On Wed, 26 Nov 2014, Tomasz Buchert wrote:
> + import pandas as _
> +- return True
> ++ return hasattr(_, "DateRange")
imho this is way too aggressive and would cause skipping all pandas
related tests (DateRange dependent or not)
> + except ImportError:
> + return False
> +
> +Index: statsmodels-0.4.2/statsmodels/tsa/base/tests/test_datetools.py
> +===================================================================
> +--- statsmodels-0.4.2.orig/statsmodels/tsa/base/tests/test_datetools.py
> ++++ statsmodels-0.4.2/statsmodels/tsa/base/tests/test_datetools.py
> +@@ -3,6 +3,7 @@ import numpy.testing as npt
> + from statsmodels.tsa.base.datetools import (_date_from_idx,
> + _idx_from_dates, date_parser, date_range_str,
> dates_from_str,
> + dates_from_range, _infer_freq, _freq_to_pandas)
> ++import nose
> +
> + def test_date_from_idx():
> + d1 = datetime(2008, 12, 31)
> +@@ -15,6 +16,7 @@ def test_date_from_idx():
> + npt.assert_equal(_date_from_idx(d1, idx, 'M'), datetime(2010, 3, 31))
> +
> + def test_idx_from_date():
> ++ raise nose.SkipTest("Skipped because of missing DateRange")
if you are introducing these changes, why not to make
def skip_if_no_daterange():
try:
import pandas as _
if not hasaattr(_, "DateRange"):
raise nose.SkipTest("Skipped because...")
except ImportError:
raise nose.SkipTest("Skipped because no pandas...")
and just call that one?
--
Yaroslav O. Halchenko, Ph.D.
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Research Scientist, Psychological and Brain Sciences Dept.
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