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. Christoph _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
