test: add unit tests for normalize_list_columns function

tests/test_pdhelper.py

@@ -0,0 +1,63 @@
+import pytest
+import pandas as pd
+from ia_collection_analyzer.pdhelper import normalize_list_columns
+
+@pytest.mark.parametrize(
+    "input_df,expected_df",
+    [
+        # Test mixed single/list values
+        (
+            pd.DataFrame({
+                'col1': ['a', ['b', 'c'], 'd'],
+                'col2': [1, [2, 3], 4]
+            }),
+            pd.DataFrame({
+                'col1': [['a'], ['b', 'c'], ['d']],
+                'col2': [[1], [2, 3], [4]]
+            })
+        ),
+        # Test single values only (should remain unchanged)
+        (
+            pd.DataFrame({'col1': ['a', 'b', 'c']}),
+            pd.DataFrame({'col1': ['a', 'b', 'c']})
+        ),
+        # Test lists only (should remain unchanged) 
+        (
+            pd.DataFrame({'col1': [['a'], ['b', 'c'], ['d']]}),
+            pd.DataFrame({'col1': [['a'], ['b', 'c'], ['d']]})
+        ),
+        # Test empty DataFrame with colums
+        (
+            pd.DataFrame(columns=['col1']),
+            pd.DataFrame(columns=['col1'])
+        ),
+        # Test empty DataFrame without columns
+        (
+            pd.DataFrame(),
+            pd.DataFrame()
+        ),
+        # Test with None/null values
+        (
+            pd.DataFrame({'col1': ['a', None, ['b']]}),
+            pd.DataFrame({'col1': [['a'], None, ['b']]})
+        ),
+        # Test multiple data types
+        (
+            pd.DataFrame({
+                'str_col': ['a', ['b'], 'c'],
+                'int_col': [1, [2], 3],
+                'float_col': [1.0, [2.0], 3.0],
+                'pure_list': [['x'], ['y'], ['z']]
+            }),
+            pd.DataFrame({
+                'str_col': [['a'], ['b'], ['c']],
+                'int_col': [[1], [2], [3]],
+                'float_col': [[1.0], [2.0], [3.0]],
+                'pure_list': [['x'], ['y'], ['z']]
+            })
+        )
+    ]
+)
+def test_normalize_list_columns(input_df, expected_df):
+    result = normalize_list_columns(input_df)
+    pd.testing.assert_frame_equal(result, expected_df)