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=================================== FAILURES ===================================
_________________________ test_dataframe_div_silenced __________________________
[gw0] linux -- Python 3.9.0 /home/travis/virtualenv/python3.9-dev/bin/python
def test_dataframe_div_silenced():
# GH#26793
pdf1 = pd.DataFrame(
{
"A": np.arange(10),
"B": [np.nan, 1, 2, 3, 4] * 2,
"C": [np.nan] * 10,
"D": np.arange(10),
},
index=list("abcdefghij"),
columns=list("ABCD"),
)
pdf2 = pd.DataFrame(
np.random.randn(10, 4), index=list("abcdefghjk"), columns=list("ABCX")
)
with tm.assert_produces_warning(None):
> pdf1.div(pdf2, fill_value=0)
pandas/tests/arithmetic/test_numeric.py:1311:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <contextlib._GeneratorContextManager object at 0x7f00d965da90>
type = None, value = None, traceback = None
def __exit__(self, type, value, traceback):
if type is None:
try:
> next(self.gen)
E AssertionError: Caused unexpected warning(s): [('DeprecationWarning', DeprecationWarning('`np.bool` is a deprecated alias for the builtin `bool`. Use `bool` by itself, which is identical in behavior, to silence this warning. If you specifically wanted the numpy scalar type, use `np.bool_` here.'), '/home/travis/build/pandas-dev/pandas/pandas/core/indexes/base.py', 377), ('DeprecationWarning', DeprecationWarning('`np.bool` is a deprecated alias for the builtin `bool`. Use `bool` by itself, which is identical in behavior, to silence this warning. If you specifically wanted the numpy scalar type, use `np.bool_` here.'), '/home/travis/build/pandas-dev/pandas/pandas/core/indexes/base.py', 377), ('DeprecationWarning', DeprecationWarning('`np.bool` is a deprecated alias for the builtin `bool`. Use `bool` by itself, which is identical in behavior, to silence this warning. If you specifically wanted the numpy scalar type, use `np.bool_` here.'), '/home/travis/build/pandas-dev/pandas/pandas/core/indexes/base.py', 377), ('DeprecationWarning', DeprecationWarning('`np.bool` is a deprecated alias for the builtin `bool`. Use `bool` by itself, which is identical in behavior, to silence this warning. If you specifically wanted the numpy scalar type, use `np.bool_` here.'), '/home/travis/build/pandas-dev/pandas/pandas/core/indexes/base.py', 377)]
Mostly due to old Pandas versions:
pandas-dev/pandas#41199pandas-dev/pandas#32056pandas-dev/pandas#34848
In one instance, also due to Lark using sre_* modules:
lark-parser/lark#1140
Those filters could also be set to `ignore` to not show the warnings at
all. This sets them to `default`, restoring the previous behavior of
showing the warnings but not failing the test run.
Perhaps it might make sense to use older Numpy versions for testing the
older Pandas versions too?
https://travis-ci.org/github/pandas-dev/pandas/jobs/699262221
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