allow creating references for empty archival datasets

virtualizarr/manifests/manifest.py

@@ -141,6 +141,15 @@ def __init__(self, entries: dict) -> None:
         self._offsets = offsets
         self._lengths = lengths
 
+    @classmethod
+    def empty(cls) -> "ChunkManifest":
+        """Create an empty chunk manifest."""
+        return cls.from_arrays(
+            paths=np.array((), dtype=np.dtypes.StringDType),
+            offsets=np.array((), dtype="uint64"),
+            lengths=np.array((), dtype="uint64"),
+        )
+
     @classmethod
     def from_arrays(
         cls,
@@ -257,6 +266,9 @@ def dict(self) -> ChunkDict:  # type: ignore[override]
         Entries whose path is an empty string will be interpreted as missing chunks and omitted from the dictionary.
         """
 
+        if len(self) == 0:
+            return cast(ChunkDict, {})
+
         coord_vectors = np.mgrid[
             tuple(slice(None, length) for length in self.shape_chunk_grid)
         ]

virtualizarr/readers/kerchunk.py

@@ -244,10 +244,8 @@ def variable_from_kerchunk_refs(
         manifest = ChunkManifest._from_kerchunk_chunk_dict(chunk_dict)
         varr = virtual_array_class(zarray=zarray, chunkmanifest=manifest)
     elif len(zarray.shape) != 0:
-        raise ValueError(
-            f"variable {var_name} appears to be broken:"
-            " it is supposed to have at least one chunk, but none can be found."
-        )
+        manifest = ChunkManifest.empty()
+        varr = virtual_array_class(zarray=zarray, chunkmanifest=manifest)
     else:
         # This means we encountered a scalar variable of dimension 0,
         # very likely that it actually has no numeric value and its only purpose

virtualizarr/tests/test_readers/test_kerchunk.py

@@ -1,5 +1,4 @@
 import numpy as np
-import pytest
 import ujson  # type: ignore
 
 from virtualizarr.manifests import ManifestArray
@@ -78,5 +77,8 @@ def test_empty_netcdf4():
     refs = gen_ds_refs(zarray=ujson.dumps(zarray))
     del refs["refs"]["a/0.0"]
 
-    with pytest.raises(ValueError, match="variable a appears to be broken"):
-        dataset_from_kerchunk_refs(refs)
+    ds = dataset_from_kerchunk_refs(refs)
+    assert "a" in ds.variables
+    assert isinstance(ds["a"].data, ManifestArray)
+    assert ds["a"].sizes == {"x": 100, "y": 200}
+    assert ds["a"].chunksizes == {"x": 50, "y": 100}

virtualizarr/tests/test_writers/test_kerchunk.py

@@ -39,6 +39,35 @@ def test_accessor_to_kerchunk_dict(self):
         result_ds_refs = ds.virtualize.to_kerchunk(format="dict")
         assert result_ds_refs == expected_ds_refs
 
+    def test_accessor_to_kerchunk_dict_empty(self):
+        manifest = ChunkManifest.empty()
+        arr = ManifestArray(
+            chunkmanifest=manifest,
+            zarray=dict(
+                shape=(2, 3),
+                dtype=np.dtype("<i8"),
+                chunks=(2, 3),
+                compressor=None,
+                filters=None,
+                fill_value=np.nan,
+                order="C",
+            ),
+        )
+        ds = Dataset({"a": (["x", "y"], arr)})
+
+        expected_ds_refs = {
+            "version": 1,
+            "refs": {
+                ".zgroup": '{"zarr_format":2}',
+                ".zattrs": "{}",
+                "a/.zarray": '{"shape":[2,3],"chunks":[2,3],"dtype":"<i8","fill_value":null,"order":"C","compressor":null,"filters":null,"zarr_format":2}',
+                "a/.zattrs": '{"_ARRAY_DIMENSIONS":["x","y"]}',
+            },
+        }
+
+        result_ds_refs = ds.virtualize.to_kerchunk(format="dict")
+        assert result_ds_refs == expected_ds_refs
+
     def test_accessor_to_kerchunk_json(self, tmp_path):
         manifest = ChunkManifest(
             entries={"0.0": dict(path="test.nc", offset=6144, length=48)}