Added facade functions to_zarr and from_zarr (#2236)

* Added facade functions `to_zarr` and `from_zarr`

* black

* added to changelog

* update PR with review comments

* fix rebase issues with changelog

* black

---------

Co-authored-by: Oriol (ZBook) <[email protected]>

Author: pSpitzner

CHANGELOG.md

@@ -6,14 +6,14 @@
 - Add InferenceData<->DataTree conversion functions ([2253](https://github.com/arviz-devs/arviz/pull/2253))
 - Bayes Factor plot: Use arviz's kde instead of the one from scipy ([2237](https://github.com/arviz-devs/arviz/pull/2237))
 - InferenceData objects can now be appended to existing netCDF4 files and to specific groups within them ([2227](https://github.com/arviz-devs/arviz/pull/2227))
+- Added facade functions `az.to_zarr` and `az.from_zarr` ([2236](https://github.com/arviz-devs/arviz/pull/2236))
 
 ### Maintenance and fixes
 - Replace deprecated np.product with np.prod ([2249](https://github.com/arviz-devs/arviz/pull/2249))
 - Fix numba deprecation warning ([2246](https://github.com/arviz-devs/arviz/pull/2246))
 - Fixes for creating numpy object array ([2233](https://github.com/arviz-devs/arviz/pull/2233) and [2239](https://github.com/arviz-devs/arviz/pull/2239))
 - Adapt histograms generated by plot_dist to input dtype ([2247](https://github.com/arviz-devs/arviz/pull/2247))
 
-
 ### Deprecation
 
 ### Documentation

arviz/data/__init__.py

@@ -15,6 +15,7 @@
 from .io_pyjags import from_pyjags
 from .io_pyro import from_pyro
 from .io_pystan import from_pystan
+from .io_zarr import from_zarr, to_zarr
 from .utils import extract, extract_dataset
 
 __all__ = [
@@ -44,6 +45,8 @@
     "to_datatree",
     "to_json",
     "to_netcdf",
+    "from_zarr",
+    "to_zarr",
     "CoordSpec",
     "DimSpec",
 ]

arviz/data/io_zarr.py

@@ -0,0 +1,46 @@
+"""Input and output support for zarr data."""
+
+from .converters import convert_to_inference_data
+from .inference_data import InferenceData
+
+
+def from_zarr(store):
+    return InferenceData.from_zarr(store)
+
+
+from_zarr.__doc__ = InferenceData.from_zarr.__doc__
+
+
+def to_zarr(data, store=None, **kwargs):
+    """
+    Convert data to zarr, optionally saving to disk if ``store`` is provided.
+
+    The zarr storage is using the same group names as the InferenceData.
+
+    Parameters
+    ----------
+    store : zarr.storage, MutableMapping or str, optional
+        Zarr storage class or path to desired DirectoryStore.
+        Default (None) a store is created in a temporary directory.
+    **kwargs : dict, optional
+        Passed to :py:func:`convert_to_inference_data`.
+
+    Returns
+    -------
+    zarr.hierarchy.group
+        A zarr hierarchy group containing the InferenceData.
+
+    Raises
+    ------
+    TypeError
+        If no valid store is found.
+
+
+    References
+    ----------
+    https://zarr.readthedocs.io/
+
+    """
+    inference_data = convert_to_inference_data(data, **kwargs)
+    zarr_group = inference_data.to_zarr(store=store)
+    return zarr_group

arviz/tests/base_tests/test_data_zarr.py

@@ -8,6 +8,7 @@
 import pytest
 
 from ... import InferenceData, from_dict
+from ... import to_zarr, from_zarr
 
 from ..helpers import (  # pylint: disable=unused-import
     chains,
@@ -103,3 +104,41 @@ def test_io_method(self, data, eight_schools_params, store, fill_attrs):
                 assert inference_data2.attrs["test"] == 1
             else:
                 assert "test" not in inference_data2.attrs
+
+    def test_io_function(self, data, eight_schools_params):
+        # create InferenceData and check it has been properly created
+        inference_data = self.get_inference_data(  # pylint: disable=W0612
+            data,
+            eight_schools_params,
+            fill_attrs=True,
+        )
+        test_dict = {
+            "posterior": ["eta", "theta", "mu", "tau"],
+            "posterior_predictive": ["eta", "theta", "mu", "tau"],
+            "sample_stats": ["eta", "theta", "mu", "tau"],
+            "prior": ["eta", "theta", "mu", "tau"],
+            "prior_predictive": ["eta", "theta", "mu", "tau"],
+            "sample_stats_prior": ["eta", "theta", "mu", "tau"],
+            "observed_data": ["J", "y", "sigma"],
+        }
+        fails = check_multiple_attrs(test_dict, inference_data)
+        assert not fails
+
+        assert inference_data.attrs["test"] == 1
+
+        # check filename does not exist and use to_zarr method
+        with TemporaryDirectory(prefix="arviz_tests_") as tmp_dir:
+            filepath = os.path.join(tmp_dir, "zarr")
+
+            to_zarr(inference_data, store=filepath)
+            # assert file has been saved correctly
+            assert os.path.exists(filepath)
+            assert os.path.getsize(filepath) > 0
+
+            inference_data2 = from_zarr(filepath)
+
+            # Everything in dict still available in inference_data2 ?
+            fails = check_multiple_attrs(test_dict, inference_data2)
+            assert not fails
+
+            assert inference_data2.attrs["test"] == 1

doc/source/api/data.rst

@@ -37,6 +37,8 @@ IO / General conversion
   to_datatree
   to_json
   to_netcdf
+  from_zarr
+  to_zarr
 
 
 General functions