Introduces a new view class to manage Telegram webhook POST requests.
Lays the groundwork for processing incoming messages with a basic
placeholder returning HTTP 200 status. Future logic implementation
is pending.
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.
This commit introduces the initial set of database migrations required for setting up the foundational models of the messaging system within the application. These models include `GatewayUser`, `GatewayUserSetting`, `Notification`, and various scheduling entities to manage notification delivery timings. It lays the groundwork for linking users to their gateway preferences, storing customizable settings per gateway-user pair, and managing notifications with flexible scheduling options. This schema setup is crucial for supporting a dynamic and configurable messaging system, enabling efficient notification management and dispatching based on user preferences and predefined schedules.
By establishing a robust database schema upfront, we ensure that the application can scale effectively, facilitating ease of maintenance and future enhancements. This migration caters to the need for a cohesive and flexible data model to represent users, their notification preferences, and the logistics of notification dispatching and scheduling within the system.
