Fix for storing dataframes with no data and only columns (#3)

Fixes #2 

The pytables library does not store anything for empty dataframe
and read_hdf excepts in this case. To fix this we check beforehand
if the HDF5 file is empty and in this case create the dataframe
from the columns attribute

aiida_dataframe/data/dataframe.py

@@ -62,8 +62,8 @@ def _update_dataframe(self, df: pd.DataFrame, filename: str | None = None) -> No
                 self.set_file(file, filename=filename)
 
         self.set_attribute("_pandas_data_hash", self._hash_dataframe(df))
-        self.set_attribute("index", list(self.df.index))
-        self.set_attribute("columns", list(self.df.columns.to_flat_index()))
+        self.set_attribute("index", list(df.index))
+        self.set_attribute("columns", list(df.columns.to_flat_index()))
 
     @staticmethod
     def _hash_dataframe(df):
@@ -82,7 +82,13 @@ def _get_dataframe_from_repo(self) -> pd.DataFrame:
                     # Copy the content of source to target in chunks
                     shutil.copyfileobj(file, temp_handle)  # type: ignore[arg-type]
 
-            return pd.read_hdf(Path(td) / self.filename)
+            # Workaround for empty dataframe
+            with pd.HDFStore(
+                Path(td) / self.filename, mode="r", errors="strict"
+            ) as store:
+                if len(store.groups()) == 0:
+                    return pd.DataFrame([], columns=self.get_attribute("columns"))
+                return pd.read_hdf(store)
 
     def _get_dataframe(self) -> pd.DataFrame:
         """

tests/test_data.py

@@ -408,3 +408,25 @@ def test_setitem_modification(entry_point):
     loaded = load_node(node.pk)
     assert loaded is not node
     assert_frame_equal(loaded.df, df_changed)
+
+
+@pytest.mark.parametrize(
+    "entry_point",
+    ("dataframe.frame",),
+)
+def test_empty_dataframe(entry_point):
+    """
+    Test that storing an empty dataframe works
+    """
+
+    PandasFrameData = DataFactory(entry_point)
+
+    # Example from pandas Docs
+    df = pd.DataFrame([], columns=["A", "B"])
+
+    node = PandasFrameData(df)
+    node.store()
+
+    loaded = load_node(node.pk)
+    assert loaded is not node
+    assert_frame_equal(loaded.df, df)