Handle multiindex

python/arcticdb/version_store/_normalization.py

@@ -291,7 +291,6 @@ def _from_tz_timestamp(ts, tz):
 def _normalize_single_index(index, index_names, index_norm, dynamic_strings=None, string_max_len=None):
     # index: pd.Index or np.ndarray -> np.ndarray
     index_tz = None
-
     if isinstance(index_norm, NormalizationMetadata.PandasIndex) and not index_norm.is_physically_stored:
         if index.name:
             if not isinstance(index.name, int) and not isinstance(index.name, str):
@@ -525,7 +524,11 @@ def denormalize(self, item, norm_meta):
 class _PandasNormalizer(Normalizer):
     def _index_to_records(self, df, pd_norm, dynamic_strings, string_max_len):
         index = df.index
-        if isinstance(index, MultiIndex):
+        if len(index) == 0 and len(df.select_dtypes(include="category").columns) == 0:
+            index_norm = pd_norm.index
+            index_norm.is_physically_stored = False
+            index = Index([])
+        elif isinstance(index, MultiIndex):
             # This is suboptimal and only a first implementation since it reduplicates the data
             index_norm = pd_norm.multi_index
             index_norm.field_count = len(index.levels) - 1

python/tests/unit/arcticdb/version_store/test_empty_column_type.py

@@ -69,7 +69,7 @@ def dtype(request):
     yield request.param
 
 
-@pytest.fixture(params=[pd.RangeIndex(0,0), pd.DatetimeIndex([])])
+@pytest.fixture(params=[pd.RangeIndex(0,0), pd.DatetimeIndex([]), pd.MultiIndex.from_arrays([[],[]], names=["a", "b"])])
 def empty_index(request):
     yield request.param
 
@@ -569,6 +569,7 @@ def test_date(self, lmdb_version_store_static_and_dynamic, date_dtype):
             )
         )
 
+
 class TestCanAppendToEmptyColumn:
     """
     Tests that it's possible to append to a column which contains no rows. The type of the columns, including the index