flake8/linter fixes

Author: brifordwylie

src/workbench/utils/chem_utils/mol_descriptors.py

@@ -346,14 +346,11 @@ def compute_descriptors(df: pd.DataFrame, include_mordred: bool = True, include_
 
     # Sanitize column names for AWS Athena compatibility
     # - Must be lowercase, no special characters except underscore, no spaces
-    result.columns = [
-        re.sub(r"_+", "_", re.sub(r"[^a-z0-9_]", "_", col.lower()))
-        for col in result.columns
-    ]
+    result.columns = [re.sub(r"_+", "_", re.sub(r"[^a-z0-9_]", "_", col.lower())) for col in result.columns]
 
     # Drop duplicate columns if any exist after sanitization
     if result.columns.duplicated().any():
-        logger.warning(f"Duplicate column names after sanitization - dropping duplicates!")
+        logger.warning("Duplicate column names after sanitization - dropping duplicates!")
         result = result.loc[:, ~result.columns.duplicated()]
 
     return result

src/workbench/utils/pandas_utils.py

@@ -158,13 +158,11 @@ def compare_dataframes(df1: pd.DataFrame, df2: pd.DataFrame, display_columns: li
         elif pd.api.types.is_float_dtype(df1[column]) or pd.api.types.is_float_dtype(df2[column]):
             # Float comparison within epsilon with NaNs treated as equal
             differences = ~((df1[column] - df2[column]).abs() <= epsilon) & ~(
-                    pd.isna(df1[column]) & pd.isna(df2[column])
+                pd.isna(df1[column]) & pd.isna(df2[column])
             )
         else:
             # Other types (int, Int64, etc.) - compare with NaNs treated as equal
-            differences = (df1[column] != df2[column]) & ~(
-                    pd.isna(df1[column]) & pd.isna(df2[column])
-            )
+            differences = (df1[column] != df2[column]) & ~(pd.isna(df1[column]) & pd.isna(df2[column]))
 
         # If differences exist, display them
         if differences.any():