Hi, I'm trying out various continuous integration options, so I happen to be testing NumPy on several platforms that I don't normally use.
Recently, I've been getting a segmentation fault on Debian 6 (with Python 2.7.2): Linux debian6-amd64 2.6.32-5-amd64 #1 SMP Thu Mar 22 17:26:33 UTC 2012 x86_64 GNU/Linux (Debian GNU/Linux 6.0 \n \l) nosetests --verbose /home/slave/tmp/numpy/numpy/random/__init__.py:91: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility from mtrand import * test_api.test_fastCopyAndTranspose ... ok test_api.test_array_astype ... ok test_api.test_copyto_fromscalar ... ok test_api.test_copyto ... ok test_api.test_copyto_maskna ... ok test_api.test_copy_order ... ok Basic test of array2string. ... ok Test custom format function for each element in array. ... ok This should only apply to 0-D arrays. See #1218. ... ok test_arrayprint.TestArrayRepr.test_nan_inf ... ok test_str (test_arrayprint.TestComplexArray) ... ok test_arrayprint.TestPrintOptions.test_basic ... ok test_arrayprint.TestPrintOptions.test_formatter ... ok test_arrayprint.TestPrintOptions.test_formatter_reset ... ok Ticket 844. ... ok test_blasdot.test_blasdot_used ... SKIP: Skipping test: test_blasdot_used Numpy is not compiled with _dotblas test_blasdot.test_dot_2args ... ok test_blasdot.test_dot_3args ... ok test_blasdot.test_dot_3args_errors ... ok test_creation_overflow (test_datetime.TestDateTime) ... ok test_datetime_add (test_datetime.TestDateTime) ... ok test_datetime_arange (test_datetime.TestDateTime) ... ok test_datetime_array_find_type (test_datetime.TestDateTime) ... ok test_datetime_array_str (test_datetime.TestDateTime) ... ok test_datetime_as_string (test_datetime.TestDateTime) ... ok test_datetime_as_string_timezone (test_datetime.TestDateTime) ... /home/slave/ tmp/numpy/numpy/core/tests/test_datetime.py:1319: UserWarning: pytz not found, pytz compatibility tests skipped warnings.warn("pytz not found, pytz compatibility tests skipped") ok test_datetime_busday_holidays_count (test_datetime.TestDateTime) ... ok test_datetime_busday_holidays_offset (test_datetime.TestDateTime) ... ok test_datetime_busday_offset (test_datetime.TestDateTime) ... ok test_datetime_busdaycalendar (test_datetime.TestDateTime) ... ok test_datetime_casting_rules (test_datetime.TestDateTime) ... ok test_datetime_divide (test_datetime.TestDateTime) ... ok test_datetime_dtype_creation (test_datetime.TestDateTime) ... ok test_datetime_is_busday (test_datetime.TestDateTime) ... ok test_datetime_like (test_datetime.TestDateTime) ... ok test_datetime_maximum_reduce (test_datetime.TestDateTime) ... ok test_datetime_minmax (test_datetime.TestDateTime) ... ok test_datetime_multiply (test_datetime.TestDateTime) ... ok test_datetime_nat_casting (test_datetime.TestDateTime) ... ok test_datetime_scalar_construction (test_datetime.TestDateTime) ... ok test_datetime_string_conversion (test_datetime.TestDateTime) ... ERROR test_datetime_subtract (test_datetime.TestDateTime) ... Segmentation fault With Python 2.6 there doesn't seem to be a problem on the same machine. Unfortunately, I haven't had time to investigate (I don't have Debian 6 to use myself, and I just started a job that doesn't involve any Python...). However, according to the Jenkins instance on ShiningPanda.com, the problem began with these changes: BUG: ticket #1578, Fix python-debug warning for python >= 2.7. STY: Small style fixes. For now, that's all I can say; I haven't manually verified the problem myself (that it exists, or that it truly started after the changes above). I hope to be able to investigate further at the weekend, but I thought I'd post to the list now in case someone else can verify the problem. Chris Segmentation fault is buried in console output of Jenkins: https://jenkins.shiningpanda.com/scipy/job/NumPy/PYTHON=CPython-2.7/6/console The previous build was ok: https://jenkins.shiningpanda.com/scipy/job/NumPy/PYTHON=CPython-2.7/5/console Changes that Jenkins claims are responsible: https://jenkins.shiningpanda.com/scipy/job/NumPy/PYTHON=CPython-2.7/6/ changes#detail0 _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion