sharding with empty inner chunk and index location start (#2336)

* test_sharding_with_empty_inner_chunk

* only update non-empty chunks offset

* format

* Update test_sharding.py

* format

---------

Co-authored-by: Norman Rzepka <[email protected]>

Author: brokkoli71

Diff for: src/zarr/codecs/pipeline.py

@@ -162,7 +162,6 @@ async def decode_batch(
     ) -> Iterable[NDBuffer | None]:
         chunk_bytes_batch: Iterable[Buffer | None]
         chunk_bytes_batch, chunk_specs = _unzip2(chunk_bytes_and_specs)
-
         (
             aa_codecs_with_spec,
             ab_codec_with_spec,

Diff for: src/zarr/codecs/sharding.py

@@ -265,7 +265,8 @@ async def finalize(
     ) -> Buffer:
         index_bytes = await index_encoder(self.index)
         if index_location == ShardingCodecIndexLocation.start:
-            self.index.offsets_and_lengths[..., 0] += len(index_bytes)
+            empty_chunks_mask = self.index.offsets_and_lengths[..., 0] == MAX_UINT_64
+            self.index.offsets_and_lengths[~empty_chunks_mask, 0] += len(index_bytes)
             index_bytes = await index_encoder(self.index)  # encode again with corrected offsets
             out_buf = index_bytes + self.buf
         else:

Diff for: tests/test_codecs/test_sharding.py

@@ -366,3 +366,30 @@ async def test_delete_empty_shards(store: Store) -> None:
 def test_pickle() -> None:
     codec = ShardingCodec(chunk_shape=(8, 8))
     assert pickle.loads(pickle.dumps(codec)) == codec
+
+
+@pytest.mark.parametrize("store", ["local", "memory"], indirect=["store"])
+@pytest.mark.parametrize(
+    "index_location", [ShardingCodecIndexLocation.start, ShardingCodecIndexLocation.end]
+)
+async def test_sharding_with_empty_inner_chunk(
+    store: Store, index_location: ShardingCodecIndexLocation
+) -> None:
+    data = np.arange(0, 16 * 16, dtype="uint32").reshape((16, 16))
+    fill_value = 1
+
+    path = f"sharding_with_empty_inner_chunk_{index_location}"
+    spath = StorePath(store, path)
+    a = await AsyncArray.create(
+        spath,
+        shape=(16, 16),
+        chunk_shape=(8, 8),
+        dtype="uint32",
+        fill_value=fill_value,
+        codecs=[ShardingCodec(chunk_shape=(4, 4), index_location=index_location)],
+    )
+    data[:4, :4] = fill_value
+    await a.setitem(..., data)
+    print("read data")
+    data_read = await a.getitem(...)
+    assert np.array_equal(data_read, data)