Complete implementation of Phase 1 enhancements including:
Backend:
- UserProfile model for storing user preferences (timezone, trading style, risk tolerance)
- DailyRoutine model for scheduling routines (morning, active_trading, evening)
- RoutineExecution model for tracking routine execution history
- Notification model for managing all types of notifications
- DailyChecklist model for daily task tracking with completion percentage
- HabitTracker model for tracking habits and streaks
Services:
- RoutineService: Handles routine execution with task registry pattern
- RoutineScheduler: Async scheduler for automated routine execution
- NotificationService: Comprehensive notification creation and delivery system
- Support for price alerts, news, routines, reminders, and performance notifications
API Endpoints (daily_helper router):
- User profile: CRUD operations, get/update preferences
- Daily routines: Create, list, execute, track history
- Notifications: CRUD, mark read, batch operations
- Daily checklists: CRUD, item management, completion tracking
- Habits: Create, track, log completions, manage streaks
- Dashboard: Summary endpoint for daily helper overview
Frontend Components:
- UserProfileSetup: Complete user profile configuration with preferences
- NotificationCenter: Bell icon with dropdown, notification management
- HabitTracker: Habit creation, streak tracking, gamification with fire emojis
- DailyChecklistPanel: Checklist management with completion percentage
Schemas:
- Full Pydantic schemas for request/response validation
- Type-safe API contracts
Features:
- Timezone support for international users
- Trading style and risk tolerance preferences
- Automated routine execution with task registry
- Real-time notifications with priority levels
- Habit streaks with motivational badges
- Daily checklist with persistent state
- Completion percentage tracking
- Notes and metadata support
All components are production-ready with error handling and user feedback.
Claude
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