Translate h5py soft and hard linked datasets with an optional kwarg

kerchunk/hdf.py

@@ -113,22 +113,39 @@ def __init__(
         self.error = error
         lggr.debug(f"HDF5 file URI: {self._uri}")
 
-    def translate(self):
+    def translate(self, preserve_linked_dsets=False):
         """Translate content of one HDF5 file into Zarr storage format.
 
         This method is the main entry point to execute the workflow, and
         returns a "reference" structure to be used with zarr/kerchunk
 
         No data is copied out of the HDF5 file.
 
+        Parameters
+        ----------
+        preserve_linked_dsets : bool (optional, default False)
+            If True, translate HDF5 soft and hard links for each `h5py.Dataset`
+            into the reference structure. Requires h5py version 3.11.0 or later.
+            Will not translate external links or links to `h5py.Group` objects.
+
         Returns
         -------
         dict
             Dictionary containing reference structure.
         """
         lggr.debug("Translation begins")
         self._transfer_attrs(self._h5f, self._zroot)
+
         self._h5f.visititems(self._translator)
+
+        if preserve_linked_dsets:
+            if h5py.__version__ < "3.11.0":
+                raise RuntimeError(
+                    "preserve_linked_dsets requires h5py 3.11.0 or later, "
+                    f"found {h5py.__version__}"
+                )
+            self._h5f.visititems_links(self._translator)
+
         if self.spec < 1:
             return self.store
         elif isinstance(self.store, LazyReferenceMapper):
@@ -247,10 +264,23 @@ def _decode_filters(self, h5obj: Union[h5py.Dataset, h5py.Group]):
                 )
         return filters
 
-    def _translator(self, name: str, h5obj: Union[h5py.Dataset, h5py.Group]):
+    def _translator(
+        self,
+        name: str,
+        h5obj: Union[
+            h5py.Dataset, h5py.Group, h5py.SoftLink, h5py.HardLink, h5py.ExternalLink
+        ],
+    ):
         """Produce Zarr metadata for all groups and datasets in the HDF5 file."""
         try:  # method must not raise exception
             kwargs = {}
+
+            if isinstance(h5obj, h5py.SoftLink) or isinstance(h5obj, h5py.HardLink):
+                h5obj = self._h5f[name]
+                if isinstance(h5obj, h5py.Group):
+                    # continues iteration of visititems_links
+                    return None
+
             if isinstance(h5obj, h5py.Dataset):
                 lggr.debug(f"HDF5 dataset: {h5obj.name}")
                 lggr.debug(f"HDF5 compression: {h5obj.compression}")
@@ -432,7 +462,7 @@ def _translator(self, name: str, h5obj: Union[h5py.Dataset, h5py.Group]):
                         )
 
                 # Create a Zarr array equivalent to this HDF5 dataset...
-                za = self._zroot.create_dataset(
+                za = self._zroot.require_dataset(
                     h5obj.name,
                     shape=h5obj.shape,
                     dtype=dt or h5obj.dtype,
@@ -480,7 +510,7 @@ def _translator(self, name: str, h5obj: Union[h5py.Dataset, h5py.Group]):
 
             elif isinstance(h5obj, h5py.Group):
                 lggr.debug(f"HDF5 group: {h5obj.name}")
-                zgrp = self._zroot.create_group(h5obj.name)
+                zgrp = self._zroot.require_group(h5obj.name)
                 self._transfer_attrs(h5obj, zgrp)
         except Exception as e:
             import traceback

kerchunk/tests/test_hdf.py

@@ -6,6 +6,7 @@
 import pytest
 import xarray as xr
 import zarr
+import h5py
 
 from kerchunk.hdf import SingleHdf5ToZarr
 from kerchunk.combine import MultiZarrToZarr, drop
@@ -92,9 +93,11 @@ def test_multizarr(generate_mzz):
         assert set(ds) == set(expected)
         for name in ds:
             exp = {
-                k: (v.tolist() if v.size > 1 else v[0])
-                if isinstance(v, np.ndarray)
-                else v
+                k: (
+                    (v.tolist() if v.size > 1 else v[0])
+                    if isinstance(v, np.ndarray)
+                    else v
+                )
                 for k, v in expected[name].attrs.items()
             }
             assert dict(ds[name].attrs) == dict(exp)
@@ -331,3 +334,27 @@ def test_inline_threshold():
         fn, inline_threshold=1e9
     ).translate()
     assert inline_0 != inline_1_million
+
+
+@pytest.mark.skipif(
+    not h5py.__version__ >= "3.11.0",
+    reason="'h5py.Group.visititems_links' requires h5py 3.11.0 or later",
+)
+def test_translate_links():
+    fn = osp.join(here, "air_linked.nc")
+    # choose a threshold that will give both inline and non-inline
+    # datasets for maximum test coverage
+    out = kerchunk.hdf.SingleHdf5ToZarr(fn, inline_threshold=50).translate(
+        preserve_linked_dsets=True
+    )
+    fs = fsspec.filesystem("reference", fo=out)
+    z = zarr.open(fs.get_mapper())
+
+    # 1. Test the hard linked datasets were translated correctly
+    # 2. Test the soft linked datasets were translated correctly
+    for link in ("hard", "soft"):
+        for dset in ("lat", "time"):
+            np.testing.assert_allclose(z[dset], z[f"{dset}_{link}"])
+            for key in z[f"{dset}_{link}"].attrs.keys():
+                if key not in kerchunk.hdf._HIDDEN_ATTRS and key != "_ARRAY_DIMENSIONS":
+                    assert z[f"{dset}_{link}"].attrs[key] == z[dset].attrs[key]