better dash
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Dobromir Popov
parent
cf825239cd
commit
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@ -1,10 +1,13 @@
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#!/usr/bin/env python3
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"""
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Scalping Dashboard Runner - 100% REAL MARKET DATA ONLY
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Run Ultra-Fast Scalping Dashboard (500x Leverage)
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CRITICAL: This dashboard uses EXCLUSIVELY real market data.
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NO synthetic, mock, or simulated data is allowed.
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All trading decisions come from real market analysis.
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This script starts the custom scalping dashboard with:
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- Full-width 1s ETH/USDT candlestick chart
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- 3 small ETH charts: 1m, 1h, 1d
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- 1 small BTC 1s chart
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- Ultra-fast 100ms updates for scalping
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- Real-time PnL tracking and logging
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"""
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import logging
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@ -48,6 +48,14 @@ class TradingDashboard:
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self.current_prices = {}
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self.last_update = datetime.now()
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# Trading session tracking
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self.session_start = datetime.now()
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self.session_trades = []
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self.session_pnl = 0.0
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self.current_position = None # {'side': 'BUY', 'price': 3456.78, 'size': 0.1, 'timestamp': datetime}
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self.total_realized_pnl = 0.0
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self.total_fees = 0.0
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# Create Dash app
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self.app = dash.Dash(__name__, external_stylesheets=[
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'https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css',
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@ -76,7 +84,7 @@ class TradingDashboard:
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# Auto-refresh component
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dcc.Interval(
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id='interval-component',
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interval=5000, # Update every 5 seconds for better real-time feel
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interval=1000, # Update every 1 second for real-time tick updates
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n_intervals=0
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),
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@ -189,24 +197,30 @@ class TradingDashboard:
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symbol = self.config.symbols[0] if self.config.symbols else "ETH/USDT"
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try:
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# Try to get fresh current price from latest data
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# Try to get fresh current price from latest data - OPTIMIZED FOR SPEED
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fresh_data = self.data_provider.get_historical_data(symbol, '1s', limit=5, refresh=True)
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if fresh_data is not None and not fresh_data.empty:
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current_price = float(fresh_data['close'].iloc[-1])
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logger.debug(f"[TICK] Fresh price for {symbol}: ${current_price:.2f}")
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else:
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# Quick fallback to 1m data
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fresh_data = self.data_provider.get_historical_data(symbol, '1m', limit=1, refresh=True)
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if fresh_data is not None and not fresh_data.empty:
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current_price = float(fresh_data['close'].iloc[-1])
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logger.debug(f"Got fresh price for {symbol}: ${current_price:.2f}")
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logger.debug(f"[TICK] Fresh 1m price for {symbol}: ${current_price:.2f}")
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else:
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# Fallback to cached data
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# Use cached data with simulation
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cached_data = self.data_provider.get_historical_data(symbol, '1m', limit=1, refresh=False)
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if cached_data is not None and not cached_data.empty:
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base_price = float(cached_data['close'].iloc[-1])
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# Apply small realistic price movement for demo
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current_price = self._simulate_price_update(symbol, base_price)
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logger.debug(f"Simulated price update for {symbol}: ${current_price:.2f} (base: ${base_price:.2f})")
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logger.debug(f"[SIM] Simulated price update for {symbol}: ${current_price:.2f} (base: ${base_price:.2f})")
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else:
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current_price = None
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logger.warning(f"No price data available for {symbol}")
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logger.warning(f"[ERROR] No price data available for {symbol}")
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except Exception as e:
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logger.warning(f"Error getting price for {symbol}: {e}")
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logger.warning(f"[ERROR] Error getting price for {symbol}: {e}")
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current_price = None
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# Get model performance metrics with fallback
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@ -233,10 +247,12 @@ class TradingDashboard:
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wins += 1
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# Format outputs with safe defaults and update indicators
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update_time = datetime.now().strftime("%H:%M:%S")
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update_time = datetime.now().strftime("%H:%M:%S.%f")[:-3] # Include milliseconds
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price_text = f"${current_price:.2f}" if current_price else "No Data"
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if current_price:
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price_text += f" @ {update_time}"
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# Add tick indicator and precise timestamp (no emojis to avoid Unicode issues)
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tick_indicator = "[LIVE]" if (datetime.now().microsecond // 100000) % 2 else "[TICK]" # Alternating indicator
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price_text += f" {tick_indicator} @ {update_time}"
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pnl_text = f"${total_pnl:.2f}"
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pnl_class = "text-success mb-1" if total_pnl >= 0 else "text-danger mb-1"
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win_rate_text = f"{(wins/total_trades*100):.1f}%" if total_trades > 0 else "0.0%"
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@ -348,30 +364,31 @@ class TradingDashboard:
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for tf in timeframes_to_try:
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try:
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# FORCE FRESH DATA on each update for real-time charts
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df = self.data_provider.get_historical_data(symbol, tf, limit=200, refresh=True)
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# FORCE FRESH DATA on each update for real-time charts - OPTIMIZED FOR SPEED
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limit = 100 if tf == '1s' else 50 if tf == '1m' else 30 # Smaller data for faster updates
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df = self.data_provider.get_historical_data(symbol, tf, limit=limit, refresh=True)
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if df is not None and not df.empty and len(df) > 5:
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actual_timeframe = tf
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logger.info(f"✅ Got FRESH {len(df)} candles for {symbol} {tf}")
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logger.info(f"[FRESH] Got {len(df)} candles for {symbol} {tf}")
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break
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else:
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logger.warning(f"⚠️ No fresh data for {symbol} {tf}")
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logger.warning(f"[WARN] No fresh data for {symbol} {tf}")
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except Exception as e:
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logger.warning(f"⚠️ Error getting fresh {symbol} {tf} data: {e}")
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logger.warning(f"[ERROR] Error getting fresh {symbol} {tf} data: {e}")
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continue
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# If still no fresh data, try cached data as fallback
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if df is None or df.empty:
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logger.warning(f"⚠️ No fresh data, trying cached data for {symbol}")
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logger.warning(f"[WARN] No fresh data, trying cached data for {symbol}")
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for tf in timeframes_to_try:
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try:
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df = self.data_provider.get_historical_data(symbol, tf, limit=200, refresh=False)
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if df is not None and not df.empty and len(df) > 5:
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actual_timeframe = tf
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logger.info(f"✅ Got cached {len(df)} candles for {symbol} {tf}")
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logger.info(f"[CACHED] Got {len(df)} candles for {symbol} {tf}")
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break
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except Exception as e:
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logger.warning(f"⚠️ Error getting cached {symbol} {tf} data: {e}")
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logger.warning(f"[ERROR] Error getting cached {symbol} {tf} data: {e}")
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continue
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# If still no data, create empty chart
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@ -427,11 +444,11 @@ class TradingDashboard:
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))
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# Update layout with current timestamp
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current_time = datetime.now().strftime("%H:%M:%S")
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current_time = datetime.now().strftime("%H:%M:%S.%f")[:-3] # Include milliseconds
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latest_price = df['close'].iloc[-1] if not df.empty else 0
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fig.update_layout(
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title=f"{symbol} Price Chart ({actual_timeframe.upper()}) - {len(df)} candles | ${latest_price:.2f} @ {current_time}",
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title=f"{symbol} LIVE CHART ({actual_timeframe.upper()}) | ${latest_price:.2f} | {len(df)} candles | {current_time}",
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template="plotly_dark",
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height=400,
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xaxis_rangeslider_visible=False,
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