)I want to instal Pypy but do not confuse the the 3rd packages or libraries with Python2.7 already in my operate system Windows 7/8 (32bit). Then I choose to follow the tutorial settings to install VirtualEnv just like "Installing using virtualenv". (2)After I install VirtualEnv successfully, I need to arrange a new space for Pypy so that I download the Pypy available to Windows as Python2.7 compatible PyPy 2.4.0 - Windows binary (32bit) shown. (3)Then I ectract the pypy-2.4.0-win32.zip file to normal foleder and use VirutalEnv commands like ">virtualenv.exe -p \pathto\pypy.exe". This command "-p $PATH" means I need to choose Pypy as a default Python interpreter,otherwise it will choose Python27 already installed in my Windows system. However the command comes a error and fail to build a virtual environment for pypy. From now on, I truly realized that the specific parameters in the command in windows and Unix/Linux is different. Although I notice that your tutorial shows that $ virtualenv -p /opt/pypy-c-jit-41718-3fb486695f20-linux/bin/pypy my-pypy-env with a difference between Windows7/8 and Unix/Linux, I still can not solve the problem in Windows 7/8 and do not know how to build a virtual environment with appointing Pypy to a default interpreting python environment in Windows 7/8. And I remember your team or website is very good at this and cannot praise your speeding performance Pypy too highly. So you are the best and professional. Hence I come to seek your help. Best Regards! Hope Pypy more and more better! Especially the versions about Windows Sincerely yours!:-) bitpeach 2014-12-13 Sat. Email From China

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Unify lib_pypy by vendoring six
by VanL 06 Dec '14

06 Dec '14

Hi all, I’ve been doing some experiments with pypy and I would interested in making parts of the codebase more 3x compatible. As a first step, I notice that there are slight differences between the lib_pypy shipped in the 2.7 and 3.2 releases. How would people feel about reducing the duplication by consolidating the lib_pypy implementations? The strategy would be: - vendor six.py within lib_pypy - unify implementation as much as possible, using either compatible syntax or six helpers - if the implementation cannot be unified, putting individual implementations behind six.PY2 or six.PY3 conditionals Thoughts? Thanks, Van

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Looking for Python/Twisted developer to work on Open-source
by Tobias Oberstein 05 Dec '14

05 Dec '14

Hi, we're looking for an experienced, dedicated Python / Twisted developer to work on http://crossbar.io/ helping us move faster. The code base is around 40k LOC right now, all open-source here https://github.com/crossbario/crossbar https://github.com/tavendo/AutobahnPython This stuff is all new, probably non-trivial, but I'd say technically exciting. Means: a "challenge" should be something that wakes you up;) We have big plans, and we're starting to see strong uptake - both community and commercial, in particular in IoT. You'll work remotely, as you like, when and where you like. Payment by hours for now, maybe more down the road. If you are interested, please respond by mail, including some interesting bits about you, plus your GitHub handle (or similar), expectations, time zone and rate. If you are not interested, please forward;) Cheers, /Tobias

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GSoC 2015: cpyext project?
by Toby St Clere Smithe 03 Dec '14

03 Dec '14

Hi all, I've posted a couple of times on here before: I maintain a Python extension for GPGPU linear algebra[1], but it uses boost.python. I do most of my scientific computing in Python, but often am forced to use CPython where I would prefer to use PyPy, largely because of the availability of extensions. I'm looking for an interesting Google Summer of Code project for next year, and would like to continue working on things that help make high-performance computing in Python straight-forward. In particular, I've had my eye on the 'optimising cpyext'[2] project for a while: might work in that area be available? I notice that it is described with difficulty 'hard', and so I'm keen to enquire early so that I can get up to speed before making a potential application in the spring. I would love to work on getting cpyext into a good enough shape that both Cython and Boost.Python extensions are functional with minimal effort on behalf of the user. Does anyone have any advice? Are there particular things I should familiarise myself with? I know there is the module/cpyext tree, but it is quite formidable for someone uninitiated! Of course, I recognise that cpyext is a much trickier proposition in comparison with things like cffi and cppyy. In particular, I'm very excited by cppyy and PyCling, but they seem quite bound up in CERN's ROOT infrastructure, which is a shame. But it's also clear that very many useful extensions currently use the CPython API, and so -- as I have often found -- the apparent relative immaturity of cpyext keeps people away from PyPy, which is also a shame! [1] https://pypi.python.org/pypi/pyviennacl [2] https://bitbucket.org/pypy/pypy/wiki/GSOC%202014 Best, Toby -- Toby St Clere Smithe http://tsmithe.net

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