Zarr Encoding Specification¶
In implementing support for the Zarr storage format, Xarray developers made some ad hoc choices about how to store NetCDF data in Zarr. Future versions of the Zarr spec will likely include a more formal convention for the storage of the NetCDF data model in Zarr; see Zarr spec repo for ongoing discussion.
First, Xarray can only read and write Zarr groups. There is currently no support
for reading / writing individual Zarr arrays. Zarr groups are mapped to
Xarray Dataset
objects.
Second, from Xarray’s point of view, the key difference between NetCDF and Zarr is that all NetCDF arrays have dimension names while Zarr arrays do not. Therefore, in order to store NetCDF data in Zarr, Xarray must somehow encode and decode the name of each array’s dimensions.
To accomplish this, Xarray developers decided to define a special Zarr array
attribute: _ARRAY_DIMENSIONS
. The value of this attribute is a list of
dimension names (strings), for example ["time", "lon", "lat"]
. When writing
data to Zarr, Xarray sets this attribute on all variables based on the variable
dimensions. When reading a Zarr group, Xarray looks for this attribute on all
arrays, raising an error if it can’t be found. The attribute is used to define
the variable dimension names and then removed from the attributes dictionary
returned to the user.
Because of these choices, Xarray cannot read arbitrary array data, but only
Zarr data with valid _ARRAY_DIMENSIONS
or
NCZarr attributes
on each array (NCZarr dimension names are defined in the .zarray
file).
After decoding the _ARRAY_DIMENSIONS
or NCZarr attribute and assigning the variable
dimensions, Xarray proceeds to [optionally] decode each variable using its
standard CF decoding machinery used for NetCDF data (see decode_cf()
).
Finally, it’s worth noting that Xarray writes (and attempts to read)
“consolidated metadata” by default (the .zmetadata
file), which is another
non-standard Zarr extension, albeit one implemented upstream in Zarr-Python.
You do not need to write consolidated metadata to make Zarr stores readable in
Xarray, but because Xarray can open these stores much faster, users will see a
warning about poor performance when reading non-consolidated stores unless they
explicitly set consolidated=False
. See Consolidated Metadata
for more details.
As a concrete example, here we write a tutorial dataset to Zarr and then re-open it directly with Zarr:
In [1]: import os
In [2]: import xarray as xr
In [3]: import zarr
In [4]: ds = xr.tutorial.load_dataset("rasm")
---------------------------------------------------------------------------
PermissionError Traceback (most recent call last)
File /usr/lib/python3/dist-packages/pooch/utils.py:262, in make_local_storage(path, env)
258 if action == "create":
259 # When running in parallel, it's possible that multiple jobs will
260 # try to create the path at the same time. Use exist_ok to avoid
261 # raising an error.
--> 262 os.makedirs(path, exist_ok=True)
263 else:
File <frozen os>:217, in makedirs(name, mode, exist_ok)
File <frozen os>:217, in makedirs(name, mode, exist_ok)
File <frozen os>:227, in makedirs(name, mode, exist_ok)
PermissionError: [Errno 13] Permission denied: '/sbuild-nonexistent'
The above exception was the direct cause of the following exception:
PermissionError Traceback (most recent call last)
Cell In[4], line 1
----> 1 ds = xr.tutorial.load_dataset("rasm")
File /build/python-xarray-69jxB9/python-xarray-2025.01.2/xarray/tutorial.py:213, in load_dataset(*args, **kwargs)
176 def load_dataset(*args, **kwargs) -> Dataset:
177 """
178 Open, load into memory, and close a dataset from the online repository
179 (requires internet).
(...)
211 load_dataset
212 """
--> 213 with open_dataset(*args, **kwargs) as ds:
214 return ds.load()
File /build/python-xarray-69jxB9/python-xarray-2025.01.2/xarray/tutorial.py:165, in open_dataset(name, cache, cache_dir, engine, **kws)
162 downloader = pooch.HTTPDownloader(headers=headers)
164 # retrieve the file
--> 165 filepath = pooch.retrieve(
166 url=url, known_hash=None, path=cache_dir, downloader=downloader
167 )
168 ds = _open_dataset(filepath, engine=engine, **kws)
169 if not cache:
File /usr/lib/python3/dist-packages/pooch/core.py:227, in retrieve(url, known_hash, fname, path, processor, downloader, progressbar)
222 action, verb = download_action(full_path, known_hash)
224 if action in ("download", "update"):
225 # We need to write data, so create the local data directory if it
226 # doesn't already exist.
--> 227 make_local_storage(path)
229 get_logger().info(
230 "%s data from '%s' to file '%s'.",
231 verb,
232 url,
233 str(full_path),
234 )
236 if downloader is None:
File /usr/lib/python3/dist-packages/pooch/utils.py:276, in make_local_storage(path, env)
272 if env is not None:
273 message.append(
274 f"Use environment variable '{env}' to specify a different location."
275 )
--> 276 raise PermissionError(" ".join(message)) from error
PermissionError: [Errno 13] Permission denied: '/sbuild-nonexistent' | Pooch could not create data cache folder '/sbuild-nonexistent/.cache/xarray_tutorial_data'. Will not be able to download data files.
In [5]: ds.to_zarr("rasm.zarr", mode="w")
Out[5]: <xarray.backends.zarr.ZarrStore at 0x7c5f82b381f0>
In [6]: zgroup = zarr.open("rasm.zarr")
In [7]: print(os.listdir("rasm.zarr"))
['latitude', 'longitude', '.zattrs', '.zgroup', '.zmetadata']
In [8]: print(zgroup.tree())
/
├── latitude (50,) float64
└── longitude (50,) float64
In [9]: dict(zgroup["Tair"].attrs)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
Cell In[9], line 1
----> 1 dict(zgroup["Tair"].attrs)
File /usr/lib/python3/dist-packages/zarr/hierarchy.py:511, in Group.__getitem__(self, item)
509 raise KeyError(item)
510 else:
--> 511 raise KeyError(item)
KeyError: 'Tair'