Fix a regression with scalar indexing due to #1800

docs/release.rst

@@ -31,6 +31,8 @@ Docs
 
 Maintenance
 ~~~~~~~~~~~
+* Fix a regression when getting or setting a single value from arrays with size-1 chunks.
+  By :user:`Deepak Cherian <dcherian>` :issue:`1874`
 
 Deprecations
 ~~~~~~~~~~~~

zarr/core.py

@@ -2030,7 +2030,9 @@ def _process_chunk(
             and not self._filters
             and self._dtype != object
         ):
-            dest = out[out_selection]
+            # For 0D arrays out_selection = () and out[out_selection] is a scalar
+            # Avoid that
+            dest = out[out_selection] if out_selection else out
             # Assume that array-like objects that doesn't have a
             # `writeable` flag is writable.
             dest_is_writable = getattr(dest, "writeable", True)

zarr/indexing.py

@@ -52,6 +52,8 @@ def is_scalar(value, dtype):
         return True
     if isinstance(value, tuple) and dtype.names and len(value) == len(dtype.names):
         return True
+    if dtype.kind == "O" and not isinstance(value, np.ndarray):
+        return True
     return False
 
 

zarr/tests/test_core.py

@@ -3157,3 +3157,52 @@ def test_issue_1279(tmpdir):
 
     written_data = ds_reopened[:]
     assert_array_equal(data, written_data)
+
+
+def test_scalar_indexing():
+    store = zarr.KVStore({})
+
+    store["a"] = zarr.create((3,), chunks=(1,), store=store)
+    store["a"][:] = [1, 2, 3]
+
+    assert store["a"][1] == np.array(2.0)
+    assert store["a"][(1,)] == np.array(2.0)
+
+    store["a"][slice(1)] = [-1]
+    assert store["a"][0] == np.array(-1)
+
+    store["a"][0] = -2
+    assert store["a"][0] == np.array(-2)
+
+    store["a"][slice(1)] = (-3,)
+    assert store["a"][0] == np.array(-3)
+
+
+def test_object_array_indexing():
+    # regression test for #1874
+    from numcodecs import MsgPack
+
+    root = zarr.group()
+    arr = root.create_dataset(
+        name="my_dataset",
+        shape=0,
+        dtype=object,
+        object_codec=MsgPack(),
+    )
+    new_items = [
+        ["A", 1],
+        ["B", 2, "hello"],
+    ]
+    arr_add = np.empty(len(new_items), dtype=object)
+    arr_add[:] = new_items
+    arr.append(arr_add)
+
+    # heterogeneous elements
+    elem = ["C", 3]
+    arr[0] = elem
+    assert arr[0] == elem
+
+    # homogeneous elements
+    elem = [1, 3]
+    arr[1] = elem
+    assert arr[1] == elem