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20 hours ago •
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pydata
Warnings in the test suite
If anyone is looking for any bite-size contributions, the test suite is throwing off many warnings. Most of these indicate that something will break in the future without code changes; thought mostly the code changes are small.
=============================== warnings summary ===============================
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/heapdict.py:11
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/heapdict.py:11: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working
class heapdict(collections.MutableMapping):
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/pydap/model.py:175
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/pydap/model.py:175: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working
from collections import OrderedDict, Mapping
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/pydap/responses/das.py:14
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/pydap/responses/das.py:14: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated, and in 3.8 it will stop working
from collections import Iterable
xarray/tests/test_accessor_dt.py::test_cftime_strftime_access[365_day]
/home/vsts/work/1/s/xarray/tests/test_accessor_dt.py:226: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar. This may lead to subtle errors in operations that depend on the length of time between dates.
xr.coding.cftimeindex.CFTimeIndex(data.time.values).to_datetimeindex(),
xarray/tests/test_accessor_dt.py::test_cftime_strftime_access[360_day]
/home/vsts/work/1/s/xarray/tests/test_accessor_dt.py:226: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, '360_day', to a pandas.DatetimeIndex, which uses dates from the standard calendar. This may lead to subtle errors in operations that depend on the length of time between dates.
xr.coding.cftimeindex.CFTimeIndex(data.time.values).to_datetimeindex(),
xarray/tests/test_accessor_dt.py::test_cftime_strftime_access[julian]
/home/vsts/work/1/s/xarray/tests/test_accessor_dt.py:226: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'julian', to a pandas.DatetimeIndex, which uses dates from the standard calendar. This may lead to subtle errors in operations that depend on the length of time between dates.
xr.coding.cftimeindex.CFTimeIndex(data.time.values).to_datetimeindex(),
xarray/tests/test_accessor_dt.py::test_cftime_strftime_access[all_leap]
xarray/tests/test_accessor_dt.py::test_cftime_strftime_access[366_day]
/home/vsts/work/1/s/xarray/tests/test_accessor_dt.py:226: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'all_leap', to a pandas.DatetimeIndex, which uses dates from the standard calendar. This may lead to subtle errors in operations that depend on the length of time between dates.
xr.coding.cftimeindex.CFTimeIndex(data.time.values).to_datetimeindex(),
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
/home/vsts/work/1/s/xarray/core/duck_array_ops.py:202: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2))
xarray/tests/test_backends.py::TestZarrDictStore::test_to_zarr_append_compute_false_roundtrip
xarray/tests/test_backends.py::TestZarrDictStore::test_to_zarr_append_compute_false_roundtrip
xarray/tests/test_backends.py::TestZarrDirectoryStore::test_to_zarr_append_compute_false_roundtrip
xarray/tests/test_backends.py::TestZarrDirectoryStore::test_to_zarr_append_compute_false_roundtrip
/home/vsts/work/1/s/xarray/conventions.py:184: SerializationWarning: variable None has data in the form of a dask array with dtype=object, which means it is being loaded into memory to determine a data type that can be safely stored on disk. To avoid this, coerce this variable to a fixed-size dtype with astype() before saving it.
SerializationWarning,
xarray/tests/test_backends.py::TestScipyInMemoryData::test_zero_dimensional_variable
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject
return f(*args, **kwds)
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_ict_format
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_ict_format_write
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_ict_format_write
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/PseudoNetCDF/icarttfiles/ffi1001.py:80: DeprecationWarning: 'U' mode is deprecated
f = openf(path, 'rU', encoding = encoding)
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_ict_format
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_ict_format_write
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/_pytest/python.py:170: RuntimeWarning: deallocating CachingFileManager(<function pncopen at 0x7f252e49a6a8>, '/home/vsts/work/1/s/xarray/tests/data/example.ict', kwargs={'format': 'ffi1001'}), but file is not already closed. This may indicate a bug.
result = testfunction(**testargs)
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_uamiv_format_read
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_uamiv_format_mfread
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_uamiv_format_write
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_uamiv_format_write
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/PseudoNetCDF/camxfiles/uamiv/Memmap.py:141: UserWarning: UnboundLocalError("local variable 'dims' referenced before assignment")
warn(repr(e))
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_uamiv_format_mfread
/home/vsts/work/1/s/xarray/tests/test_backends.py:103: FutureWarning: In xarray version 0.13 the default behaviour of `open_mfdataset`
will change. To retain the existing behavior, pass
combine='nested'. To use future default behavior, pass
combine='by_coords'. See
http://xarray.pydata.org/en/stable/combining.html#combining-multi
**kwargs
xarray/tests/test_backends.py::TestPseudoNetCDFFormat::test_uamiv_format_mfread
/home/vsts/work/1/s/xarray/backends/api.py:931: FutureWarning: Also `open_mfdataset` will no longer accept a `concat_dim` argument.
To get equivalent behaviour from now on please use the new
`combine_nested` function instead (or the `combine='nested'` option to
`open_mfdataset`).The datasets supplied do not have global dimension coordinates. In
future, to continue concatenating without supplying dimension
coordinates, please use the new `combine_nested` function (or the
`combine='nested'` option to open_mfdataset.
from_openmfds=True,
xarray/tests/test_coding_times.py::test_cf_datetime_nan[num_dates1-days since 2000-01-01-expected_list1]
xarray/tests/test_coding_times.py::test_cf_datetime_nan[num_dates2-days since 2000-01-01-expected_list2]
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/numpy/testing/_private/utils.py:913: FutureWarning: Converting timezone-aware DatetimeArray to timezone-naive ndarray with 'datetime64[ns]' dtype. In the future, this will return an ndarray with 'object' dtype where each element is a 'pandas.Timestamp' with the correct 'tz'.
To accept the future behavior, pass 'dtype=object'.
To keep the old behavior, pass 'dtype="datetime64[ns]"'.
verbose=verbose, header='Arrays are not equal')
xarray/tests/test_dataarray.py::TestDataArray::test_drop_index_labels
xarray/tests/test_dataarray.py::TestDataArray::test_drop_index_labels
xarray/tests/test_dataarray.py::TestDataArray::test_drop_index_labels
/home/vsts/work/1/s/xarray/core/dataarray.py:1842: DeprecationWarning: dropping dimensions using list-like labels is deprecated; use dict-like arguments.
ds = self._to_temp_dataset().drop(labels, dim, errors=errors)
xarray/tests/test_dataset.py::TestDataset::test_drop_index_labels
/home/vsts/work/1/s/xarray/tests/test_dataset.py:2066: DeprecationWarning: dropping dimensions using list-like labels is deprecated; use dict-like arguments.
actual = data.drop(["a"], "x")
xarray/tests/test_dataset.py::TestDataset::test_drop_index_labels
/home/vsts/work/1/s/xarray/tests/test_dataset.py:2070: DeprecationWarning: dropping dimensions using list-like labels is deprecated; use dict-like arguments.
actual = data.drop(["a", "b"], "x")
xarray/tests/test_dataset.py::TestDataset::test_drop_index_labels
/home/vsts/work/1/s/xarray/tests/test_dataset.py:2078: DeprecationWarning: dropping dimensions using list-like labels is deprecated; use dict-like arguments.
data.drop(["c"], dim="x")
xarray/tests/test_dataset.py::TestDataset::test_drop_index_labels
/home/vsts/work/1/s/xarray/tests/test_dataset.py:2080: DeprecationWarning: dropping dimensions using list-like labels is deprecated; use dict-like arguments.
actual = data.drop(["c"], dim="x", errors="ignore")
xarray/tests/test_dataset.py::TestDataset::test_drop_index_labels
/home/vsts/work/1/s/xarray/tests/test_dataset.py:2086: DeprecationWarning: dropping dimensions using list-like labels is deprecated; use dict-like arguments.
actual = data.drop(["a", "b", "c"], "x", errors="ignore")
xarray/tests/test_dataset.py::TestDataset::test_drop_labels_by_keyword
/home/vsts/work/1/s/xarray/tests/test_dataset.py:2135: DeprecationWarning: dropping dimensions using list-like labels is deprecated; use dict-like arguments.
data.drop(labels=["a"], dim="x", x="a")
xarray/tests/test_dataset.py::TestDataset::test_convert_dataframe_with_many_types_and_multiindex
/home/vsts/work/1/s/xarray/core/dataset.py:3959: FutureWarning: Converting timezone-aware DatetimeArray to timezone-naive ndarray with 'datetime64[ns]' dtype. In the future, this will return an ndarray with 'object' dtype where each element is a 'pandas.Timestamp' with the correct 'tz'.
To accept the future behavior, pass 'dtype=object'.
To keep the old behavior, pass 'dtype="datetime64[ns]"'.
data = np.asarray(series).reshape(shape)
xarray/tests/test_dataset.py::TestDataset::test_convert_dataframe_with_many_types_and_multiindex
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/pandas/core/apply.py:321: FutureWarning: Converting timezone-aware DatetimeArray to timezone-naive ndarray with 'datetime64[ns]' dtype. In the future, this will return an ndarray with 'object' dtype where each element is a 'pandas.Timestamp' with the correct 'tz'.
To accept the future behavior, pass 'dtype=object'.
To keep the old behavior, pass 'dtype="datetime64[ns]"'.
results[i] = self.f(v)
xarray/tests/test_distributed.py::test_dask_distributed_cfgrib_integration_test
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/tornado/gen.py:772: RuntimeWarning: deallocating CachingFileManager(<function open at 0x7f2527b49bf8>, '/tmp/tmpt4tmnjh3/temp-2044.tif', mode='r', kwargs={}), but file is not already closed. This may indicate a bug.
self.future = convert_yielded(yielded)
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-float-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-int-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-float32-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-False-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-float-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-int-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-float32-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-min-True-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-float-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-int-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-float32-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-False-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-float-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-int-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-float32-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-False-max-True-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-True-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-True-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-True-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-True-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-float-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-int-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-float32-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-False-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-True-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-True-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-True-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-True-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-float-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-int-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-float32-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-min-True-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-True-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-True-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-True-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-True-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-float-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-int-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-float32-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-False-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-True-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-True-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-True-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-True-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-float-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-int-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-float32-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-bool_-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-str-1]
xarray/tests/test_duck_array_ops.py::test_argmin_max[x-True-max-True-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-False-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-True-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-True-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-True-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-True-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-min-True-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-False-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-True-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-True-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-True-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-True-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-False-max-True-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-True-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-True-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-False-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-True-True-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-True-True-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-True-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-True-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-True-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-True-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-min-True-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-True-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-True-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-False-False-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-True-True-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-True-True-str-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-True-False-float-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-True-False-int-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-True-False-float32-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-True-False-bool_-2]
xarray/tests/test_duck_array_ops.py::test_argmin_max[y-True-max-True-False-str-2]
/home/vsts/work/1/s/xarray/core/dataarray.py:1842: FutureWarning: dropping coordinates using key values of dict-like labels is deprecated; use drop_vars or a list of coordinates.
ds = self._to_temp_dataset().drop(labels, dim, errors=errors)
xarray/tests/test_plot.py::TestPlotStep::test_step
/home/vsts/work/1/s/xarray/plot/plot.py:321: MatplotlibDeprecationWarning: Passing the drawstyle with the linestyle as a single string is deprecated since Matplotlib 3.1 and support will be removed in 3.3; please pass the drawstyle separately using the drawstyle keyword argument to Line2D or set_drawstyle() method (or ds/set_ds()).
primitive = ax.plot(xplt_val, yplt_val, *args, **kwargs)
xarray/tests/test_print_versions.py::test_show_versions
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/setuptools/depends.py:2: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses
import imp
xarray/tests/test_sparse.py::test_dataarray_method[obj.roll(*(), **{'x': 2})-True]
/home/vsts/work/1/s/xarray/core/dataarray.py:2632: FutureWarning: roll_coords will be set to False in the future. Explicitly set roll_coords to silence warning.
shifts=shifts, roll_coords=roll_coords, **shifts_kwargs
xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_ufuncs
/home/vsts/work/1/s/xarray/tests/test_sparse.py:711: PendingDeprecationWarning: xarray.ufuncs will be deprecated when xarray no longer supports versions of numpy older than v1.17. Instead, use numpy ufuncs directly.
assert_equal(np.sin(x), xu.sin(x))
xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_ufuncs
/home/vsts/work/1/s/xarray/core/dataarray.py:2393: PendingDeprecationWarning: xarray.ufuncs will be deprecated when xarray no longer supports versions of numpy older than v1.17. Instead, use numpy ufuncs directly.
return self.__array_wrap__(f(self.variable.data, *args, **kwargs))
xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_groupby_bins
/home/vsts/work/1/s/xarray/core/groupby.py:780: FutureWarning: Default reduction dimension will be changed to the grouped dimension in a future version of xarray. To silence this warning, pass dim=xarray.ALL_DIMS explicitly.
**kwargs
-- Docs: https://docs.pytest.org/en/latest/warnings.html
- First one: https://github.com/DanielStutzbach/heapdict/pull/13
- Second/third one: https://github.com/pydap/pydap/issues/203
- linestyle/drawstyle one: #3274
If people want more, here are some from a fresh compilation: https://paste.xinu.at/LnH/
If people want more, here are some from a fresh compilation: https://paste.xinu.at/LnH/
Although it looks like we've regressed, 95% of those (by number, not necessarily effort) are pint
Even 99% by number. ;) And essentially only one warning repeated 5k times.
These are the (much less numerous) warnings without pint:
=============================== warnings summary ===============================
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
xarray/tests/test_accessor_str.py::test_empty_str_methods
/build/python-xarray/src/xarray-0.15.0/xarray/core/duck_array_ops.py:224: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2))
xarray/tests/test_backends.py::TestNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF3ViaNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_orthogonal_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_vectorized_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestNetCDF4ClassicViaNetCDF4Data::test_array_type_after_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_orthogonal_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_orthogonal_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_orthogonal_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_orthogonal_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_vectorized_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_vectorized_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_vectorized_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_vectorized_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_vectorized_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_vectorized_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_vectorized_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_vectorized_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_array_type_after_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_array_type_after_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_array_type_after_indexing
xarray/tests/test_backends.py::TestGenericNetCDFData::test_array_type_after_indexing
<__array_function__ internals>:5: DeprecationWarning: `np.alen` is deprecated, use `len` instead
xarray/tests/test_concat.py::test_concat_compat
/build/python-xarray/src/xarray-0.15.0/xarray/core/dataarray.py:669: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
return key in self.data
xarray/tests/test_dataarray.py::TestDataArray::test_stack_unstack
/usr/lib/python3.8/site-packages/pandas/util/__init__.py:12: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.
import pandas.util.testing
xarray/tests/test_dataarray.py::TestDataArray::test_to_and_from_empty_series
/build/python-xarray/src/xarray-0.15.0/xarray/tests/test_dataarray.py:3468: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.
expected = pd.Series([])
xarray/tests/test_duck_array_ops.py::test_datetime_mean[False]
xarray/tests/test_duck_array_ops.py::test_datetime_mean[False]
xarray/tests/test_groupby.py::test_groupby_drops_nans
/build/python-xarray/src/xarray-0.15.0/xarray/core/nanops.py:142: RuntimeWarning: Mean of empty slice
return np.nanmean(a, axis=axis, dtype=dtype)
Update! Lots of plotting ones. Pint has had huge progress!
=============================== warnings summary ===============================
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/_pytest/junitxml.py:446
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/_pytest/junitxml.py:446: PytestDeprecationWarning: The 'junit_family' default value will change to 'xunit2' in pytest 6.0. See:
>>> from pandas.tseries.frequencies import to_offset
>>> df = df.resample(freq="3s").mean()
>>> df.index = df.index.to_timestamp() + to_offset("8H")
ds.bar.to_series().resample("24H", loffset="-12H").mean()
xarray/tests/test_dataset.py::test_ndrolling_reduce[True-max-None-True-2]
xarray/tests/test_dataset.py::test_ndrolling_reduce[True-max-None-True-2]
xarray/tests/test_dataset.py::test_ndrolling_reduce[True-max-None-False-2]
xarray/tests/test_dataset.py::test_ndrolling_reduce[True-max-None-False-2]
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/dask/utils.py:31: RuntimeWarning: All-NaN slice encountered
return func(*args, **kwargs)
xarray/tests/test_dataset.py::test_ndrolling_reduce[True-max-None-True-2]
xarray/tests/test_dataset.py::test_ndrolling_reduce[True-max-None-True-2]
xarray/tests/test_dataset.py::test_ndrolling_reduce[True-max-None-False-2]
xarray/tests/test_dataset.py::test_ndrolling_reduce[True-max-None-False-2]
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/dask/core.py:121: RuntimeWarning: All-NaN slice encountered
return func(*(_execute_task(a, cache) for a in args))
xarray/tests/test_dataset.py::test_trapz_datetime[np-True]
xarray/tests/test_dataset.py::test_trapz_datetime[cftime-True]
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/dask/array/core.py:1359: FutureWarning: The `numpy.trapz` function is not implemented by Dask array. You may want to use the da.map_blocks function or something similar to silence this warning. Your code may stop working in a future release.
FutureWarning,
xarray/tests/test_distributed.py::test_dask_distributed_cfgrib_integration_test
/usr/share/miniconda/envs/xarray-tests/lib/python3.7/site-packages/cfgrib/messages.py:379: RuntimeWarning: deallocating CachingFileManager(<function open at 0x7fc3ffc6acb0>, '/tmp/tmpqgz759fe/temp-2438.tif', mode='r', kwargs={}), but file is not already closed. This may indicate a bug.
for i, value in enumerate(header_values):
xarray/tests/test_interp.py::test_decompose[nearest]
xarray/tests/test_interp.py::test_decompose[nearest]
xarray/tests/test_interp.py::test_decompose[linear]
xarray/tests/test_interp.py::test_decompose[linear]
/home/vsts/work/1/s/xarray/core/dataarray.py:2060: PendingDeprecationWarning: dropping variables using `drop` will be deprecated; using drop_vars is encouraged.
ds = self._to_temp_dataset().drop(labels, dim, errors=errors)
xarray/tests/test_interp.py::test_interpolate_chunk_advanced[linear]
xarray/tests/test_interp.py::test_interpolate_chunk_advanced[nearest]
/home/vsts/work/1/s/xarray/core/missing.py:633: PerformanceWarning: Increasing number of chunks by factor of 35
var.transpose(*original_dims).data, x, destination, method, kwargs
xarray/tests/test_interp.py::test_interpolate_chunk_advanced[linear]
xarray/tests/test_interp.py::test_interpolate_chunk_advanced[nearest]
/home/vsts/work/1/s/xarray/core/missing.py:737: PerformanceWarning: Increasing number of chunks by factor of 35
new_axes=new_axes,
xarray/tests/test_plot.py: 41 warnings
/home/vsts/work/1/s/xarray/plot/utils.py:624: MatplotlibDeprecationWarning: The 'extend' parameter to Colorbar has no effect because it is overridden by the mappable; it is deprecated since 3.3 and will be removed two minor releases later.
cbar = fig.colorbar(primitive, **cbar_kwargs)
xarray/tests/test_plot.py::TestPlot::test_contourf_cmap_set_with_bad_under_over
/home/vsts/work/1/s/xarray/tests/test_plot.py:368: MatplotlibDeprecationWarning: You are modifying the state of a globally registered colormap. In future versions, you will not be able to modify a registered colormap in-place. To remove this warning, you can make a copy of the colormap first. cmap = copy.copy(mpl.cm.get_cmap("viridis"))
cmap.set_bad("w")
xarray/tests/test_plot.py::TestPlot::test_contourf_cmap_set_with_bad_under_over
/home/vsts/work/1/s/xarray/tests/test_plot.py:375: MatplotlibDeprecationWarning: You are modifying the state of a globally registered colormap. In future versions, you will not be able to modify a registered colormap in-place. To remove this warning, you can make a copy of the colormap first. cmap = copy.copy(mpl.cm.get_cmap("viridis"))
cmap.set_under("r")
xarray/tests/test_plot.py::TestPlot::test_contourf_cmap_set_with_bad_under_over
/home/vsts/work/1/s/xarray/tests/test_plot.py:379: MatplotlibDeprecationWarning: You are modifying the state of a globally registered colormap. In future versions, you will not be able to modify a registered colormap in-place. To remove this warning, you can make a copy of the colormap first. cmap = copy.copy(mpl.cm.get_cmap("viridis"))
cmap.set_over("g")
xarray/tests/test_plot.py::TestDiscreteColorMap::test_discrete_colormap_list_of_levels
xarray/tests/test_plot.py::TestDiscreteColorMap::test_discrete_colormap_int_levels
xarray/tests/test_plot.py::TestImshow::test_seaborn_palette_as_cmap
/home/vsts/work/1/s/xarray/plot/plot.py:903: MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.
primitive = ax.imshow(z, **defaults)
xarray/tests/test_plot.py::TestDiscreteColorMap::test_discrete_colormap_list_of_levels
xarray/tests/test_plot.py::TestDiscreteColorMap::test_discrete_colormap_int_levels
xarray/tests/test_plot.py::TestDiscreteColorMap::test_discrete_colormap_list_levels_and_vmin_or_vmax
xarray/tests/test_plot.py::TestPcolormesh::test_seaborn_palette_as_cmap
/home/vsts/work/1/s/xarray/plot/plot.py:968: MatplotlibDeprecationWarning: Passing parameters norm and vmin/vmax simultaneously is deprecated since 3.3 and will become an error two minor releases later. Please pass vmin/vmax directly to the norm when creating it.
primitive = ax.pcolormesh(x, y, z, **kwargs)
xarray/tests/test_plot.py: 10 warnings
/home/vsts/work/1/s/xarray/plot/facetgrid.py:421: MatplotlibDeprecationWarning: The 'extend' parameter to Colorbar has no effect because it is overridden by the mappable; it is deprecated since 3.3 and will be removed two minor releases later.
self._mappables[-1], ax=list(self.axes.flat), **kwargs
xarray/tests/test_plot.py::TestPcolormesh::test_dont_infer_interval_breaks_for_cartopy
/home/vsts/work/1/s/xarray/plot/plot.py:968: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3. Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading']. This will become an error two minor releases later.
primitive = ax.pcolormesh(x, y, z, **kwargs)
xarray/tests/test_plot.py::test_get_axis_cartopy
/home/vsts/work/1/s/xarray/plot/utils.py:437: UserWarning: Requested projection is different from current axis projection, creating new axis with requested projection.
ax = plt.gca(**kwargs)
xarray/tests/test_sparse.py::test_variable_method[obj.argmax(*(), **{})-True]
xarray/tests/test_sparse.py::test_variable_method[obj.argmin(*(), **{})-True]
/home/vsts/work/1/s/xarray/tests/test_sparse.py:65: DeprecationWarning: Behaviour of argmin/argmax with neither dim nor axis argument will change to return a dict of indices of each dimension. To get a single, flat index, please use np.argmin(da.data) or np.argmax(da.data) instead of da.argmin() or da.argmax().
return getattr(obj, self.meth)(*self.args, **self.kwargs)
xarray/tests/test_sparse.py::test_dataarray_method[obj.argmax(*(), **{})-True]
/home/vsts/work/1/s/xarray/core/dataarray.py:4060: DeprecationWarning: Behaviour of argmin/argmax with neither dim nor axis argument will change to return a dict of indices of each dimension. To get a single, flat index, please use np.argmin(da.data) or np.argmax(da.data) instead of da.argmin() or da.argmax().
result = self.variable.argmax(dim, axis, keep_attrs, skipna)
xarray/tests/test_sparse.py::test_dataarray_method[obj.argmin(*(), **{})-True]
/home/vsts/work/1/s/xarray/core/dataarray.py:3957: DeprecationWarning: Behaviour of argmin/argmax with neither dim nor axis argument will change to return a dict of indices of each dimension. To get a single, flat index, please use np.argmin(da.data) or np.argmax(da.data) instead of da.argmin() or da.argmax().
result = self.variable.argmin(dim, axis, keep_attrs, skipna)
xarray/tests/test_variable.py::TestVariableWithDask::test_pad[xr_arg0-np_arg0-mean]
xarray/tests/test_variable.py::TestVariableWithDask::test_pad[xr_arg1-np_arg1-mean]
xarray/tests/test_variable.py::TestVariableWithDask::test_pad[xr_arg2-np_arg2-mean]
xarray/tests/test_variable.py::TestVariableWithDask::test_pad[xr_arg3-np_arg3-mean]
xarray/tests/test_variable.py::TestVariableWithDask::test_pad[xr_arg4-np_arg4-mean]
/home/vsts/work/1/s/xarray/core/dask_array_compat.py:142: UserWarning: dask.array.pad(mode="mean") converts integers to floats. xarray converts these floats back to integers to keep the interface consistent. There is a chance that this introduces rounding errors. If you wish to keep the values as floats, first change the dtype to a float before calling pad.
UserWarning,
-- Docs: https://docs.pytest.org/en/stable/warnings.html
-------- generated xml file: /home/vsts/work/1/s/junit/test-results.xml --------
Currently most warnings (> 1500 of 1900) stem from netCDF4. They should be fixed in the newest netCDF4 version (1.5.4). See https://github.com/Unidata/netcdf4-python/blob/master/Changelog (alen -> len and tostring -> tobytes). However, netCDF 1.5.4 can not be installed alongside pynio (conda-forge/pynio-feedstock#90).
Addendum: Removing pynio from the tests and thus using the newest version of netCDF4 brings the warnings down to 71 (from 1931), see #4492
