Update DK and FD lineup functions in app.py to include a limit parameter for enhanced lineup generation control. This change allows users to specify the maximum number of lineups generated, improving customization and flexibility in lineup creation.

Refactor FD lineup data retrieval in app.py to streamline logic for handling priority variables and slate types. This update consolidates the data fetching process, ensuring consistent DataFrame creation and enhancing overall code readability and maintainability.

Refactor lineup data retrieval in app.py to streamline DataFrame creation by ensuring consistent indentation and structure. This change enhances code readability and maintains clarity in the data processing for both DK and FD lineup functions.

Refactor lineup data retrieval in app.py to replace direct cursor concatenation with DataFrame conversion for improved data handling. This change enhances the clarity and structure of the data being processed in both DK and FD lineup functions.

Refactor lineup data retrieval in app.py to use math.ceil for limit calculations in DK and FD functions. This change ensures accurate rounding for the number of records fetched based on the priority mix, enhancing data integrity in lineup generation.

Enhance DK and FD lineup functions in app.py by introducing a priority mix parameter for improved lineup customization. This update allows users to specify a mix of projection and ownership when no priority variable is selected, enhancing the flexibility and effectiveness of lineup generation.

Add priority variable selection to optimals tab in app.py for enhanced lineup customization. This update allows users to choose between 'proj' and 'Own' as priority variables, improving the flexibility of lineup configurations.

Enhance lineup initialization in app.py by adding a priority variable to the DK and FD lineup functions. This update allows for sorting of lineup data based on user-defined priorities, improving lineup customization and data retrieval efficiency.

Update salary calculation in app.py by adjusting the Salary column values to be divided by 1.5. This change improves the accuracy of salary data in the application.

Implement error handling for tab selection in app.py by wrapping the segmented control in a try-except block. This enhancement ensures that the application remains functional even if an error occurs during tab selection, improving overall stability and user experience.

Refactor tab navigation in app.py by replacing tabbed interface with a segmented control for improved user experience. This change allows users to select between "Scoring Percentages", "Player ROO", "Optimals", and "Handbuilder" more intuitively, enhancing the overall layout and accessibility of the application.

Update FanDuel stack input limits in app.py to allow a maximum of 5 stacks, enhancing user flexibility in lineup configuration. This change aligns the input options with those available for DraftKings, improving consistency across platforms.

Enhance salary input functionality in app.py by adding conditional logic for minimum and maximum salary based on slate type for FanDuel. This update allows users to set different salary ranges for Regular and Showdown slates, improving flexibility in lineup management.

Update fd_sd_columns in app.py to include FLEX5, enhancing data structure for saved lineups. This change ensures consistency across column definitions for better functionality in lineup management.

Add clear saved lineups functionality in app.py by introducing a new button to delete saved lineups from session state. This update enhances user control over saved data and improves overall user experience by providing a clearer interface for managing lineups.

Update lineup saving logic in app.py to use lineup_display_df for storing player data. This change ensures consistency in saved lineups and improves the overall functionality of the save feature.

Update column layout in app.py to adjust button spacing and enhance visual clarity. Add conditional display for saved lineups, improving user feedback when no lineups are available. This update streamlines the user experience by providing clearer information on lineup status.

Add handbuilder lineup export functionality in app.py by introducing a new export button. This allows users to download saved lineups as a CSV file, enhancing data management and user experience. Additionally, new column definitions for DraftKings and FanDuel handbuilder exports have been added for improved clarity.

Add clear and save lineup buttons in app.py to enhance user interaction. The clear button resets the lineup, while the save button allows users to store their lineups in session state, improving overall functionality and user experience.

Add informational tooltip in app.py for optimals filters to enhance user guidance. Adjust column layout for download buttons to streamline the export process, improving overall user experience.

Enhance data export functionality in app.py by adding a fourth column for stack inputs and implementing filters for minimum and maximum salary and stack counts. This update improves user experience by allowing more granular control over exported data for both DraftKings and FanDuel.

Add new convert_pm_df function for Portfolio Manager exports in app.py. Update download buttons to utilize this new function, enhancing data export functionality and ensuring consistent CSV formatting for both IDs and Names.

Refactor data export logic in app.py to remove unnecessary index settings for columns in DraftKings and FanDuel exports. This change enhances data clarity by ensuring only relevant columns are dropped, streamlining the export process for both Portfolio Manager options.

Refactor data export logic in app.py to ensure consistent column dropping and index setting for DraftKings and FanDuel across slate types. This update improves data clarity and maintains a streamlined export process for both Portfolio Manager options.

Refactor data export logic in app.py to streamline column dropping and index setting for DraftKings and FanDuel. This update enhances the clarity of exported data by ensuring consistent handling across different slate types, improving overall user experience.

Enhance data export functionality in app.py by implementing conditional column dropping and index setting based on selected site and slate type for both DraftKings and FanDuel. This update ensures accurate data formatting for Portfolio Manager exports, improving user experience and data clarity.

Refactor data export handling in app.py by removing unnecessary index setting in download button data. This change simplifies the export process for both Portfolio Manager options, ensuring cleaner data output.

Refactor download button layout in app.py to improve organization and accessibility of export options. Adjusted column widths for Regular and Portfolio Manager exports, ensuring a more user-friendly interface for data downloads.

Remove unused variable pm_export in app.py to clean up code and improve clarity in data handling for slate types.

Refactor download button data handling in app.py to use convert_df_to_csv for ROO exports. This change improves data export functionality for both Regular and Portfolio Manager options, ensuring consistent file formatting.

Add download buttons for ROO exports in app.py based on slate type. Implemented separate export options for Regular and Showdown slates, enhancing user functionality and data accessibility.

Remove unused gspread import from app.py to streamline dependencies and improve code clarity.

Update scoring percentages calculation in app.py to include separate metrics for DraftKings and FanDuel. This change enhances the data structure by introducing 'DK_Runs/$' and 'FD_Runs/$', while also refining the handling of average salary columns for each platform, improving overall data accuracy for player selection.

Update app.py to include 'FLEX5' in player selection for various slate types. This change enhances the data structure for player lineups, ensuring compatibility with expanded player options in the application.

Refactor player selection logic in app.py to improve handling of 'Top (1-5)' and 'Mid (4-8)' conditions. This update introduces additional player selection when the count is less than auto_size_var, ensuring accurate sorting and selection of players, thereby enhancing the application's functionality.

Enhance player selection logic in app.py by adding display of selected players for 'Mid (4-8)' condition. This update improves user feedback by showing the selected players when the count is less than the specified auto_size_var, thereby enhancing the application's usability.

Update player selection logic in app.py to correctly handle additional player selection for 'Mid (4-8)' condition. This change ensures that the logic accommodates the specified auto_size_var, enhancing the accuracy of player selection in the application.

Enhance player selection logic in app.py to ensure accurate handling of auto_size_var for 'Top (1-5)' and 'Mid (4-8)' conditions. This update improves player selection by allowing for an additional player when the selected count is less than the specified size, thereby enhancing the application's functionality.

Fix player selection logic in app.py to correctly handle auto_size_var for 'Mid (4-8)' condition. This adjustment ensures accurate player selection based on the specified size, enhancing the functionality of the application.

Refactor player selection logic in app.py to accommodate dynamic auto size

Refactor player data mapping in app.py to improve position-based logic

Enhance data handling in app.py by expanding player data mapping

Comment out redundant player index setting in app.py to prevent potential errors during data display. This change maintains the existing functionality while improving error handling in the data presentation logic.

Refactor player count logic in app.py to enhance clarity

Refactor opponent and team total mapping in app.py for improved data handling

Refactor data mapping in app.py to simplify opponent assignment

Remove redundant CSS rule for portal element in app.py to streamline styling

Update CSS in app.py to further adjust font size for portal element

Update CSS in app.py to adjust font size for portal element

Add CSS rule in app.py to set font size for table rows