Add clarifying comments addressing code review feedback

Explain cross-version compatibility requirements for annotation strings and dtype conversion logic

Co-authored-by: soxofaan <44946+soxofaan@users.noreply.github.com>

Author: Copilot

openeo/extra/job_management/_manager.py

@@ -94,8 +94,10 @@ def normalize_df(self, df: pd.DataFrame) -> pd.DataFrame:
         """
         new_columns = {col: req.default for (col, req) in self._requirements.items() if col not in df.columns}
         df = df.assign(**new_columns)
-        # Apply dtype conversions to ensure compatibility with pandas 3's stricter type checking
-        # This is especially important for columns that may contain NaN values but need to be strings
+        # Apply dtype conversions to ensure compatibility with pandas 3's stricter type checking.
+        # This is especially important for columns that may contain NaN values but need to be strings.
+        # We only convert columns with specific dtype requirements (e.g., "str", "float64").
+        # Columns with dtype="object" are skipped because "object" is pandas' flexible catch-all type.
         dtype_conversions = {}
         for col, req in self._requirements.items():
             if col in df.columns and req.dtype != "object":

openeo/udf/run_code.py

@@ -78,11 +78,14 @@ def _get_annotation_str(annotation: Union[str, type]) -> str:
 
 def _annotation_is_pandas_series(annotation) -> bool:
     # Support both pandas 2.x ("pandas.core.series.Series") and pandas 3.x ("pandas.Series")
+    # We explicitly list both paths to ensure cross-version compatibility:
+    # - UDFs written with pandas 2.x annotations should work in pandas 3.x environments
+    # - UDFs written with pandas 3.x annotations should work in pandas 2.x environments
     return annotation in {
         pandas.Series,
-        _get_annotation_str(pandas.Series),
-        "pandas.core.series.Series",  # Legacy pandas 2.x path
-        "pandas.Series",  # pandas 3.x path
+        _get_annotation_str(pandas.Series),  # Current pandas version's path
+        "pandas.core.series.Series",  # Explicit pandas 2.x path for cross-version support
+        "pandas.Series",  # Explicit pandas 3.x path for cross-version support
     }