Hi, On Wed, Jun 27, 2012 at 12:38 AM, Christoph Gohlke <[email protected]> wrote: > On 6/26/2012 8:13 PM, Travis Oliphant wrote: >>> For the main repos we use buildbot and test on: >>> >>> Ubuntu Maverick 32-bit >>> Debian sid 64-bit >>> OSX 10.4 PPC >>> OSX 10.5 Intel >>> Debian wheezy PPC >>> Debian squeeze ARM (a Raspberry PI no less) >>> WIndows XP 32 bit >>> SPARC (courtesy of our friends at NeuroDebian) >>> >>> http://nipy.bic.berkeley.edu/builders >>> >>> We've found several issues with numpy using these, and I've fed them >>> back as I found them, >>> >>> http://projects.scipy.org/numpy/ticket/2076 >>> http://projects.scipy.org/numpy/ticket/2077 >>> http://projects.scipy.org/numpy/ticket/2174 >>> >>> They are particularly useful for difficult to reproduce problems >>> because they test often and leave a record that we can point to. As >>> I've said before, y'all are welcome to use these machines for numpy >>> builds / tests. >> >> Now that Ondrej is working on getting continuous integration up for NumPy, >> I would encourage him to take you up on that offer. Can these machines run >> a Jenkins slave? >> >> Having periodic tests of Sage, Pandas, matplotlib, scipy, and other projects >> is a major priority and really critical before we can really talk about how >> to migrate the APIs. Thankfully, Ondrej is available to help get this >> project started and working this summer. >> >> -Travis >> > > > FWIW: I can relatively easy (batch script) build numpy from github and > run the test suites of many packages available at > <http://www.lfd.uci.edu/~gohlke/pythonlibs/> against it. > > For example at > <http://www.lfd.uci.edu/~gohlke/pythonlibs/tests/numpy-MKL-1.7.0.dev-66bd39f-win-amd64-py2.7/> > are the test results of assimulo, bitarray, bottleneck, h5py, > matplotlib, numexpr, pandas, pygame, scipy, skimage, sklearn, > statsmodels, and pytables, built against numpy-1.6.x and run against > numpy-1.7.0.dev-66bd39f on win-amd64-py2.7.
Thanks - that's very helpful. Do you have your build system documented somewhere? Is it easy to replicate do you think? Cheers, Matthew _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
