Replaces count annotation with custom aggregation logic to
correctly count status entries per date in heatmap data.
Improves data processing by calculating occurrences manually.
Removes previous annotation and modifies output format.
This ensures data accuracy before encoding into JSON response.
Removed unnecessary imports across various modules to streamline the application's dependencies and improve loading times. Specific changes include the removal of unused Django model and admin imports in several apps, simplifying view imports by eliminating unutilized components, and cleaning up static CSS for better maintainability. Corrections were made to conditional expressions for clearer logic. The removal of the django.test.TestCase import in test files reflects a shift towards a different testing strategy or the current lack of tests. Exception handling has been made more explicit to avoid catching unintended exceptions, paving the way for more robust error handling and logging in the future. Additionally, a new CSS file was added for frontend enhancements, indicating ongoing UI/UX improvements.
These changes collectively aim to make the codebase more maintainable and efficient, reducing clutter and focusing on used functionalities. It's a step towards optimizing the application's performance and ensuring a clean, manageable codebase for future development.
Reinforced user data access rules to bolster security and reorganized distribution files into separate directories for cleaner structure. Added a new heatmap visualization for mood statistics on the dashboard, making user engagements more interactive and insightful. Implemented a JSON view to support the heatmap feature, fetching mood entries within a specified time range.
This change responds to the need for improved data security and a more engaging user interface, directly addressing user feedback for clearer insights into their mood patterns over time.
