Implement Phase 1: Daily Helper Foundation

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.

backend/app/models/models.py

@@ -1,4 +1,4 @@
-from sqlalchemy import Column, Integer, String, Float, DateTime, ForeignKey, Enum
+from sqlalchemy import Column, Integer, String, Float, DateTime, ForeignKey, Enum, Boolean, Date, JSON, Text
 from sqlalchemy.orm import relationship
 from sqlalchemy.sql import func
 import enum
@@ -70,3 +70,102 @@ class AIAnalysisLog(Base):
     support_levels = Column(String)  # JSON string
     resistance_levels = Column(String)  # JSON string
     created_at = Column(DateTime(timezone=True), server_default=func.now())
+
+
+# Phase 1: Daily Helper Enhancements
+
+class UserProfile(Base):
+    """User profile and preferences for daily helper features"""
+    __tablename__ = "user_profiles"
+
+    id = Column(Integer, primary_key=True, index=True)
+    email = Column(String, unique=True, index=True, nullable=True)
+    username = Column(String, unique=True, index=True, nullable=True)
+    timezone = Column(String, default="UTC")
+    preferred_trading_start = Column(String, default="09:00")  # HH:MM format
+    preferred_trading_end = Column(String, default="17:00")    # HH:MM format
+    risk_tolerance = Column(String, default="moderate")  # conservative, moderate, aggressive
+    trading_style = Column(String, default="day_trader")  # scalper, day_trader, swing_trader
+    daily_target = Column(Float, nullable=True)  # Daily profit target
+    max_loss = Column(Float, nullable=True)      # Maximum loss tolerance
+    notifications_enabled = Column(Boolean, default=True)
+    email_reports = Column(Boolean, default=True)
+    sms_enabled = Column(Boolean, default=False)
+    push_notifications = Column(Boolean, default=True)
+    phone_number = Column(String, nullable=True)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    updated_at = Column(DateTime(timezone=True), onupdate=func.now())
+
+
+class DailyRoutine(Base):
+    """Scheduled daily trading routines"""
+    __tablename__ = "daily_routines"
+
+    id = Column(Integer, primary_key=True, index=True)
+    user_id = Column(String, nullable=True)
+    routine_type = Column(String)  # morning, active_trading, evening
+    scheduled_time = Column(String)  # HH:MM format
+    tasks = Column(JSON, default=[])  # List of task names
+    enabled = Column(Boolean, default=True)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    updated_at = Column(DateTime(timezone=True), onupdate=func.now())
+
+
+class RoutineExecution(Base):
+    """Track routine execution history"""
+    __tablename__ = "routine_executions"
+
+    id = Column(Integer, primary_key=True, index=True)
+    routine_id = Column(Integer, ForeignKey("daily_routines.id"))
+    executed_at = Column(DateTime(timezone=True), server_default=func.now())
+    completion_status = Column(String)  # completed, failed, partial
+    tasks_completed = Column(JSON, default=[])  # List of completed task names
+    execution_notes = Column(Text, nullable=True)
+
+
+class Notification(Base):
+    """System notifications for user"""
+    __tablename__ = "notifications"
+
+    id = Column(Integer, primary_key=True, index=True)
+    user_id = Column(String, nullable=True)
+    notification_type = Column(String)  # price_alert, routine, report, news, reminder
+    title = Column(String)
+    message = Column(Text)
+    priority = Column(String, default="normal")  # low, normal, high, critical
+    delivery_method = Column(String, default="push")  # push, email, sms
+    data = Column(JSON, nullable=True)  # Additional metadata
+    read = Column(Boolean, default=False)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    read_at = Column(DateTime(timezone=True), nullable=True)
+
+
+class DailyChecklist(Base):
+    """Daily checklist items and completion status"""
+    __tablename__ = "daily_checklists"
+
+    id = Column(Integer, primary_key=True, index=True)
+    user_id = Column(String, nullable=True)
+    checklist_date = Column(Date, default=func.current_date())
+    checklist_type = Column(String)  # morning, active_trading, evening, all
+    items = Column(JSON, default=[])  # List of {id, title, completed, completed_at}
+    completion_percentage = Column(Float, default=0.0)
+    notes = Column(Text, nullable=True)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    updated_at = Column(DateTime(timezone=True), onupdate=func.now())
+
+
+class HabitTracker(Base):
+    """Track user habits and streaks"""
+    __tablename__ = "habit_trackers"
+
+    id = Column(Integer, primary_key=True, index=True)
+    user_id = Column(String, nullable=True)
+    habit_name = Column(String)  # journaling, planning, review, trading
+    frequency = Column(String)  # daily, weekly
+    completion_dates = Column(JSON, default=[])  # List of ISO date strings
+    current_streak = Column(Integer, default=0)
+    longest_streak = Column(Integer, default=0)
+    total_completions = Column(Integer, default=0)
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    updated_at = Column(DateTime(timezone=True), onupdate=func.now())