JamesTang
f30bcdc680
- Promoted prototype dashboard to main app - Added /api/market-data endpoint - Implemented market_simulator.py for realistic OHLCV generation - Updated MoomooClient to serve simulated scenarios - Wired frontend to backend API
100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
#!/usr/bin/env python3
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"""
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Simple dashboard server for Quantitative Trading Platform.
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Provides mock metrics for PnL, drawdown, and win rate.
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"""
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from flask import Flask, render_template, jsonify, request
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import random
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from datetime import datetime, timedelta
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from data.connectors import create_moomoo_client, Interval
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app = Flask(__name__)
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# Initialize MoomooClient in mock mode (using our LLM scenario generator)
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client = create_moomoo_client(mock_mode=True)
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@app.route('/')
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def dashboard():
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"""Serve the dashboard HTML page."""
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return render_template('index.html')
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@app.route('/api/market-data/<symbol>')
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def market_data(symbol):
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"""
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API endpoint returning market data for a symbol.
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Fetches 30 days of daily data by default for the dashboard.
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"""
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try:
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# Fetch OHLCV data from our connector (which uses the simulator)
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end_date = datetime.now()
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start_date = end_date - timedelta(days=30)
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# Determine interval from query param, default to 1d
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interval_str = request.args.get('interval', '1d')
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interval = Interval(interval_str)
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ohlcv_data = client.get_ohlcv(
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symbol=symbol.upper(),
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interval=interval,
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start_date=start_date,
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end_date=end_date,
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limit=100
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)
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# Transform for frontend
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daily_pnl = []
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cumulative = 0
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# Simple simulation of PnL based on close price changes
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# In a real app, this would come from the Strategy/Portfolio engine
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initial_balance = 10000.0
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position_size = 10 # shares
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prev_close = ohlcv_data[0].close if ohlcv_data else 0
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for point in ohlcv_data:
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change = point.close - prev_close
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pnl = change * position_size
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cumulative += pnl
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daily_pnl.append({
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'date': point.timestamp.strftime('%Y-%m-%d'),
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'pnl': round(pnl, 2),
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'cumulative': round(cumulative, 2),
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'close': point.close
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})
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prev_close = point.close
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# Calculate summary metrics
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total_pnl = cumulative
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peak = max([d['cumulative'] for d in daily_pnl]) if daily_pnl else 0
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trough = min([d['cumulative'] for d in daily_pnl]) if daily_pnl else 0
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max_drawdown = min(0, trough - peak)
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profitable_days = sum(1 for d in daily_pnl if d['pnl'] > 0)
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win_rate = (profitable_days / len(daily_pnl) * 100) if daily_pnl else 0
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return jsonify({
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'symbol': symbol.upper(),
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'metrics': {
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'total_pnl': round(total_pnl, 2),
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'max_drawdown': round(max_drawdown, 2),
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'win_rate': round(win_rate, 1),
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'portfolio_value': round(initial_balance + total_pnl, 2),
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'peak': round(peak, 2),
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'trough': round(trough, 2)
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},
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'daily_pnl': daily_pnl
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})
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except Exception as e:
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return jsonify({'error': str(e)}), 500
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@app.route('/health')
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def health():
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"""Health check endpoint."""
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return jsonify({'status': 'healthy', 'timestamp': datetime.now().isoformat()})
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=5000, debug=True) |