# This requires a configured writable hsds server in ~/.hscfg

import h5pyd
import xarray as xr
with h5pyd.File("/test/rho/y.h5", "w") as f:
    f.create_dataset('foo', (), dtype=bytes)
xr.open_datatree("/test/rho/y.h5", engine='h5netcdf', driver='h5pyd',)

[...]

File ~/git/xarray/xarray/backends/h5netcdf_.py:222, in H5NetCDFStore.open_store_variable(self, name, var)
    216 encoding = {
    217     "chunksizes": var.chunks,
    218     "fletcher32": var.fletcher32,
    219     "shuffle": var.shuffle,
    220 }
    221 if var.chunks:
--> 222     encoding["preferred_chunks"] = dict(
    223         zip(var.dimensions, var.chunks, strict=True)
    224     )
    225 # Convert h5py-style compression options to NetCDF4-Python
    226 # style, if possible
    227 if var.compression == "gzip":

ValueError: zip() argument 2 is longer than argument 1

Cell In[36], line 4
      2 with h5pyd.File("/test/rho/y.h5", "w") as f:
      3     f.create_dataset('foo', (), dtype=bytes)
----> 4 xr.open_datatree("/test/rho/y.h5", engine='h5netcdf', driver='h5pyd',)

File ~/git/xarray/xarray/backends/api.py:1130, in open_datatree(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, inline_array, chunked_array_type, from_array_kwargs, backend_kwargs, **kwargs)
   1118 decoders = _resolve_decoders_kwargs(
   1119     decode_cf,
   1120     open_backend_dataset_parameters=(),
   (...)   1126     decode_coords=decode_coords,
   1127 )
   1128 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None)
-> 1130 backend_tree = backend.open_datatree(
   1131     filename_or_obj,
   1132     drop_variables=drop_variables,
   1133     **decoders,
   1134     **kwargs,
   1135 )
   1137 tree = _datatree_from_backend_datatree(
   1138     backend_tree,
   1139     filename_or_obj,
   (...)   1149     **kwargs,
   1150 )
   1152 return tree

File ~/git/xarray/xarray/backends/h5netcdf_.py:514, in H5netcdfBackendEntrypoint.open_datatree(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, format, group, lock, invalid_netcdf, phony_dims, decode_vlen_strings, driver, driver_kwds, **kwargs)
    493 def open_datatree(
    494     self,
    495     filename_or_obj: str | os.PathLike[Any] | ReadBuffer | AbstractDataStore,
   (...)    512     **kwargs,
    513 ) -> DataTree:
--> 514     groups_dict = self.open_groups_as_dict(
    515         filename_or_obj,
    516         mask_and_scale=mask_and_scale,
    517         decode_times=decode_times,
    518         concat_characters=concat_characters,
    519         decode_coords=decode_coords,
    520         drop_variables=drop_variables,
    521         use_cftime=use_cftime,
    522         decode_timedelta=decode_timedelta,
    523         format=format,
    524         group=group,
    525         lock=lock,
    526         invalid_netcdf=invalid_netcdf,
    527         phony_dims=phony_dims,
    528         decode_vlen_strings=decode_vlen_strings,
    529         driver=driver,
    530         driver_kwds=driver_kwds,
    531         **kwargs,
    532     )
    534     return datatree_from_dict_with_io_cleanup(groups_dict)

File ~/git/xarray/xarray/backends/h5netcdf_.py:590, in H5netcdfBackendEntrypoint.open_groups_as_dict(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, format, group, lock, invalid_netcdf, phony_dims, decode_vlen_strings, driver, driver_kwds, **kwargs)
    588 store_entrypoint = StoreBackendEntrypoint()
    589 with close_on_error(group_store):
--> 590     group_ds = store_entrypoint.open_dataset(
    591         group_store,
    592         mask_and_scale=mask_and_scale,
    593         decode_times=decode_times,
    594         concat_characters=concat_characters,
    595         decode_coords=decode_coords,
    596         drop_variables=drop_variables,
    597         use_cftime=use_cftime,
    598         decode_timedelta=decode_timedelta,
    599     )
    601 if group:
    602     group_name = str(NodePath(path_group).relative_to(parent))

File ~/git/xarray/xarray/backends/store.py:44, in StoreBackendEntrypoint.open_dataset(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta)
     30 def open_dataset(
     31     self,
     32     filename_or_obj: str | os.PathLike[Any] | ReadBuffer | AbstractDataStore,
   (...)     40     decode_timedelta=None,
     41 ) -> Dataset:
     42     assert isinstance(filename_or_obj, AbstractDataStore)
---> 44     vars, attrs = filename_or_obj.load()
     45     encoding = filename_or_obj.get_encoding()
     47     vars, attrs, coord_names = conventions.decode_cf_variables(
     48         vars,
     49         attrs,
   (...)     56         decode_timedelta=decode_timedelta,
     57     )

File ~/git/xarray/xarray/backends/common.py:312, in AbstractDataStore.load(self)
    293 def load(self):
    294     """
    295     This loads the variables and attributes simultaneously.
    296     A centralized loading function makes it easier to create
   (...)    309     are requested, so care should be taken to make sure its fast.
    310     """
    311     variables = FrozenDict(
--> 312         (_decode_variable_name(k), v) for k, v in self.get_variables().items()
    313     )
    314     attributes = FrozenDict(self.get_attrs())
    315     return variables, attributes

File ~/git/xarray/xarray/backends/h5netcdf_.py:262, in H5NetCDFStore.get_variables(self)
    261 def get_variables(self):
--> 262     return FrozenDict(
    263         (k, self.open_store_variable(k, v)) for k, v in self.ds.variables.items()
    264     )

File ~/git/xarray/xarray/core/utils.py:457, in FrozenDict(*args, **kwargs)
    456 def FrozenDict(*args, **kwargs) -> Frozen:
--> 457     return Frozen(dict(*args, **kwargs))

File ~/git/xarray/xarray/backends/h5netcdf_.py:263, in <genexpr>(.0)
    261 def get_variables(self):
    262     return FrozenDict(
--> 263         (k, self.open_store_variable(k, v)) for k, v in self.ds.variables.items()
    264     )

File ~/git/xarray/xarray/backends/h5netcdf_.py:222, in H5NetCDFStore.open_store_variable(self, name, var)
    216 encoding = {
    217     "chunksizes": var.chunks,
    218     "fletcher32": var.fletcher32,
    219     "shuffle": var.shuffle,
    220 }
    221 if var.chunks:
--> 222     encoding["preferred_chunks"] = dict(
    223         zip(var.dimensions, var.chunks, strict=True)
    224     )
    225 # Convert h5py-style compression options to NetCDF4-Python
    226 # style, if possible
    227 if var.compression == "gzip":

ValueError: zip() argument 2 is longer than argument 1