id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
1523260646,PR_kwDOAMm_X85G2w0L,7427,Change .groupby fastpath to work for monotonic increasing and decreasing,4671621,open,0,,,6,2023-01-06T22:32:26Z,2023-02-25T22:51:37Z,,FIRST_TIME_CONTRIBUTOR,,0,pydata/xarray/pulls/7427,"This fixes GH6220 which makes it possible to use the fastpath for .groupby for monotonically increasing and decreasing values.

- [x] Closes #6220
- [x] Tests added
- [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst`
- [ ] New functions/methods are listed in `api.rst`
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1561464090,I_kwDOAMm_X85dEg0a,7483,Upgrading dask-core and distributed packages to 2023.1.1 breaks tests,4671621,closed,0,,,1,2023-01-29T21:31:13Z,2023-01-31T18:45:48Z,2023-01-31T18:45:48Z,NONE,,,,"### What happened?

Creating a fresh testing environment and running the tests causes those in [test_distributed.py](https://github.com/pydata/xarray/blob/main/xarray/tests/test_distributed.py) to fail.

### What did you expect to happen?

All tests should pass.

### Minimal Complete Verifiable Example

Environment was setup as follows (according to contribution guidelines)
```shell
// Env setup
conda create -c conda-forge -n xarray-tests python=3.10
conda env update -f ci/requirements/environment.yml
conda activate xarray-tests
pip install -e .

// Running tests
pytest xarray/tests/test_distributed.py
```


### MVCE confirmation

- [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
- [ ] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result.
- [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

### Relevant log output

_No response_

### Anything else we need to know?

This can be remedied when manually downgrading `dask-core` and `distributed` packages from 2023.1.1 to 2023.1.0. Fixing their versions should fix this error until the underlying reason can be figured out.

### Environment

<details>
INSTALLED VERSIONS
------------------
commit: d385e2063a6b5919e1fe9dd3e27a24bc7117137e
python: 3.10.8 | packaged by conda-forge | (main, Nov 22 2022, 08:26:04) [GCC 10.4.0]
python-bits: 64
OS: Linux
OS-release: 6.1.6-200.fc37.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.2
libnetcdf: 4.8.1

xarray: 2023.1.1.dev14+gd385e206
pandas: 1.5.3
numpy: 1.23.5
scipy: 1.10.0
netCDF4: 1.6.0
pydap: installed
h5netcdf: 1.1.0
h5py: 3.8.0
Nio: None
zarr: 2.13.3
cftime: 1.6.2
nc_time_axis: 1.4.1
PseudoNetCDF: 3.2.2
rasterio: 1.3.4
cfgrib: 0.9.10.3
iris: 3.4.0
bottleneck: 1.3.6
dask: 2023.1.1
distributed: 2023.1.1
matplotlib: 3.6.3
cartopy: 0.21.1
seaborn: 0.12.2
numbagg: 0.2.2
fsspec: 2023.1.0
cupy: None
pint: 0.20.1
sparse: 0.13.0
flox: 0.6.7
numpy_groupies: 0.9.20
setuptools: 66.1.1
pip: 22.3.1
conda: 22.11.1
pytest: 7.2.1
mypy: None
IPython: None
sphinx: None
</details>
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