- Deleted `app_new.py`, which was previously the main entry point for the dashboard application, to streamline the codebase.
- Consolidated the application initialization and callback registration logic into `main.py`, enhancing modularity and maintainability.
- Updated the logging and error handling practices in `main.py` to ensure consistent application behavior and improved debugging capabilities.
These changes simplify the application structure, aligning with project standards for modularity and maintainability.
- Introduced a comprehensive data collection framework, including `CollectorServiceConfig`, `BaseDataCollector`, and `CollectorManager`, enhancing modularity and maintainability.
- Developed `CollectorFactory` for streamlined collector creation, promoting separation of concerns and improved configuration handling.
- Enhanced `DataCollectionService` to utilize the new architecture, ensuring robust error handling and logging practices.
- Added `TaskManager` for efficient management of asynchronous tasks, improving performance and resource management.
- Implemented health monitoring and auto-recovery features in `CollectorManager`, ensuring reliable operation of data collectors.
- Updated imports across the codebase to reflect the new structure, ensuring consistent access to components.
These changes significantly improve the architecture and maintainability of the data collection service, aligning with project standards for modularity, performance, and error handling.
- Extracted callback management logic into a new `CallbackDispatcher` class, promoting separation of concerns and enhancing modularity.
- Updated `BaseDataCollector` to utilize the `CallbackDispatcher` for adding, removing, and notifying data callbacks, improving code clarity and maintainability.
- Refactored related methods to ensure consistent error handling and logging practices.
- Added unit tests for the `CallbackDispatcher` to validate its functionality and ensure robust error handling.
These changes streamline the callback management architecture, aligning with project standards for maintainability and performance.
- Extracted connection management logic into a new `ConnectionManager` class, promoting separation of concerns and enhancing modularity.
- Updated `BaseDataCollector` to utilize the `ConnectionManager` for connection, disconnection, and reconnection processes, improving code clarity and maintainability.
- Refactored connection-related methods and attributes, ensuring consistent error handling and logging practices.
- Enhanced the `OKXCollector` to implement the new connection management approach, streamlining its connection logic.
- Added unit tests for the `ConnectionManager` to validate its functionality and ensure robust error handling.
These changes improve the architecture of the data collector, aligning with project standards for maintainability and performance.
- Introduced a new `CollectorStateAndTelemetry` class to encapsulate the status, health checks, and statistics of the data collector, promoting modularity and separation of concerns.
- Updated `BaseDataCollector` to replace direct status management with calls to the new telemetry class, enhancing maintainability and readability.
- Refactored logging methods to utilize the telemetry class, ensuring consistent logging practices.
- Modified the `OKXCollector` to integrate with the new telemetry system for improved status reporting and error handling.
- Added comprehensive tests for the `CollectorStateAndTelemetry` class to ensure functionality and reliability.
These changes streamline the data collector's architecture, aligning with project standards for maintainability and performance.
