Roadmap¶
This document outlines some possible new features and enhancements for the application, as well as known issues that are being tracked.
New Features¶
Simplify the extraction of unique dependencies: Currently, there is no efficient method to quickly extract unique forward and backward dependencies, along with their minimum dependency levels, for a given field, parameter, or sheet, as demonstrated on the Example page. By expanding the output Excel file to include additional precalculated columns, we can streamline this process and make it more user-friendly.
Batch processing: implement functionality to process multiple Tableau workbooks at once
Remove multi-line comments from cleaned calculations: Currently, multi-line comments are not removed from the cleaned calculated field expressions in the output Excel file. The goal is to eliminate all single- and multi-line comments from the original calculation expressions.
Provide Linux and macOS executables: Develop and distribute executables for the tool compatible with Linux and macOS, expanding accessibility for users on different operating systems.
Known Issues¶
Some of these issues stem from limitations within the tool.
Others are related to the current version of the tableaudocumentapi Python
package, which at the moment doesn’t appear to be actively developed.
The lack of new releases may be related to emerging alternatives, such as the
official Tableau Metadata API and other third-party solutions for managing
Tableau workbooks.
Incomplete Processing of Tableau Workbooks: Some Tableau workbooks generate errors during analysis, and further investigation is needed to identify the causes and implement necessary bug fixes.
Not all dependencies are captured: Some fields may be used solely to initialize parameter values when the workbook is opened, while data source fields may depend on fields hidden in the data source and not visible in the dashboard; additionally, fields and parameters may be utilized in dashboard actions.
Not all field captions are captured: Field captions may be missing, resulting in the use of their internal ID in the outputs, which may relate to hidden fields and dependencies.
Not all extracted fields are assigned to the correct data source: Some (copies of) fields may be linked to a data source to which they do not belong.
Enhancements¶
Optimization of recursive dependency analysis functions: Enhance the performance of the recursive functions that analyze backward and forward field dependencies by implementing memoization to cache previously computed results. This enhancement may significantly reduce redundant calculations and improve overall execution time for complex Tableau workbooks.
Centralization of configuration settings: Centralizing configurations such as colors, output file names, and shapes will streamline management and improve consistency across the tool.
Improve the quality and readability of output graphs: Enhance the aesthetics of the output network graphs by refining colors, fonts, and node arrangements in the PNG/SVG images for better visual appeal and clarity.
Prettify the Flask App: Improve the user interface and overall design of the Flask application to enhance user experience and make it visually appealing.
Refactor the main processing routine: The
process_twbfunction in theshared\processing.pyscript is quite large. It could be divided into smaller, distinct parts to improve readability and make the code easier to follow and maintain.