Implemented comprehensive economic calendar system for trading event alerts:
Backend (economic_calendar.py):
- GET /api/economic-calendar/events: Fetch events by days, countries, impact level
- GET /api/economic-calendar/today: Get today's scheduled events
- GET /api/economic-calendar/upcoming: Events within X hours (1-168)
- GET /api/economic-calendar/high-impact: Only critical events (next 30 days)
- GET /api/economic-calendar/by-country/{country}: Country-specific events
- GET /api/economic-calendar/impact-analysis: Gold trading impact analysis
- GET /api/economic-calendar/calendar-view: Calendar view with events by day
- POST /api/economic-calendar/events/{event_id}/notify: Set reminder notifications
- GET /api/economic-calendar/stats: Event statistics and busiest days
Features:
- Sample economic events: NFP, CPI, Unemployment, Fed Rate Decision, ECB Rate
- Impact levels: High/Medium/Low with color coding
- Forecast, previous, and actual values tracking
- Event filtering by country, impact, and days ahead
- Multiple sort options: date, importance, impact
- Notifications 15-120 minutes before events
- Gold trading correlation analysis
- Statistics for 7-day and 30-day windows
Frontend (EconomicCalendar.tsx):
- Calendar overview with event statistics
- Upcoming and high-impact event tabs
- Country-based filtering
- Impact-based color coding (red/yellow/blue)
- Event details: forecast, previous, actual values
- Trading tips for different event types
- Event time display with timezone consideration
- Correlation guidance (USD inverse, rates inverse)
- Visual indicators for pending/actual events
Integration:
- Registered economic_calendar router in main.py
- Added EconomicCalendar tab to App.tsx
- Integrated with navigation system
- Full TypeScript support
Note: Currently uses mock data. In production, integrate with:
- Trading Economics API
- Forexfactory Calendar
- Economic Calendar Pro
- OANDA Calendar
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.
This document outlines a 6-phase strategy to transform the Gold Trading
Simulator from an excellent trading platform into an efficient daily helper.
Includes detailed specifications for automation, notifications, data
persistence, mobile support, AI enhancements, and reporting.
- Phase 1: User profiles, routine automation, notifications, habit tracking
- Phase 2: Smart notification scheduling, email reports, SMS alerts
- Phase 3: Extended performance tracking, pattern recognition, lessons database
- Phase 4: Economic calendar integration, PWA support, widget system
- Phase 5: AI pattern recognition, predictive analytics, AI coach
- Phase 6: Advanced reporting, PDF/Excel exports, analytics dashboards
Estimated total effort: 12-15 weeks with recommended phased implementation.
Quick wins available in 1-2 weeks for immediate value.
Claude