What happened?

https://docs.xarray.dev/en/stable/internals/how-to-add-new-backend.html#indexing-examples

I believe there's a typo in the BASIC indexing support example: ```python

shall support integers

backend_array._raw_indexing_method(1, 1) ```

Should be: ```python

shall support integers

backend_array._raw_indexing_method((1, 1)) ```

Suggestion of possible fixes: * Make sure it is a typo. * Create a valid custom MyBackendArray and initialize it. So it is easier to tell if it's a typo. * Add type hinting so mypy can easier catch these errors.

What did you expect to happen?

No response

Minimal Complete Verifiable Example

No response

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, returning the result.
• [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

What is your issue?

As I've understood it ZarrBackendEntrypoint is the engine used when loading zarr-files. But for some reason we show ZarrStore in xr.backends. I believe the ZarrStore class is supposed to be just a implementation detail, right?

```python

The available engines:

xr.backends.list_engines() Out[23]: {'netcdf4': <xarray.backends.netCDF4_.NetCDF4BackendEntrypoint object at 0x00000296D05D11F0>, 'h5netcdf': <xarray.backends.h5netcdf_.H5netcdfBackendEntrypoint object at 0x00000296D05D14C0>, 'scipy': <xarray.backends.scipy_.ScipyBackendEntrypoint object at 0x00000296D05D11C0>, 'pseudonetcdf': <xarray.backends.pseudonetcdf_.PseudoNetCDFBackendEntrypoint object at 0x00000296D05D1430>, 'pydap': <xarray.backends.pydap_.PydapBackendEntrypoint object at 0x00000296D05D1310>, 'store': <xarray.backends.store.StoreBackendEntrypoint object at 0x00000296D05D1340>, 'zarr': <xarray.backends.zarr.ZarrBackendEntrypoint object at 0x00000296D05D12E0>}

The public class is ZarrStore instead of ZarrBackendEntrypoint, how come?

dir(xr.backends) Out[22]: ['AbstractDataStore', 'BackendArray', 'BackendEntrypoint', 'CachingFileManager', 'CfGribDataStore', 'DummyFileManager', 'FileManager', 'H5NetCDFStore', 'InMemoryDataStore', 'NetCDF4DataStore', 'NioDataStore', 'PseudoNetCDFDataStore', 'PydapDataStore', 'ScipyDataStore', 'ZarrStore', 'all', 'builtins', 'cached', 'doc', 'file', 'loader', 'name', 'package', 'path', 'spec', 'api', 'cfgrib_', 'common', 'file_manager', 'h5netcdf_', 'list_engines', 'locks', 'lru_cache', 'memory', 'netCDF4_', 'netcdf3', 'plugins', 'pseudonetcdf_', 'pydap_', 'pynio_', 'rasterio_', 'scipy_', 'store', 'zarr'] ```

What happened?

Any matplotlib gurus have any ideas how to nicely fit 3d plots in facetgrid? python ds = xr.tutorial.scatter_example_dataset(seed=42) fg = ds.plot.scatter(x="A", y="B", z="z", hue="y", markersize="x", row="x", col="w")

2d looks fine: python fg = ds.plot.scatter(x="A", y="B", hue="y", markersize="x", row="x", col="w")

What did you expect to happen?

No plots overlapping each other, even if rotating the plots.

Minimal Complete Verifiable Example

No response

MVCE confirmation

• [x] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [x] Complete example — the example is self-contained, including all data and the text of any traceback.
• [x] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, 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?

No response

Environment

What happened: Dataset.interp silently drops boolean variables.

What you expected to happen: If I'm interpolating a group of variables I expect to get all of them back in the correct shape with relevant values in them.

If the variables are boolean or object arrays I don't expect it to do linear interpolation because it doesn't make sense but stepwise interpolation like nearest or zero order interpolation should be fine to expect.

Minimal Complete Verifiable Example:

```python import numpy as np a = np.arange(0, 5) b = np.core.defchararray.add("long_variable_name", a.astype(str)) coords = dict(time=da.array([0, 1])) data_vars = dict() for v in b: data_vars[v] = xr.DataArray( name=v, data=np.array([0, 1]).astype(bool), dims=["time"], coords=coords, ) ds1 = xr.Dataset(data_vars)

Print raw data:

print(ds1) Out[3]: <xarray.Dataset> Dimensions: (time: 2) Coordinates: * time (time) int32 0 1 Data variables: long_variable_name0 (time) bool False True long_variable_name1 (time) bool False True long_variable_name2 (time) bool False True long_variable_name3 (time) bool False True long_variable_name4 (time) bool False True

Interpolate:

ds1 = ds1.interp( time=da.array([0, 0.5, 1, 2]), assume_sorted=True, method="nearest", kwargs=dict(fill_value="extrapolate"), )

Print interpolated data:

<xarray.Dataset> Dimensions: (time: 4) Coordinates: * time (time) float64 0.0 0.5 1.0 2.0 Data variables: empty ```

Anything else we need to know?: ds.interp_likeuse ds.reindex in these cases which seems like a good choice in ds.interp as well. But I think that both ds.interp and ds.interp_like should fill by default with nearest value instead of np.nan because we're still requesting interpolation.

Environment:

Is your feature request related to a problem? Please describe. I've been working on opening custom hdf formats in xarray, reading up on the apiv2 it is currently only possible to declare a new external plugin in setup.py but that doesn't seem easy or intuitive to me.

Describe the solution you'd like Why can't we simply be allowed to add functions to the engine parameter? Example: ```python from custom_backend import engine

ds = xr.load_dataset(filename, engine=engine) ``` This seems like a small function change to me from my initial quick look because there's mainly a bunch of string checks in the normal case until we get to the registered backend functions, if we send in a function instead in the engine-parameter we can just bypass those checks.