wip
This commit is contained in:
Dobromir Popov
@ -757,4 +757,203 @@ class EnhancedScalpingDashboard:
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html.H6(f"{symbol[:3]}/USDT", className="text-warning"),
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html.P(f"Ticks: {tick_count}", className="text-white"),
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html.P(f"Duration: {duration:.1f}m", className="text-white"),
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html.P
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html.P(f"Candles: {candle_count}", className="text-white")
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], className="mb-3")
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)
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return html.Div(details)
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except Exception as e:
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logger.error(f"Error creating cache details: {e}")
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return html.P(f"Cache Error: {str(e)}", className="text-danger")
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def _create_system_performance(self, avg_duration: float):
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"""Create system performance display"""
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try:
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session_duration = datetime.now() - self.trading_session.start_time
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session_hours = session_duration.total_seconds() / 3600
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win_rate = self.trading_session.get_win_rate()
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performance_info = [
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html.P(f"Callback: {avg_duration:.1f}ms", className="text-white"),
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html.P(f"Session: {session_hours:.1f}h", className="text-white"),
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html.P(f"Win Rate: {win_rate:.1%}", className="text-success" if win_rate > 0.5 else "text-warning"),
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html.P(f"Trades: {self.trading_session.total_trades}", className="text-white")
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]
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return html.Div(performance_info)
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except Exception as e:
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logger.error(f"Error creating system performance: {e}")
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return html.P(f"Performance Error: {str(e)}", className="text-danger")
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def _create_trading_log(self):
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"""Create trading log display"""
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try:
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recent_trades = self.trading_session.trade_history[-5:] # Last 5 trades
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if not recent_trades:
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return html.P("No trades yet...", className="text-muted text-center")
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log_entries = []
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for trade in reversed(recent_trades): # Most recent first
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timestamp = trade['timestamp'].strftime("%H:%M:%S")
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action = trade['action']
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symbol = trade['symbol']
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price = trade['price']
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pnl = trade.get('pnl', 0)
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confidence = trade['confidence']
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color_class = "text-success" if action == 'BUY' else "text-danger" if action == 'SELL' else "text-muted"
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pnl_class = "text-success" if pnl > 0 else "text-danger" if pnl < 0 else "text-muted"
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log_entries.append(
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html.Div([
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html.Span(f"{timestamp} ", className="text-info"),
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html.Span(f"{action} ", className=color_class),
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html.Span(f"{symbol} ", className="text-warning"),
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html.Span(f"${price:.2f} ", className="text-white"),
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html.Span(f"({confidence:.1%}) ", className="text-muted"),
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html.Span(f"P&L: ${pnl:+.2f}", className=pnl_class)
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], className="mb-1")
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)
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return html.Div(log_entries)
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except Exception as e:
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logger.error(f"Error creating trading log: {e}")
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return html.P(f"Log Error: {str(e)}", className="text-danger")
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def _start_real_time_streaming(self):
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"""Start real-time data streaming"""
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try:
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# Subscribe to data provider
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self.data_provider_subscriber_id = self.data_provider.subscribe(
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callback=self._handle_market_tick,
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symbols=['ETHUSDT', 'BTCUSDT']
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)
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# Start streaming
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self.streaming = True
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# Start background thread for orchestrator
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orchestrator_thread = Thread(target=self._run_orchestrator, daemon=True)
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orchestrator_thread.start()
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logger.info("Real-time streaming started")
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logger.info(f"Subscriber ID: {self.data_provider_subscriber_id}")
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except Exception as e:
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logger.error(f"Error starting real-time streaming: {e}")
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def _handle_market_tick(self, tick: MarketTick):
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"""Handle incoming market tick"""
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try:
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with self.data_lock:
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# Update live prices
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symbol_display = f"{tick.symbol[:3]}/{tick.symbol[3:]}"
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self.live_prices[symbol_display] = tick.price
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# Add to tick cache (15-minute window)
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self.tick_cache.add_tick(tick.symbol, tick)
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# Process tick for 1s candle aggregation
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self.candle_aggregator.process_tick(tick.symbol, tick)
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except Exception as e:
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logger.error(f"Error handling market tick: {e}")
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def _run_orchestrator(self):
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"""Run trading orchestrator in background"""
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try:
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while self.streaming:
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try:
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# Get recent ticks for model training
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eth_ticks = self.tick_cache.get_recent_ticks('ETHUSDT', minutes=15)
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btc_ticks = self.tick_cache.get_recent_ticks('BTCUSDT', minutes=15)
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if eth_ticks:
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# Make trading decision
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decision = self.orchestrator.make_trading_decision(
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symbol='ETH/USDT',
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current_price=eth_ticks[-1].price,
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market_data={'recent_ticks': eth_ticks}
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)
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if decision and decision.action != 'HOLD':
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# Execute trade
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trade_result = self.trading_session.execute_trade(
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decision, eth_ticks[-1].price
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)
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if trade_result:
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self.recent_decisions.append(decision)
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if len(self.recent_decisions) > 50:
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self.recent_decisions.pop(0)
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logger.info(f"TRADE EXECUTED: {decision.action} {decision.symbol} "
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f"@ ${eth_ticks[-1].price:.2f} | "
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f"Confidence: {decision.confidence:.1%}")
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time.sleep(1) # Check every second
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except Exception as e:
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logger.error(f"Error in orchestrator loop: {e}")
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time.sleep(5) # Wait longer on error
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except Exception as e:
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logger.error(f"Error in orchestrator thread: {e}")
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def run(self, host: str = '127.0.0.1', port: int = 8051, debug: bool = False):
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"""Run the enhanced dashboard"""
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try:
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logger.info(f"Starting Enhanced Scalping Dashboard at http://{host}:{port}")
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logger.info("Features: 1s OHLCV bars, 15min tick cache, enhanced volume display")
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self.app.run_server(
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host=host,
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port=port,
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debug=debug,
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use_reloader=False # Prevent issues with threading
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)
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except Exception as e:
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logger.error(f"Error running dashboard: {e}")
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raise
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finally:
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self.streaming = False
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if self.data_provider_subscriber_id:
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self.data_provider.unsubscribe(self.data_provider_subscriber_id)
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def main():
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"""Main function to run enhanced dashboard"""
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import logging
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# Setup logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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try:
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# Initialize components
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data_provider = DataProvider()
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orchestrator = EnhancedTradingOrchestrator(data_provider)
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# Create and run dashboard
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dashboard = EnhancedScalpingDashboard(
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data_provider=data_provider,
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orchestrator=orchestrator
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)
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dashboard.run(host='127.0.0.1', port=8051, debug=False)
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except KeyboardInterrupt:
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logger.info("Dashboard stopped by user")
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except Exception as e:
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logger.error(f"Error running enhanced dashboard: {e}")
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raise
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if __name__ == "__main__":
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main()
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