Re: [Numpy-discussion] distributing wheels SSE/superpack options
On Sat, Dec 7, 2013 at 8:01 PM, Chris Barker chris.bar...@noaa.gov wrote: On Sat, Dec 7, 2013 at 4:09 AM, Ralf Gommers ralf.gomm...@gmail.comwrote: Wow -- took a little while, but presto! A pile of wheels, ready to go: $ ls wheelhouse/ Jinja2-2.7.1-py27-none-any.whl pyzmq-14.0.1-cp27-none-macosx_10_6_intel.whl MarkupSafe-0.18-cp27-none-macosx_10_6_intel.whl readline-6.2.4.1-cp27-none-macosx_10_6_intel.whl Pygments-1.6-py27-none-any.whl tornado-3.1.1-py27-none-any.whl ipython-1.1.0-py27-none-any.whl Now, do they work? They do on my machine. Is there somewhere I could put them up so folks could test? You can't upload that whole stack anywhere pip finds it automatically. yeah, that's where I'm still a little confused about pip and a wheelhouse -- other than PyPi, is there a way to put a pile of wheels somewhere and point pip to them -- i.e. simple http or ftp server or something? Or are folks going to need to download the whole pile first, then point pip at a local dir? I'm under the impression that $ pip install --use-wheel --no-index --find-links=/local_download_dir ipython and $ pip install --use-wheel --no-index --find-links=hosting_url ipython should both work. But I've been running into multiple issues so far - from having to upgrade pip itself and having to manually remove setuptools to having no wheel-2.7 command (when wheel is the 2.6 version). I've uploaded numpy and scipy wheels plus your set at http://sourceforge.net/projects/numpy/files/wheels_to_test/. I'll start a new thread with a request for testing. Ralf ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On Sun, Dec 8, 2013 at 2:59 AM, Ralf Gommers ralf.gomm...@gmail.com wrote: I'm under the impression that $ pip install --use-wheel --no-index --find-links=/local_download_dir ipython and $ pip install --use-wheel --no-index --find-links=hosting_url ipython should both work. Cool that _should_ be easy and useful But I've been running into multiple issues so far - from having to upgrade pip itself and having to manually remove setuptools to having no wheel-2.7 command (when wheel is the 2.6 version). oh well -- this just shows how little that has been tested. Whici is why it's good we're doing this. I've uploaded numpy and scipy wheels plus your set at http://sourceforge.net/projects/numpy/files/wheels_to_test/. I'll start a new thread with a request for testing. great, thanks! -Chris Ralf ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On Sat, Dec 7, 2013 at 7:44 AM, Chris Barker chris.bar...@noaa.gov wrote: On Fri, Dec 6, 2013 at 10:06 AM, Ralf Gommers ralf.gomm...@gmail.comwrote: One of the things that we should start doing for numpy is distribute releases as wheels. On OS X at least this is quite simple, so I propose to just experiment with it. OK -- maybe on the wrong list, but an itch of mine is OSX binaries of IPython (and the dependencies required for the notebook, too. There is right no way for an OS_X user without the compiler setup to get iPython without going to Anaconda or Canopy, Yet it's a really great tool for newbies So I just sat down and did a simple: pip wheel --wheel-dir=wheelhouse2 ipython[all] Wow -- took a little while, but presto! A pile of wheels, ready to go: $ ls wheelhouse/ Jinja2-2.7.1-py27-none-any.whl pyzmq-14.0.1-cp27-none-macosx_10_6_intel.whl MarkupSafe-0.18-cp27-none-macosx_10_6_intel.whl readline-6.2.4.1-cp27-none-macosx_10_6_intel.whl Pygments-1.6-py27-none-any.whl tornado-3.1.1-py27-none-any.whl ipython-1.1.0-py27-none-any.whl Now, do they work? They do on my machine. Is there somewhere I could put them up so folks could test? You can't upload that whole stack anywhere pip finds it automatically. Temporarily you can put them on SourceForge or on any public download site. Then people can download and install with wheel. If you send me a link to those files, then I'll put them up together with the numpy wheels on SF. Ralf -Chris I can create some to try out and put them on a separate folder on SourceForge. If that works they can be put on PyPi. For Windows things are less simple, because the wheel format doesn't handle the multiple builds (no SSE, SSE2, SSE3) that are in the superpack installers. A problem is that we don't really know how many users still have old CPUs that don't support SSE3. The impact for those users is high, numpy will install but crash (see https://github.com/scipy/scipy/issues/1697). Questions: 1. does anyone have a good idea to obtain statistics? 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? Ralf P.S. related question: did anyone check whether the recently merged NPY_HAVE_SSE2_INTRINSIC puts SSE2 instructions into the no-SSE binary? ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On Sat, Dec 7, 2013 at 4:09 AM, Ralf Gommers ralf.gomm...@gmail.com wrote: Wow -- took a little while, but presto! A pile of wheels, ready to go: $ ls wheelhouse/ Jinja2-2.7.1-py27-none-any.whl pyzmq-14.0.1-cp27-none-macosx_10_6_intel.whl MarkupSafe-0.18-cp27-none-macosx_10_6_intel.whl readline-6.2.4.1-cp27-none-macosx_10_6_intel.whl Pygments-1.6-py27-none-any.whl tornado-3.1.1-py27-none-any.whl ipython-1.1.0-py27-none-any.whl Now, do they work? They do on my machine. Is there somewhere I could put them up so folks could test? You can't upload that whole stack anywhere pip finds it automatically. yeah, that's where I'm still a little confused about pip and a wheelhouse -- other than PyPi, is there a way to put a pile of wheels somewhere and point pip to them -- i.e. simple http or ftp server or something? Or are folks going to need to download the whole pile first, then point pip at a local dir? Temporarily you can put them on SourceForge or on any public download site. Then people can download and install with wheel. If you send me a link to those files, then I'll put them up together with the numpy wheels on SF. Thanks -- I'll try to do that later today. -Chris Ralf -Chris I can create some to try out and put them on a separate folder on SourceForge. If that works they can be put on PyPi. For Windows things are less simple, because the wheel format doesn't handle the multiple builds (no SSE, SSE2, SSE3) that are in the superpack installers. A problem is that we don't really know how many users still have old CPUs that don't support SSE3. The impact for those users is high, numpy will install but crash (see https://github.com/scipy/scipy/issues/1697). Questions: 1. does anyone have a good idea to obtain statistics? 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? Ralf P.S. related question: did anyone check whether the recently merged NPY_HAVE_SSE2_INTRINSIC puts SSE2 instructions into the no-SSE binary? ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
Temporarily you can put them on SourceForge or on any public download site. Then people can download and install with wheel. If you send me a link to those files, then I'll put them up together with the numpy wheels on SF. Thanks -- I'll try to do that later today.-- Done: https://www.dropbox.com/sh/pqn6fag18rgewlr/QQdNUwT7Fw/OSX_Wheels Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On 06.12.2013 19:06, Ralf Gommers wrote: Hi all, There are a few discussions on packaging for the scientific Python stack ongoing, on the NumFOCUS and distutils lists: https://groups.google.com/forum/#!topic/numfocus/mVNakFqfpZg https://groups.google.com/forum/#!topic/numfocus/HUcwXTM_jNY http://thread.gmane.org/gmane.comp.python.distutils.devel/20202 http://thread.gmane.org/gmane.comp.python.distutils.devel/20296 One of the things that we should start doing for numpy is distribute releases as wheels. On OS X at least this is quite simple, so I propose to just experiment with it. I can create some to try out and put them on a separate folder on SourceForge. If that works they can be put on PyPi. For Windows things are less simple, because the wheel format doesn't handle the multiple builds (no SSE, SSE2, SSE3) that are in the superpack installers. A problem is that we don't really know how many users still have old CPUs that don't support SSE3. The impact for those users is high, numpy will install but crash (see https://github.com/scipy/scipy/issues/1697). Questions: 1. does anyone have a good idea to obtain statistics? 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? why SSE3 and not SSE2? SSE2 is a requirement of the amd64 ABI, so it is present in all 64 bit x86 cpus, so a even majority of windows machines running 32 bit will have it. SSE3 is not mandated by any ABI so it should more likely to find machines without it. to my knowledge SSE3 is not such big a difference to SSE2, only a little better complex arithmetic and horizontal additions, I don't think its worth it. Are there performance comparisons for ATLAS with SSE2 and SSE3 available? P.S. related question: did anyone check whether the recently merged NPY_HAVE_SSE2_INTRINSIC puts SSE2 instructions into the no-SSE binary? according to https://github.com/numpy/numpy/issues/3760 SSE2 should be off in the binaries created with mingw. but there was also https://github.com/numpy/numpy/issues/3680, but that might have been built with the VSC compiler (I think by Christoph Gohlke) Assuming linux objdump works correctly on windows .pyd files there are indeed sse2 instructions in the win32 build created with VSC. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On 6 December 2013 20:09, Chris Barker chris.bar...@noaa.gov wrote: 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? sounds good -- it looks like SSE3 has been around a good while: http://en.wikipedia.org/wiki/SSE3 8+ years is a pretty long time in computer land! anyone know how long SSE3 has been around? I don't have statistics but I do have a couple of data points. Both of the computers I regularly use (my work desktop and my girlfriend's laptop) have SSE2 but not SSE3. Really I'm not sure that releasing a potentially compatible binary - with no install time checks - is such a good idea. What we really want is a situation where you can confidently advise someone to just pip install numpy without caveats i.e. a solution that just works. Oscar ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On Fri, Dec 6, 2013 at 8:28 PM, Oscar Benjamin oscar.j.benja...@gmail.comwrote: On 6 December 2013 20:09, Chris Barker chris.bar...@noaa.gov wrote: 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? sounds good -- it looks like SSE3 has been around a good while: http://en.wikipedia.org/wiki/SSE3 8+ years is a pretty long time in computer land! anyone know how long SSE3 has been around? I don't have statistics but I do have a couple of data points. Both of the computers I regularly use (my work desktop and my girlfriend's laptop) have SSE2 but not SSE3. Really I'm not sure that releasing a potentially compatible binary - with no install time checks - is such a good idea. What we really want is a situation where you can confidently advise someone to just pip install numpy without caveats i.e. a solution that just works. agreed. Also, we should not lie to ourselves: our current ATLAS on windows are most likely not very efficient anyway, SSE or not. Ralf, you mentioned that openblas was problematic on windows ? I could not find any recent discussion on that list. David ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On 12/6/2013 10:06 AM, Ralf Gommers wrote: Hi all, There are a few discussions on packaging for the scientific Python stack ongoing, on the NumFOCUS and distutils lists: https://groups.google.com/forum/#!topic/numfocus/mVNakFqfpZg https://groups.google.com/forum/#%21topic/numfocus/mVNakFqfpZg https://groups.google.com/forum/#!topic/numfocus/HUcwXTM_jNY https://groups.google.com/forum/#%21topic/numfocus/HUcwXTM_jNY http://thread.gmane.org/gmane.comp.python.distutils.devel/20202 http://thread.gmane.org/gmane.comp.python.distutils.devel/20296 One of the things that we should start doing for numpy is distribute releases as wheels. On OS X at least this is quite simple, so I propose to just experiment with it. I can create some to try out and put them on a separate folder on SourceForge. If that works they can be put on PyPi. For Windows things are less simple, because the wheel format doesn't handle the multiple builds (no SSE, SSE2, SSE3) that are in the superpack installers. A problem is that we don't really know how many users still have old CPUs that don't support SSE3. The impact for those users is high, numpy will install but crash (see https://github.com/scipy/scipy/issues/1697). Questions: 1. does anyone have a good idea to obtain statistics? 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? Ralf P.S. related question: did anyone check whether the recently merged NPY_HAVE_SSE2_INTRINSIC puts SSE2 instructions into the no-SSE binary? Has anyone succeeded building wheels for numpy, scipy, and matplotlib? On Windows `bdist_wheel` fails for me. It looks like numpy.distutils doesn't know about wheels and version 0.22.0 fails to package matplotlib. Pillow, pandas, scikit-image, scikits-learn work. Christoph Numpy 1.8.x --- ... running build_scripts creating build\scripts.win-amd64-3.3 Creating build\scripts.win-amd64-3.3\f2py.py adding 'build\scripts.win-amd64-3.3\f2py.py' to scripts Running from numpy source directory. usage: setup.py [global_opts] cmd1 [cmd1_opts] [cmd2 [cmd2_opts] ...] or: setup.py --help [cmd1 cmd2 ...] or: setup.py --help-commands or: setup.py cmd --help error: invalid command 'bdist_wheel' Scipy 0.13.x ... X:\Python27-x64\lib\distutils\dist.py:267: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) usage: setup.py [global_opts] cmd1 [cmd1_opts] [cmd2 [cmd2_opts] ...] or: setup.py --help [cmd1 cmd2 ...] or: setup.py --help-commands or: setup.py cmd --help error: invalid command 'bdist_wheel' Matplotlib 1.3.x ... installing to build\bdist.win32\wheel running install running install_lib copying pylab.py - build\bdist.win32\wheel\matplotlib-1.3.1.data\.. error: build\bdist.win32\wheel\matplotlib-1.3.1.data\..: Cannot create a file when that file already exists ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On Fri, Dec 6, 2013 at 8:38 PM, Christoph Gohlke cgoh...@uci.edu wrote: On 12/6/2013 10:06 AM, Ralf Gommers wrote: Hi all, There are a few discussions on packaging for the scientific Python stack ongoing, on the NumFOCUS and distutils lists: https://groups.google.com/forum/#!topic/numfocus/mVNakFqfpZg https://groups.google.com/forum/#%21topic/numfocus/mVNakFqfpZg https://groups.google.com/forum/#!topic/numfocus/HUcwXTM_jNY https://groups.google.com/forum/#%21topic/numfocus/HUcwXTM_jNY http://thread.gmane.org/gmane.comp.python.distutils.devel/20202 http://thread.gmane.org/gmane.comp.python.distutils.devel/20296 One of the things that we should start doing for numpy is distribute releases as wheels. On OS X at least this is quite simple, so I propose to just experiment with it. I can create some to try out and put them on a separate folder on SourceForge. If that works they can be put on PyPi. For Windows things are less simple, because the wheel format doesn't handle the multiple builds (no SSE, SSE2, SSE3) that are in the superpack installers. A problem is that we don't really know how many users still have old CPUs that don't support SSE3. The impact for those users is high, numpy will install but crash (see https://github.com/scipy/scipy/issues/1697). Questions: 1. does anyone have a good idea to obtain statistics? 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? Ralf P.S. related question: did anyone check whether the recently merged NPY_HAVE_SSE2_INTRINSIC puts SSE2 instructions into the no-SSE binary? Has anyone succeeded building wheels for numpy, scipy, and matplotlib? I did for numpy and scipy. You had to hack a bit numpy.distutils to make it work for scipy,but nothing that would be too complicated to really fix. In your case, the trick is to use the setupegg file: python setupegg.py bdist_wheel David On Windows `bdist_wheel` fails for me. It looks like numpy.distutils doesn't know about wheels and version 0.22.0 fails to package matplotlib. Pillow, pandas, scikit-image, scikits-learn work. Christoph Numpy 1.8.x --- ... running build_scripts creating build\scripts.win-amd64-3.3 Creating build\scripts.win-amd64-3.3\f2py.py adding 'build\scripts.win-amd64-3.3\f2py.py' to scripts Running from numpy source directory. usage: setup.py [global_opts] cmd1 [cmd1_opts] [cmd2 [cmd2_opts] ...] or: setup.py --help [cmd1 cmd2 ...] or: setup.py --help-commands or: setup.py cmd --help error: invalid command 'bdist_wheel' Scipy 0.13.x ... X:\Python27-x64\lib\distutils\dist.py:267: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) usage: setup.py [global_opts] cmd1 [cmd1_opts] [cmd2 [cmd2_opts] ...] or: setup.py --help [cmd1 cmd2 ...] or: setup.py --help-commands or: setup.py cmd --help error: invalid command 'bdist_wheel' Matplotlib 1.3.x ... installing to build\bdist.win32\wheel running install running install_lib copying pylab.py - build\bdist.win32\wheel\matplotlib-1.3.1.data\.. error: build\bdist.win32\wheel\matplotlib-1.3.1.data\..: Cannot create a file when that file already exists ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On 12/6/2013 12:40 PM, David Cournapeau wrote: On Fri, Dec 6, 2013 at 8:38 PM, Christoph Gohlke cgoh...@uci.edu mailto:cgoh...@uci.edu wrote: On 12/6/2013 10:06 AM, Ralf Gommers wrote: Hi all, There are a few discussions on packaging for the scientific Python stack ongoing, on the NumFOCUS and distutils lists: https://groups.google.com/forum/#!topic/numfocus/mVNakFqfpZg https://groups.google.com/forum/#%21topic/numfocus/mVNakFqfpZg https://groups.google.com/forum/#%21topic/numfocus/mVNakFqfpZg https://groups.google.com/forum/#!topic/numfocus/HUcwXTM_jNY https://groups.google.com/forum/#%21topic/numfocus/HUcwXTM_jNY https://groups.google.com/forum/#%21topic/numfocus/HUcwXTM_jNY http://thread.gmane.org/gmane.comp.python.distutils.devel/20202 http://thread.gmane.org/gmane.comp.python.distutils.devel/20296 One of the things that we should start doing for numpy is distribute releases as wheels. On OS X at least this is quite simple, so I propose to just experiment with it. I can create some to try out and put them on a separate folder on SourceForge. If that works they can be put on PyPi. For Windows things are less simple, because the wheel format doesn't handle the multiple builds (no SSE, SSE2, SSE3) that are in the superpack installers. A problem is that we don't really know how many users still have old CPUs that don't support SSE3. The impact for those users is high, numpy will install but crash (see https://github.com/scipy/scipy/issues/1697). Questions: 1. does anyone have a good idea to obtain statistics? 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? Ralf P.S. related question: did anyone check whether the recently merged NPY_HAVE_SSE2_INTRINSIC puts SSE2 instructions into the no-SSE binary? Has anyone succeeded building wheels for numpy, scipy, and matplotlib? I did for numpy and scipy. You had to hack a bit numpy.distutils to make it work for scipy,but nothing that would be too complicated to really fix. In your case, the trick is to use the setupegg file: python setupegg.py bdist_wheel David Thank you. The setupegg.py trick worked. Could the numpy.distutils hack be applied to the numpy 1.8.x and master branches? I'll try to fix the matplotlib issue. Christoph ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On Fri, Dec 6, 2013 at 10:01 PM, Christoph Gohlke cgoh...@uci.edu wrote: On 12/6/2013 12:40 PM, David Cournapeau wrote: On Fri, Dec 6, 2013 at 8:38 PM, Christoph Gohlke cgoh...@uci.edu mailto:cgoh...@uci.edu wrote: Has anyone succeeded building wheels for numpy, scipy, and matplotlib? I did for numpy and scipy. You had to hack a bit numpy.distutils to make it work for scipy,but nothing that would be too complicated to really fix. In your case, the trick is to use the setupegg file: python setupegg.py bdist_wheel David Thank you. The setupegg.py trick worked. Could the numpy.distutils hack be applied to the numpy 1.8.x and master branches? I'll try to fix the matplotlib issue. This should make ``python setup.py bdist_wheel`` work: https://github.com/numpy/numpy/pull/4110 Ralf ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On Fri, Dec 6, 2013 at 9:37 PM, David Cournapeau courn...@gmail.com wrote: On Fri, Dec 6, 2013 at 8:28 PM, Oscar Benjamin oscar.j.benja...@gmail.com wrote: On 6 December 2013 20:09, Chris Barker chris.bar...@noaa.gov wrote: 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? sounds good -- it looks like SSE3 has been around a good while: http://en.wikipedia.org/wiki/SSE3 8+ years is a pretty long time in computer land! anyone know how long SSE3 has been around? I don't have statistics but I do have a couple of data points. Both of the computers I regularly use (my work desktop and my girlfriend's laptop) have SSE2 but not SSE3. Really I'm not sure that releasing a potentially compatible binary - with no install time checks - is such a good idea. What we really want is a situation where you can confidently advise someone to just pip install numpy without caveats i.e. a solution that just works. agreed. Also, we should not lie to ourselves: our current ATLAS on windows are most likely not very efficient anyway, SSE or not. Ralf, you mentioned that openblas was problematic on windows ? I could not find any recent discussion on that list. I didn't mean specifically on Windows. I based that on comments like: https://github.com/numpy/numpy/issues/4007#issuecomment-27688947 http://article.gmane.org/gmane.comp.python.scientific.devel/18098 https://github.com/numpy/numpy/issues/3545 Ralf ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] distributing wheels SSE/superpack options
On Fri, Dec 6, 2013 at 10:06 AM, Ralf Gommers ralf.gomm...@gmail.comwrote: One of the things that we should start doing for numpy is distribute releases as wheels. On OS X at least this is quite simple, so I propose to just experiment with it. OK -- maybe on the wrong list, but an itch of mine is OSX binaries of IPython (and the dependencies required for the notebook, too. There is right no way for an OS_X user without the compiler setup to get iPython without going to Anaconda or Canopy, Yet it's a really great tool for newbies So I just sat down and did a simple: pip wheel --wheel-dir=wheelhouse2 ipython[all] Wow -- took a little while, but presto! A pile of wheels, ready to go: $ ls wheelhouse/ Jinja2-2.7.1-py27-none-any.whl pyzmq-14.0.1-cp27-none-macosx_10_6_intel.whl MarkupSafe-0.18-cp27-none-macosx_10_6_intel.whl readline-6.2.4.1-cp27-none-macosx_10_6_intel.whl Pygments-1.6-py27-none-any.whl tornado-3.1.1-py27-none-any.whl ipython-1.1.0-py27-none-any.whl Now, do they work? They do on my machine. Is there somewhere I could put them up so folks could test? -Chris I can create some to try out and put them on a separate folder on SourceForge. If that works they can be put on PyPi. For Windows things are less simple, because the wheel format doesn't handle the multiple builds (no SSE, SSE2, SSE3) that are in the superpack installers. A problem is that we don't really know how many users still have old CPUs that don't support SSE3. The impact for those users is high, numpy will install but crash (see https://github.com/scipy/scipy/issues/1697). Questions: 1. does anyone have a good idea to obtain statistics? 2. in the absence of statistics, can we do an experiment by putting one wheel up on PyPi which contains SSE3 instructions, for python 3.3 I propose, and seeing for how many (if any) users this goes wrong? Ralf P.S. related question: did anyone check whether the recently merged NPY_HAVE_SSE2_INTRINSIC puts SSE2 instructions into the no-SSE binary? ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
