Add Ellipsis typehint to reductions

[headtr1ck]

This PR adds the ellipsis typehint to reductions (only where they behave differently from None to reduce overhead).
Follow up on #7017 (comment)

Additionally I was changing a lot of "one or more dimensions" typehints to str | Iterable[Hashable] (See #6142).
Some code changes were necessary to support this fully. Before several things were not working with actual hashable dimensions that are not strings.

[max-sixty]

Excellent @headtr1ck !

Do we need to run pytest --accept to get the docstrings? It looks like we lost lots...

[headtr1ck]

Could any dev that uses linux rerun the generate_reductions and pytest --doctest-modules xarray/core/_reductions.py --accept?
On windows I still get different results (maybe that should be fixed at some point...)

[headtr1ck]

Turns out that the buildin ellipsis works now with mypy.
Did not test it for older python versions, may require some special casing (Lets see if the tests pass)?

[max-sixty]

Here's the diff from pytest-accept (it is weird that it's slightly different on windows...)

commit 83615a94a6b7c0ae0cf0e0240d7705d9ce6c21e5
Author: Maximilian Roos <m@maxroos.com>
Date: Sat Sep 17 12:36:45 2022 -0700
pytest-accept
diff --git a/xarray/core/_reductions.py b/xarray/core/_reductions.py
index a7cf7ec2..d0c2a9d7 100644
--- a/xarray/core/_reductions.py+++ b/xarray/core/_reductions.py@@ -97,7 +97,7 @@ def count(
<xarray.Dataset>
Dimensions: ()
Data variables:
- da int32 5+ da int64 5
"""
return self.reduce(
duck_array_ops.count,
@@ -4400,7 +4400,7 @@ def count(
>>> da.groupby("labels").count()
<xarray.DataArray (labels: 3)>
- array([1, 2, 2], dtype=int64)+ array([1, 2, 2])
Coordinates:
* labels (labels) object 'a' 'b' 'c'
"""
@@ -5485,7 +5485,7 @@ def count(
>>> da.resample(time="3M").count()
<xarray.DataArray (time: 3)>
- array([1, 3, 1], dtype=int64)+ array([1, 3, 1])
Coordinates:
* time (time) datetime64[ns] 2001-01-31 2001-04-30 2001-07-31
"""

[Illviljan]

I wonder if Dims should include ellipsis as well? The few times it's missing might be issues with the functions?

[Illviljan]

@@ -4400,7 +4400,7 @@ def count(
>>> da.groupby("labels").count()
<xarray.DataArray (labels: 3)>
- array([1, 2, 2], dtype=int64)+ array([1, 2, 2])
Coordinates:
* labels (labels) object 'a' 'b' 'c'
"""

Is it just me that this example crashes the second time I run it?

importnumpyasnpimportpandasaspdimportxarrayasxrda=xr.DataArray(
np.array([1, 2, 3, 1, 2, np.nan]),
dims="time",
coords=dict(
time=("time", pd.date_range("01-01-2001", freq="M", periods=6)),
labels=("time", np.array(["a", "b", "c", "c", "b", "a"])),
),
)
da.groupby("labels").count()

Details

Traceback (mostrecentcalllast):
File"C:\Users\J.W\anaconda3\envs\xarray-tests\lib\site-packages\spyder_kernels\py3compat.py", line356, incompat_execexec(code, globals, locals)
File"g:\program\dropbox\python\xarray_groupby_windows_diff.py", line34, in<module>da.groupby("labels").count()
File"c:\users\j.w\documents\github\xarray\xarray\core\_reductions.py", line4384, incountreturnself._flox_reduce(
File"c:\users\j.w\documents\github\xarray\xarray\core\groupby.py", line738, in_flox_reduceresult=xarray_reduce(
File"C:\Users\J.W\anaconda3\envs\xarray-tests\lib\site-packages\flox\xarray.py", line240, inxarray_reduceds, *by=xr.broadcast(ds, *by, exclude=exclude_dims)
File"c:\users\j.w\documents\github\xarray\xarray\core\alignment.py", line1046, inbroadcastargs=align(*args, join="outer", copy=False, exclude=exclude)
File"c:\users\j.w\documents\github\xarray\xarray\core\alignment.py", line765, inalignaligner.align()
File"c:\users\j.w\documents\github\xarray\xarray\core\alignment.py", line549, inalignself.find_matching_indexes()
File"c:\users\j.w\documents\github\xarray\xarray\core\alignment.py", line256, infind_matching_indexesobj_indexes, obj_index_vars=self._normalize_indexes(obj.xindexes)
File"c:\users\j.w\documents\github\xarray\xarray\core\alignment.py", line205, in_normalize_indexespd_idx=safe_cast_to_index(data)
File"c:\users\j.w\documents\github\xarray\xarray\core\utils.py", line140, insafe_cast_to_indexindex=pd.Index(np.asarray(array), **kwargs)
File"C:\Users\J.W\anaconda3\envs\xarray-tests\lib\site-packages\pandas\core\indexes\base.py", line483, in__new__data=sanitize_array(data, None, dtype=dtype, copy=copy)
File"C:\Users\J.W\anaconda3\envs\xarray-tests\lib\site-packages\pandas\core\construction.py", line524, insanitize_arrayraiseValueError("index must be specified when data is not list-like")
ValueError: indexmustbespecifiedwhendataisnotlist-like

[headtr1ck]

Is it just me that this example crashes the second time I run it?

Could you specify what you mean by "second time I run it"?
Executing the groupby twice?

[Illviljan]

Just running that script file several times without restarting the console. It might be a Spyder bug though since I can't reproduce it in a stand alone ipython console.

This for example works (the first time):

importnumpyasnpimportpandasaspdimportxarrayasxrda=xr.DataArray(
np.array([1, 2, 3, 1, 2, np.nan]),
dims="time",
coords=dict(
time=("time", pd.date_range("01-01-2001", freq="M", periods=6)),
labels=("time", np.array(["a", "b", "c", "c", "b", "a"])),
),
)
da.groupby("labels").count()
da=xr.DataArray(
np.array([1, 2, 3, 1, 2, np.nan]),
dims="time",
coords=dict(
time=("time", pd.date_range("01-01-2001", freq="M", periods=6)),
labels=("time", np.array(["a", "b", "c", "c", "b", "a"])),
),
)
da.groupby("labels").count()

[headtr1ck]

importnumpyasnpimportpandasaspdimportxarrayasxrda=xr.DataArray(
np.array([1, 2, 3, 1, 2, np.nan]),
dims="time",
coords=dict(
time=("time", pd.date_range("01-01-2001", freq="M", periods=6)),
labels=("time", np.array(["a", "b", "c", "c", "b", "a"])),
),
)
da.groupby("labels").count()
da=xr.DataArray(
np.array([1, 2, 3, 1, 2, np.nan]),
dims="time",
coords=dict(
time=("time", pd.date_range("01-01-2001", freq="M", periods=6)),
labels=("time", np.array(["a", "b", "c", "c", "b", "a"])),
),
)
da.groupby("labels").count()

For me this works in a python terminal, python script and jupyter notebook (I don't use spyder but vscode).