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COMPAT: IntegerXXDtypes string repr cause numpy deprecation warnings #24593
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"Strange" thing here is that this is not being raised on the numpy-dev build on Azure, which should be failing when there are uncatched numpy warnings (so either there is a reason that they are not raised there, or there is a problem with the "fail-on-warning" mode) |
Do you know what test this is hit in? It's possible that the warnings are being elevated to errors in the numpydev build, but whatever code is calling this may be catching the exception. |
Would still be good to investigate why Azure dev build was not failing. @TomAugspurger do you remember on what is is supposed to fail? On any warning? Or only DeprecationWarning/FutureWarnings? Only from specific packages? Or only from pandas? It is a bit fishy that in the azure build there is no warning at all, while in all travis builds there are plenty of warnings (both from numpy and pandas). Which seems to indicate that just no warnings are reported at all with pytest on azure. |
It should fail on any warning from any package.
Checking in #24616.
It's possible that the warnings (from numpy / pandas) are only hit on code
that's not run as part of the numpydev build.
…On Fri, Jan 4, 2019 at 8:46 AM Joris Van den Bossche < ***@***.***> wrote:
Would still be good to investigate why Azure dev build was not failing.
@TomAugspurger <https://github.com/TomAugspurger> do you remember on what
is is supposed to fail? On any warning? Or only
DeprecationWarning/FutureWarnings? Only from specific packages? Or only
from pandas?
It is a bit fishy that in the azure build there is no warning at all,
while in all travis builds there are plenty of warnings (both from numpy
and pandas). Which seems to indicate that just no warnings are reported at
all with pytest on azure.
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It's running |
Which might be the case, as only numpy ans scipy are installed (so no plotting, not any optional IO, ..) |
The 'numeric-style' type codes are deprecated in numpy, but they clash with our pandas integer dtypes strings (with the capital):
This causes some deprecation warnings in
pd.core.dtypes.common._get_dtype_type
, which surfaces those through egis_integer_dtype
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