Refactor handling of working portfolio in distribute_preset function to ensure proper checks for empty portfolios and maintain accurate filtering logic. This change improves robustness and clarity in the portfolio processing flow.

global_func/distribute_preset.py

@@ -22,16 +22,19 @@ def distribute_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols:
             print(finish_threshold)
             print(lower_threshold)
             print(working_portfolio[['Finish_percentile', 'Weighted Own']].sort_values(by='Finish_percentile', ascending=True).head(10))
-            curr_own_type_max = working_portfolio.loc[0, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[0, 'Weighted Own'])
+            if len(working_portfolio) == 0:
+                continue
+            elif len(working_portfolio) >= 1:
+                curr_own_type_max = working_portfolio.loc[0, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[0, 'Weighted Own'])
 
-            for i in range(1, len(working_portfolio)):
-                if working_portfolio.loc[i, 'Weighted Own'] > curr_own_type_max:
-                    rows_to_drop.append(i)
-                else:
-                    curr_own_type_max = working_portfolio.loc[i, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[i, 'Weighted Own'])
-            
-            working_portfolio = working_portfolio.drop(rows_to_drop).reset_index(drop=True)
-            concat_portfolio = pd.concat([concat_portfolio, working_portfolio])
+                for i in range(1, len(working_portfolio)):
+                    if working_portfolio.loc[i, 'Weighted Own'] > curr_own_type_max:
+                        rows_to_drop.append(i)
+                    else:
+                        curr_own_type_max = working_portfolio.loc[i, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[i, 'Weighted Own'])
+                
+                working_portfolio = working_portfolio.drop(rows_to_drop).reset_index(drop=True)
+                concat_portfolio = pd.concat([concat_portfolio, working_portfolio])
 
         if len(concat_portfolio) >= lineup_target:
             return concat_portfolio.sort_values(by='Finish_percentile', ascending=True).head(lineup_target)