gogo2/ENHANCED_SCALPING_DASHBOARD_1S_BARS_SUMMARY.md

Enhanced Scalping Dashboard with 1s Bars and 15min Cache - Implementation Summary

Overview

Successfully implemented an enhanced real-time scalping dashboard with the following key improvements:

🎯 Core Features Implemented

1. 1-Second OHLCV Bar Charts (instead of tick points)

   • Real-time candle aggregation from tick data
   • Proper OHLCV calculation with volume tracking
   • Buy/sell volume separation for enhanced analysis

2. 15-Minute Server-Side Tick Cache

   • Rolling 15-minute window of raw tick data
   • Optimized for model training data access
   • Thread-safe implementation with deque structures

3. Enhanced Volume Visualization

   • Separate buy/sell volume bars
   • Volume comparison charts between symbols
   • Real-time volume analysis subplot

4. Ultra-Low Latency WebSocket Streaming

   • Direct tick processing pipeline
   • Minimal latency between market data and display
   • Efficient data structures for real-time updates

📁 Files Created/Modified

New Files:

• web/enhanced_scalping_dashboard.py - Main enhanced dashboard implementation
• run_enhanced_scalping_dashboard.py - Launcher script with configuration options

Key Components:

1. TickCache Class

class TickCache:
    """15-minute tick cache for model training"""
    - cache_duration_minutes: 15 (configurable)
    - max_cache_size: 50,000 ticks per symbol
    - Thread-safe with Lock()
    - Automatic cleanup of old ticks

2. CandleAggregator Class

class CandleAggregator:
    """Real-time 1-second candle aggregation from tick data"""
    - Aggregates ticks into 1-second OHLCV bars
    - Tracks buy/sell volume separately
    - Maintains rolling window of 300 candles (5 minutes)
    - Thread-safe implementation

3. TradingSession Class

class TradingSession:
    """Session-based trading with $100 starting balance"""
    - $100 starting balance per session
    - Real-time P&L tracking
    - Win rate calculation
    - Trade history logging

4. EnhancedScalpingDashboard Class

class EnhancedScalpingDashboard:
    """Enhanced real-time scalping dashboard with 1s bars and 15min cache"""
    - 1-second update frequency
    - Multi-chart layout with volume analysis
    - Real-time performance monitoring
    - Background orchestrator integration

🎨 Dashboard Layout

Header Section:

• Session ID and metrics
• Current balance and P&L
• Live ETH/USDT and BTC/USDT prices
• Cache status (total ticks)

Main Chart (700px height):

• ETH/USDT 1-second OHLCV candlestick chart
• Volume subplot with buy/sell separation
• Trading signal overlays
• Real-time price and candle count display

Secondary Charts:

• BTC/USDT 1-second bars (350px)
• Volume analysis comparison chart (350px)

Status Panels:

• 15-minute tick cache details
• System performance metrics
• Live trading actions log

🔧 Technical Implementation

Data Flow:

1. Market Ticks → DataProvider WebSocket
2. Tick Processing → TickCache (15min) + CandleAggregator (1s)
3. Dashboard Updates → 1-second callback frequency
4. Trading Decisions → Background orchestrator thread
5. Chart Rendering → Plotly with dark theme

Performance Optimizations:

• Thread-safe data structures
• Efficient deque collections
• Minimal callback duration (<50ms target)
• Background processing for heavy operations

Volume Analysis:

• Buy volume: Green bars (#00ff88)
• Sell volume: Red bars (#ff6b6b)
• Volume comparison between ETH and BTC
• Real-time volume trend analysis

🚀 Launch Instructions

Basic Launch:

python run_enhanced_scalping_dashboard.py

Advanced Options:

python run_enhanced_scalping_dashboard.py --host 0.0.0.0 --port 8051 --debug --log-level DEBUG

Access Dashboard:

• URL: http://127.0.0.1:8051
• Features: 1s bars, 15min cache, enhanced volume display
• Update frequency: 1 second

📊 Key Metrics Displayed

Session Metrics:

• Current balance (starts at $100)
• Session P&L (real-time)
• Win rate percentage
• Total trades executed

Cache Statistics:

• Tick count per symbol
• Cache duration in minutes
• Candle count (1s aggregated)
• Ticks per minute rate

System Performance:

• Callback duration (ms)
• Session duration (hours)
• Real-time performance monitoring

🎯 Benefits Over Previous Implementation

1. Better Market Visualization:

   • 1s OHLCV bars provide clearer price action
   • Volume analysis shows market sentiment
   • Proper candlestick charts instead of scatter plots

2. Enhanced Model Training:

   • 15-minute tick cache provides rich training data
   • Real-time data pipeline for continuous learning
   • Optimized data structures for fast access

3. Improved Performance:

   • Lower latency data processing
   • Efficient memory usage with rolling windows
   • Thread-safe concurrent operations

4. Professional Dashboard:

   • Clean, dark theme interface
   • Multiple chart views
   • Real-time status monitoring
   • Trading session tracking

🔄 Integration with Existing System

The enhanced dashboard integrates seamlessly with:

• core.data_provider.DataProvider for market data
• core.enhanced_orchestrator.EnhancedTradingOrchestrator for trading decisions
• Existing logging and configuration systems
• Model training pipeline (via 15min tick cache)

📈 Next Steps

1. Model Integration: Use 15min tick cache for real-time model training
2. Advanced Analytics: Add technical indicators to 1s bars
3. Multi-Timeframe: Support for multiple timeframe views
4. Alert System: Price/volume-based notifications
5. Export Features: Data export for analysis

🎉 Success Criteria Met

✅ 1-second bar charts implemented ✅ 15-minute tick cache operational ✅ Enhanced volume visualization ✅ Ultra-low latency streaming ✅ Real-time candle aggregation ✅ Professional dashboard interface ✅ Session-based trading tracking ✅ System performance monitoring

The enhanced scalping dashboard is now ready for production use with significantly improved market data visualization and model training capabilities.