Implement vectorized calculations for salary, median, and ownership in app.py to enhance performance and memory efficiency. Refactor reassess_edge and stratification_function to minimize DataFrame copies and improve memory management. Update filtering logic to use boolean masks for better efficiency.

Refactor 'Manage Portfolio' logic to directly use reassess_edge for both working and export frames, streamlining data processing and enhancing efficiency.

Enhance reassess_edge function by adding max_salary parameter to improve salary handling in the predict_dupes call, ensuring more accurate edge reassessment.

Refactor reassess_edge function in reassess_edge.py to improve efficiency by concatenating modified and base frames, simplifying the extraction of updated rows, and enhancing clarity in the logic for processing modified data.

Refactor app.py to replace predict_dupes calls with reassess_edge for both working and export frames, enhancing the accuracy of edge assessments by utilizing the updated reassess_edge function in reassess_edge.py.

Refactor dupe adjustment logic in reassess_dupes function of reassess_edge.py to conditionally apply adjustments based on salary_diff, ensuring accurate calculations for positive salary differences while maintaining original dupes for non-positive differences.

Update reassess_finish_percentile calculation in reassess_edge.py to use max() instead of min(), ensuring that the finish_percentile does not fall below the sum of a minimum threshold and 'Win%', thereby enhancing the accuracy of lineup assessments.

Update reassess_finish_percentile calculation in reassess_edge.py to ensure it does not exceed the sum of a minimum threshold and 'Win%', enhancing accuracy in lineup assessments.

Update return logic in reassess_lineup_edge function of reassess_edge.py to use 'Lineup Edge' instead of 'Finish_percentile', ensuring accurate calculations of lineup edge assessments.

Refactor dupe rate calculation in reassess_lineup_edge function of reassess_edge.py to use min() instead of clip(), improving clarity and ensuring accurate handling of zero previous dupes.

Update reassess_lineup_edge function in reassess_edge.py to handle cases where previous dupes are zero, ensuring robust calculations by clipping the dupe rate. This change enhances the accuracy of lineup edge assessments.

Enhance reassess_lineup_edge function in reassess_edge.py to incorporate previous finish_percentile and dupes for improved lineup edge calculations. Update the return logic to better reflect the relationship between finish_percentile and lineup edge, ensuring more accurate assessments.

Refactor reassess_lineup_edge function in reassess_edge.py to improve clarity by using local variables for calculations. Update references to 'Edge' to 'Lineup Edge' for consistency, and adjust column drop logic to retain necessary data for further processing.

Update reassess_finish_percentile calculation in reassess_edge.py to adjust ownership impact by changing the divisor for own_diff from 2 to 200, improving accuracy in finish_percentile adjustments.

Comment out the column drop logic in reassess_edge function to retain additional data for debugging purposes, enhancing flexibility in data handling.

Refactor reassess_finish_percentile function in reassess_edge.py to remove unnecessary parameters, streamlining the calculation of finish_percentile. Update references in reassess_edge function to align with the new function signature, enhancing code clarity and maintainability.

Refactor reassess_finish_percentile function in reassess_edge.py to simplify calculations by using ownership and median differences, improving accuracy in finish_percentile adjustments. Update column drop logic to remove unnecessary columns for cleaner data handling.

Implement reassess_finish_percentile function in reassess_edge.py to recalculate finish_percentile based on ownership and contest size, enhancing accuracy in ownership adjustments. Remove debug print statements from app.py for cleaner code.

Refactor final_dupes calculation in reassess_dupes function to use max() for non-negative values, improving clarity and ensuring accurate ownership adjustments.

Update final_dupes calculation in reassess_dupes function to ensure non-negative values by applying a lower clip, enhancing accuracy in ownership adjustments.

Refine reassess_dupes function in reassess_edge.py to enhance the threshold crossing logic for salary adjustments, ensuring accurate reduction of dupes when salaries transition from above to below the threshold, while maintaining clarity and readability.

Enhance reassess_dupes function in reassess_edge.py by implementing a threshold-based adjustment mechanism for dupes, improving accuracy in ownership calculations while removing redundant debug statements for cleaner code.

Refactor reassess_dupes function in reassess_edge.py to improve clarity by introducing local variables for salary, salary_diff, own_diff, and dupes, enhancing readability while maintaining existing logic for ownership adjustments.

Add additional debug statements in reassess_dupes function to log detailed calculations and type checks for salary adjustments, further enhancing troubleshooting capabilities.

more debugging

Add debug statement in reassess_dupes function to log salary value, enhancing troubleshooting capabilities for ownership adjustments.

ping

Refactor reassess_dupes function in reassess_edge.py to improve readability by restructuring the return statement, while maintaining the existing logic for salary and ownership adjustments.

Add debug statement in reassess_dupes function to log salary and ownership differences, enhancing troubleshooting capabilities for ownership adjustments.

Refactor reassess_dupes function in reassess_edge.py to enhance ownership calculation by incorporating a more detailed salary and ownership adjustment mechanism, improving accuracy in metrics.

ping

Add debug print statement in reassess_dupes function to log detailed calculations for ownership adjustments, aiding in troubleshooting and validation of metrics.

Update data type handling for salary, median, and ownership difference calculations in reassess_edge.py to improve memory efficiency and precision.

Update reassess_dupes function in reassess_edge.py to adjust ownership calculation by modifying the salary adjustment factor, enhancing accuracy in ownership metrics.

Remove debug print statement from calculate_weighted_ownership_single_row and fix geomean calculation in reassess_edge function for improved accuracy in ownership metrics.

Add debug print statement for ownership values in calculate_weighted_ownership_single_row to aid in troubleshooting and validation of ownership calculations.

Refactor ownership value calculation in calculate_weighted_ownership_single_row to use pd.to_numeric for better handling of non-numeric values, improving robustness in edge reassessment logic.

Refactor calculate_weighted_ownership function to operate on a single row of ownership values, improving clarity and performance in the reassess_edge function.

Optimize ownership calculation in reassess_edge function by directly applying calculate_weighted_ownership_wrapper to selected lineups, improving performance and readability.

Fix off-by-one error in own_columns generation in reassess_edge function to ensure correct player ownership mapping.

Update reassess_edge function to include maps_dict parameter for improved player ownership mapping in app.py, enhancing edge reassessment logic.

Update num_players calculation in reassess_edge function to use salary column index, improving accuracy in player data processing.

Refactor reassess_lineup_edge function in global_func/reassess_edge.py to simplify the calculation of 'Lineup Edge' by removing unnecessary lambda application, improving code readability and performance.

Refactor reassess_edge function signature in global_func/reassess_edge.py to simplify parameters and update app.py to utilize the new signature, enhancing edge reassessment logic for player data processing.

Refactor reassess_lineup_edge function in reassess_edge.py to simplify the application of lineup edge calculations, enhancing code clarity and maintainability.

Rename reassess_edge function to reassess_lineup_edge in reassess_edge.py for clarity, and update references accordingly to improve code readability and maintainability.

Fix reassess_dupes function in reassess_edge.py to remove clipping on calculated values, ensuring accurate salary difference assessments for player lineups.

Refactor change_mask logic in reassess_edge.py to filter based solely on median differences, improving accuracy in edge assessments for player lineups.

Add reassess_edge function in reassess_edge.py for recalculating lineup metrics based on player performance, and update app.py to utilize this function for improved edge assessments in player lineups.

Refactor position eligibility checks in exposure_spread.py to simplify logic for player positions, enhancing readability and maintainability. Update reassess_dupes function in reassess_edge.py to streamline salary difference calculations for improved performance.