Merge pull request #169 from alliander-opensource/fix/code-smells

Fix Sonar Code Smells

Author: bramstoeller

src/power_grid_model_io/converters/pandapower_converter.py

@@ -144,12 +144,13 @@ def _fill_extra_info(self, extra_info: ExtraInfo):
                     extra_info[pgm_id] = {"id_reference": {"table": pp_table, "index": pp_idx}}
         for component_data in self.pgm_input_data.values():
             for attr_name in component_data.dtype.names:
-                if NODE_REF_RE.fullmatch(attr_name):
-                    for pgm_id, node_id in component_data[["id", attr_name]]:
-                        if pgm_id not in extra_info:
-                            extra_info[pgm_id] = {attr_name: node_id}
-                        else:
-                            extra_info[pgm_id][attr_name] = node_id
+                if not NODE_REF_RE.fullmatch(attr_name):
+                    continue
+                for pgm_id, node_id in component_data[["id", attr_name]]:
+                    if pgm_id in extra_info:
+                        extra_info[pgm_id][attr_name] = node_id
+                    else:
+                        extra_info[pgm_id] = {attr_name: node_id}
 
     def _extra_info_to_idx_lookup(self, extra_info: ExtraInfo):
         """

src/power_grid_model_io/converters/tabular_converter.py

@@ -478,7 +478,7 @@ def _parse_col_def_filter(
                     value_column=sub_def["value_column"],
                 )
             elif isinstance(sub_def, list):
-                col_data = self._parse_pandas_function(data=data, table=table, function=name, col_def=sub_def)
+                col_data = self._parse_pandas_function(data=data, table=table, fn_name=name, col_def=sub_def)
             elif isinstance(sub_def, dict):
                 col_data = self._parse_function(data=data, table=table, function=name, col_def=sub_def)
             else:
@@ -549,13 +549,13 @@ def auto_id(row: np.ndarray):
 
         return col_data.apply(auto_id, axis=1, raw=True)
 
-    def _parse_pandas_function(self, data: TabularData, table: str, function: str, col_def: List[Any]) -> pd.DataFrame:
+    def _parse_pandas_function(self, data: TabularData, table: str, fn_name: str, col_def: List[Any]) -> pd.DataFrame:
         """Special vectorized functions.
 
         Args:
           data: The data
           table: The name of the current table
-          function: The name of the function.
+          fn_name: The name of the function.
           col_def: The definition of the function arguments
 
         Returns:
@@ -564,15 +564,15 @@ def _parse_pandas_function(self, data: TabularData, table: str, function: str, c
         assert isinstance(col_def, list)
 
         # "multiply" is an alias for "prod"
-        if function == "multiply":
-            function = "prod"
+        if fn_name == "multiply":
+            fn_name = "prod"
 
         col_data = self._parse_col_def(data=data, table=table, col_def=col_def, extra_info=None)
 
         try:
-            fn_ptr = getattr(col_data, function)
+            fn_ptr = getattr(col_data, fn_name)
         except AttributeError as ex:
-            raise ValueError(f"Pandas DataFrame has no function '{function}'") from ex
+            raise ValueError(f"Pandas DataFrame has no function '{fn_name}'") from ex
 
         # If the function expects an 'other' argument, apply the function per column (e.g. divide)
         empty = inspect.Parameter.empty
@@ -581,12 +581,12 @@ def _parse_pandas_function(self, data: TabularData, table: str, function: str, c
             n_columns = col_data.shape[1] if col_data.ndim > 1 else 1
             result = col_data.iloc[:, 0]
             for i in range(1, n_columns):
-                result = getattr(result, function)(other=col_data.iloc[:, i])
+                result = getattr(result, fn_name)(other=col_data.iloc[:, i])
             return pd.DataFrame(result)
 
         # If the function expects any argument
         if any(param.default == empty for name, param in fn_sig.parameters.items() if name != "kwargs"):
-            raise ValueError(f"Invalid pandas function DataFrame.{function}")
+            raise ValueError(f"Invalid pandas function DataFrame.{fn_name}")
 
         return pd.DataFrame(fn_ptr(axis=1))
 

src/power_grid_model_io/data_types/tabular_data.py

@@ -203,7 +203,7 @@ def items(self) -> Generator[Tuple[str, Union[pd.DataFrame, np.ndarray]], None,
         """
         Mimic the dictionary .items() function
 
-        Returns: An generator of the table names and the raw table data
+        Returns: A generator of the table names and the raw table data
         """
 
         # Note: PyCharm complains about the type, but it is correct, as an ItemsView extends from

src/power_grid_model_io/functions/_functions.py

@@ -100,8 +100,7 @@ def both_zeros_to_nan(value: float, other_value: float) -> float:
     value   0      value     nan
     nan     nan    value     nan
     """
-    if value == 0:
-        if other_value == 0 or not has_value(other_value):
-            _LOG.warning("0 replaced to nan")
-            return float("nan")
+    if value == 0 and (other_value == 0 or not has_value(other_value)):
+        _LOG.warning("0 replaced to nan")
+        return float("nan")
     return value

src/power_grid_model_io/utils/regex.py

@@ -42,7 +42,7 @@
 $               End of the string
 """
 
-PVS_EFFICIENCY_TYPE_RE = re.compile(r"[ ,..]1 pu: (95|97) %")
+PVS_EFFICIENCY_TYPE_RE = re.compile(r"[ ,.]1 pu: (95|97) %")
 r"""
 Regular expressions to match the efficiency type percentage at 1 pu, eg:
     - 0,1 pu: 93 %; 1 pu: 97 %

tests/unit/converters/test_tabular_converter.py

@@ -459,7 +459,7 @@ def test_parse_col_def_filter__pandas_function(mock_parse_function: MagicMock, c
 
     # Assert
     mock_parse_function.assert_called_once_with(
-        data=data, table="nodes", function="multiply", col_def=["id_number", "u_nom"]
+        data=data, table="nodes", fn_name="multiply", col_def=["id_number", "u_nom"]
     )
     pd.testing.assert_frame_equal(result, function_result)
 
@@ -707,7 +707,7 @@ def test_parse_pandas_function(
     mock_parse_col_def.return_value = parse_col_def_data
 
     # Act
-    result = converter._parse_pandas_function(data=data, table="foo", function=function, col_def=col_def)
+    result = converter._parse_pandas_function(data=data, table="foo", fn_name=function, col_def=col_def)
 
     # Assert
     mock_parse_col_def.assert_called_once_with(data=data, table="foo", col_def=col_def, extra_info=None)
@@ -723,7 +723,7 @@ def test_parse_pandas_function__no_data(mock_parse_col_def: MagicMock, converter
     mock_parse_col_def.return_value = parse_col_def_data
 
     # Act
-    result = converter._parse_pandas_function(data=data, table="foo", function="multiply", col_def=col_def)
+    result = converter._parse_pandas_function(data=data, table="foo", fn_name="multiply", col_def=col_def)
 
     # Assert
     mock_parse_col_def.assert_called_once_with(data=data, table="foo", col_def=col_def, extra_info=None)
@@ -737,17 +737,15 @@ def test_parse_pandas_function__invalid(mock_parse_col_def: MagicMock, converter
 
     # Act / Assert
     with pytest.raises(AssertionError):
-        converter._parse_pandas_function(
-            data=MagicMock(), table="foo", function="multiply", col_def=123  # type: ignore
-        )
+        converter._parse_pandas_function(data=MagicMock(), table="foo", fn_name="multiply", col_def=123)  # type: ignore
 
     # Act / Assert
     with pytest.raises(ValueError, match="Pandas DataFrame has no function 'bar'"):
-        converter._parse_pandas_function(data=MagicMock(), table="foo", function="bar", col_def=[])
+        converter._parse_pandas_function(data=MagicMock(), table="foo", fn_name="bar", col_def=[])
 
     # Act / Assert
     with pytest.raises(ValueError, match="Invalid pandas function DataFrame.apply"):
-        converter._parse_pandas_function(data=MagicMock(), table="foo", function="apply", col_def=[])
+        converter._parse_pandas_function(data=MagicMock(), table="foo", fn_name="apply", col_def=[])
 
 
 @patch("power_grid_model_io.converters.tabular_converter.get_function")