Re: Bug#954170: Help: Test suite failures (Was: ITP: anndata -- Annotated gene by sample numpy matrix)
On 06.11.20 00:37, Diane Trout wrote:
> On Thu, 2020-11-05 at 14:59 -0800, Diane Trout wrote:
>> On Thu, 2020-11-05 at 21:08 +0100, Andreas Tille wrote:
>>> Control: tags -1 help
>>>
>>> Hi Diane and Steffen,
>>>
>>> I fixed the Build-Depends in this package which leads to the
>>> effect that
>>>
>>> a) the Build-time test is run
>>> b) shows the same errors as the autopkgtest
>> I went ahead and filed an upstream bug asking for any advice about
>> the
>> unexpected warning.
>>
>> https://github.com/theislab/anndata/issues/443
> I discovered anndata is having trouble with the version of pandas we're
> shipping. This patch fixes the test failure, though I thought I'd ask
> upstream if they want to do this, or be more accepting of warnings.
> (I'm not sure which versions of pandas they want to support).
>
> Should we wait for upstream or just go ahead and add the patches to our
> packaging?
Nice work!
Thank you for spotting that.
As much as I want anndata to be ready, IIRC it is mostly for bcbio and
there are also some other packages still pending. I hence suggest to
strengthen our ties with upstream and wait for a new release.
Best,
Steffen
> --- anndata/_core/anndata.py 2020-11-05 12:23:54.976471806 -0800
> +++ /run/schroot/mount/unstable-amd64-sbuild-6f63c09f-36e0-4302-9409-
> 6689c5b05354/build/python-anndata-exfcES/python-anndata-
> 0.7.4+ds/anndata/_core/anndata.py 2020-11-05 15:28:33.517496264
> -0800
> @@ -19,5 +19,5 @@
> from numpy import ma
> import pandas as pd
> -from pandas.api.types import is_string_dtype, is_categorical
> +from pandas.api.types import is_string_dtype, is_categorical_dtype
> from scipy import sparse
> from scipy.sparse import issparse
> @@ -1089,8 +1089,8 @@
>
> def _remove_unused_categories(self, df_full, df_sub, uns):
> - from pandas.api.types import is_categorical
> + from pandas.api.types import is_categorical_dtype
>
> for k in df_full:
> - if not is_categorical(df_full[k]):
> + if not is_categorical_dtype(df_full[k]):
> continue
> all_categories = df_full[k].cat.categories
> @@ -1190,5 +1190,5 @@
> key
> for key in df.columns
> - if is_string_dtype(df[key]) and not
> is_categorical(df[key])
> + if is_string_dtype(df[key]) and not
> is_categorical_dtype(df[key])
> ]
> for key in string_cols:
>
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