On Fri, Oct 8, 2010 at 1:09 AM, Jonathan March <[email protected]> wrote:
> On Wed, Oct 6, 2010 at 6:17 PM, <[email protected]> wrote: > > On Wed, Oct 6, 2010 at 7:08 PM, Jonathan March <[email protected]> > wrote: > >> It appears that the numpy testing decorators for skipping and for > >> known failure should behave similarly to each other, at least from > >> their descriptions here: > >> > http://projects.scipy.org/numpy/wiki/TestingGuidelines#known-failures-skipping-tests > >> > >> Yet in the following example, run under nose, they behave quite > differently: > >> > >> ==== > >> from numpy.testing import dec > >> > >> @dec.knownfailureif( True, "known failure test message") > >> def test_will_fail(): > >> pass > >> > >> @dec.skipif( True, "skip test message") > >> def test_to_skip(): > >> pass > >> ==== > >> > >> The skipped test is marked as "S" as expected, but when the > >> KnownFailureTest exception is raised, nose handles it as an error > >> (marked "E" rather than "K" as expected, and printing the stack > >> trace.) > >> > >> It's also interesting that nose has a --no-skip option but no > >> corresponding option for ignoring known failure decorators. > >> > >> Why the discrepancy? Who is out of step with whom? This is with numpy > >> 1.4.0 and nosetests 0.11.3 > > > > just as additional information > > > > This only happens on the command line, with nosetests packagename > > but not with the function, packagename.test() > > > Knownfailure is a numpy-specific plugin, which needs to be loaded for tests decorated with @dec.knownfailureif to be marked as K instead of E. This plugin loading is done by the NoseTester class (defined in numpy/testing/nosetester.py) which is used when tests are run through numpy.test(). Using 'nosetests' on the command line skips this plugin loading, hence the error. Nose does have a "skip" plugin so that never gives an error. > > Josef > > > Numpy issue, nose issue, or user issue? > User issue. Cheers, Ralf > > > >> Thanks, > >> Jonathan March > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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