wip-dash-broken
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@ -1,26 +1,31 @@
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"""
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Ultra-Fast Scalping Dashboard (500x Leverage) - Real Market Data
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Ultra-Fast Real-Time Scalping Dashboard (500x Leverage) - Live Data Streaming
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Dashboard using ONLY real market data from APIs with:
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- Main 1s ETH/USDT chart (full width)
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Real-time WebSocket streaming dashboard with:
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- Main 1s ETH/USDT chart (full width) with live updates
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- 4 small charts: 1m ETH, 1h ETH, 1d ETH, 1s BTC
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- 500 candles preloaded at startup
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- Real-time updates from data provider
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- WebSocket price streaming for instant updates
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- Europe/Sofia timezone support
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- Ultra-low latency UI updates (100ms)
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- NO CACHED DATA - 100% live streaming
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"""
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import asyncio
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import json
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import logging
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import time
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import websockets
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import pytz
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from datetime import datetime, timedelta
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from threading import Thread
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from threading import Thread, Lock
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from typing import Dict, List, Optional, Any
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import pandas as pd
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import numpy as np
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import requests
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import dash
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from dash import dcc, html, Input, Output
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import plotly.graph_objects as go
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import pandas as pd
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import numpy as np
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from core.config import get_config
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from core.data_provider import DataProvider
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@ -28,185 +33,156 @@ from core.enhanced_orchestrator import EnhancedTradingOrchestrator, TradingActio
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logger = logging.getLogger(__name__)
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class ScalpingDashboard:
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"""Real market data scalping dashboard for 500x leverage trading"""
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class RealTimeScalpingDashboard:
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"""Real-time scalping dashboard with WebSocket streaming and ultra-low latency"""
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def __init__(self, data_provider: DataProvider = None, orchestrator: EnhancedTradingOrchestrator = None):
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"""Initialize the dashboard with real market data"""
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"""Initialize the real-time dashboard with WebSocket streaming"""
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self.config = get_config()
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self.data_provider = data_provider or DataProvider()
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self.orchestrator = orchestrator or EnhancedTradingOrchestrator(self.data_provider)
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# Timezone setup
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self.timezone = pytz.timezone('Europe/Sofia')
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# Dashboard state
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self.recent_decisions = []
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self.scalping_metrics = {
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'total_trades': 0,
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'win_rate': 0.78,
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'total_pnl': 0.0, # Will be updated by runner
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'avg_trade_time': 3.2, # seconds
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'total_pnl': 0.0,
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'avg_trade_time': 3.2,
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'leverage': '500x',
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'last_action': None
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}
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# Real market data cache - preload 500 candles for each chart
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self.market_data = {
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# Real-time price streaming data
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self.live_prices = {
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'ETH/USDT': 0.0,
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'BTC/USDT': 0.0
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}
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# Real-time chart data (no caching - always fresh)
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self.chart_data = {
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'ETH/USDT': {
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'1s': None, # Main chart
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'1m': None, # Small chart
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'1h': None, # Small chart
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'1d': None # Small chart
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'1s': pd.DataFrame(),
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'1m': pd.DataFrame(),
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'1h': pd.DataFrame(),
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'1d': pd.DataFrame()
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},
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'BTC/USDT': {
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'1s': None # Small chart
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'1s': pd.DataFrame()
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}
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}
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# Initialize real market data
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self._preload_market_data()
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# WebSocket streaming control
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self.streaming = False
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self.websocket_threads = []
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self.data_lock = Lock()
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# Create Dash app
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self.app = dash.Dash(__name__)
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# Create Dash app with real-time updates
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self.app = dash.Dash(__name__,
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external_stylesheets=['https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css'])
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# Setup layout and callbacks
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self._setup_layout()
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self._setup_callbacks()
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self._start_real_time_streaming()
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logger.info("Ultra-Fast Scalping Dashboard initialized with REAL MARKET DATA")
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def _preload_market_data(self):
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"""Preload 500 candles for each chart from real market APIs"""
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logger.info("🔄 Preloading 500 candles of real market data...")
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try:
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# Load ETH/USDT data for main chart and small charts
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self.market_data['ETH/USDT']['1s'] = self.data_provider.get_historical_data(
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'ETH/USDT', '1s', limit=500
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)
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self.market_data['ETH/USDT']['1m'] = self.data_provider.get_historical_data(
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'ETH/USDT', '1m', limit=500
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)
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self.market_data['ETH/USDT']['1h'] = self.data_provider.get_historical_data(
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'ETH/USDT', '1h', limit=500
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)
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self.market_data['ETH/USDT']['1d'] = self.data_provider.get_historical_data(
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'ETH/USDT', '1d', limit=500
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)
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# Load BTC/USDT 1s data for small chart
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self.market_data['BTC/USDT']['1s'] = self.data_provider.get_historical_data(
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'BTC/USDT', '1s', limit=500
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)
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# Log successful data loading
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for symbol in self.market_data:
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for timeframe, data in self.market_data[symbol].items():
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if data is not None and not data.empty:
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logger.info(f"✅ Loaded {len(data)} candles for {symbol} {timeframe}")
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logger.info(f" Price range: ${data['close'].min():.2f} - ${data['close'].max():.2f}")
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else:
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logger.warning(f"⚠️ No data loaded for {symbol} {timeframe}")
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logger.info("✅ Market data preload complete - ready for real-time updates")
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except Exception as e:
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logger.error(f"❌ Error preloading market data: {e}")
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# Initialize empty DataFrames as fallback
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for symbol in self.market_data:
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for timeframe in self.market_data[symbol]:
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self.market_data[symbol][timeframe] = pd.DataFrame()
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logger.info("🚀 Real-Time Scalping Dashboard initialized with LIVE STREAMING")
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logger.info("📡 WebSocket price streaming enabled")
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logger.info(f"🌍 Timezone: {self.timezone}")
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def _setup_layout(self):
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"""Setup the 5-chart dashboard layout"""
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"""Setup the ultra-fast real-time dashboard layout"""
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self.app.layout = html.Div([
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# Header with real-time metrics
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# Header with live metrics
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html.Div([
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html.H1("ULTRA-FAST SCALPING DASHBOARD - 500x LEVERAGE - REAL MARKET DATA",
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className="text-center mb-4"),
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html.H1("🚀 REAL-TIME SCALPING DASHBOARD - 500x LEVERAGE - LIVE STREAMING",
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className="text-center mb-4 text-white"),
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html.P(f"🌍 Sofia Time Zone | 📡 Live WebSocket Streaming | ⚡ 100ms Updates",
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className="text-center text-info"),
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# Real-time metrics row
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# Live metrics row
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html.Div([
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html.Div([
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html.H3(id="live-pnl", className="text-success"),
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html.P("Total P&L")
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html.P("Total P&L", className="text-white")
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], className="col-md-2 text-center"),
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html.Div([
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html.H3(id="win-rate", className="text-info"),
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html.P("Win Rate")
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html.P("Win Rate", className="text-white")
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], className="col-md-2 text-center"),
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html.Div([
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html.H3(id="total-trades", className="text-primary"),
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html.P("Total Trades")
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html.P("Total Trades", className="text-white")
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], className="col-md-2 text-center"),
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html.Div([
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html.H3(id="last-action", className="text-warning"),
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html.P("Last Action")
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html.P("Last Action", className="text-white")
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], className="col-md-2 text-center"),
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html.Div([
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html.H3(id="eth-price", className="text-white"),
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html.P("ETH/USDT Live")
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html.H3(id="eth-price", className="text-success"),
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html.P("ETH/USDT LIVE", className="text-white")
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], className="col-md-2 text-center"),
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html.Div([
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html.H3(id="btc-price", className="text-white"),
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html.P("BTC/USDT Live")
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html.H3(id="btc-price", className="text-success"),
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html.P("BTC/USDT LIVE", className="text-white")
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], className="col-md-2 text-center")
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], className="row mb-4")
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], className="bg-dark p-3 mb-3"),
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# Main 1s ETH/USDT chart (full width)
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# Main 1s ETH/USDT chart (full width) - REAL-TIME
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html.Div([
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html.H4("ETH/USDT 1s Real-Time Chart (Main Trading Signal)",
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html.H4("📈 ETH/USDT 1s Real-Time Chart (Live WebSocket Feed)",
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className="text-center mb-3"),
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dcc.Graph(id="main-eth-1s-chart", style={"height": "500px"})
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dcc.Graph(id="main-eth-1s-chart", style={"height": "600px"})
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], className="mb-4"),
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# Row of 4 small charts
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# Row of 4 small charts - ALL REAL-TIME
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html.Div([
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# ETH/USDT 1m
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html.Div([
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html.H6("ETH/USDT 1m", className="text-center"),
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dcc.Graph(id="eth-1m-chart", style={"height": "250px"})
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html.H6("ETH/USDT 1m LIVE", className="text-center"),
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dcc.Graph(id="eth-1m-chart", style={"height": "300px"})
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], className="col-md-3"),
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# ETH/USDT 1h
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html.Div([
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html.H6("ETH/USDT 1h", className="text-center"),
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dcc.Graph(id="eth-1h-chart", style={"height": "250px"})
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html.H6("ETH/USDT 1h LIVE", className="text-center"),
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dcc.Graph(id="eth-1h-chart", style={"height": "300px"})
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], className="col-md-3"),
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# ETH/USDT 1d
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html.Div([
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html.H6("ETH/USDT 1d", className="text-center"),
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dcc.Graph(id="eth-1d-chart", style={"height": "250px"})
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html.H6("ETH/USDT 1d LIVE", className="text-center"),
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dcc.Graph(id="eth-1d-chart", style={"height": "300px"})
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], className="col-md-3"),
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# BTC/USDT 1s
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html.Div([
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html.H6("BTC/USDT 1s", className="text-center"),
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dcc.Graph(id="btc-1s-chart", style={"height": "250px"})
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html.H6("BTC/USDT 1s LIVE", className="text-center"),
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dcc.Graph(id="btc-1s-chart", style={"height": "300px"})
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], className="col-md-3")
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], className="row mb-4"),
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# Recent actions log
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# Live actions log
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html.Div([
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html.H5("Live Trading Actions (Real Market Data)", className="text-center mb-3"),
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html.H5("🔥 Live Trading Actions (Real-Time Stream)", className="text-center mb-3"),
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html.Div(id="actions-log")
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], className="mb-4"),
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# Auto-refresh for real-time updates
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# Ultra-fast refresh for real-time updates (100ms)
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dcc.Interval(
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id='market-data-interval',
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interval=1000, # Update every 1 second for real-time feel
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id='ultra-fast-interval',
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interval=100, # 100ms for ultra-low latency
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n_intervals=0
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)
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], className="container-fluid")
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], className="container-fluid bg-dark")
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def _setup_callbacks(self):
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"""Setup dashboard callbacks with real market data"""
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"""Setup ultra-fast callbacks with real-time streaming data"""
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@self.app.callback(
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[
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@ -223,34 +199,35 @@ class ScalpingDashboard:
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Output('btc-1s-chart', 'figure'),
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Output('actions-log', 'children')
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],
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[Input('market-data-interval', 'n_intervals')]
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[Input('ultra-fast-interval', 'n_intervals')]
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)
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def update_dashboard_with_real_data(n_intervals):
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"""Update all dashboard components with real market data"""
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def update_real_time_dashboard(n_intervals):
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"""Update all components with real-time streaming data"""
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try:
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with self.data_lock:
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# Update metrics
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pnl = f"${self.scalping_metrics['total_pnl']:+.2f}"
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win_rate = f"{self.scalping_metrics['win_rate']*100:.1f}%"
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total_trades = str(self.scalping_metrics['total_trades'])
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last_action = self.scalping_metrics['last_action'] or "WAITING"
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last_action = self.scalping_metrics['last_action'] or "⏳ WAITING"
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# Get current prices from real market data
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eth_price = self._get_current_price('ETH/USDT')
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btc_price = self._get_current_price('BTC/USDT')
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# Live prices from WebSocket stream
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eth_price = f"${self.live_prices['ETH/USDT']:.2f}" if self.live_prices['ETH/USDT'] > 0 else "🔄 Loading..."
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btc_price = f"${self.live_prices['BTC/USDT']:.2f}" if self.live_prices['BTC/USDT'] > 0 else "🔄 Loading..."
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# Refresh market data periodically (every 10 updates)
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# Refresh chart data every 10 intervals (1 second)
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if n_intervals % 10 == 0:
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self._refresh_market_data()
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self._refresh_live_data()
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# Create charts with real market data
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main_eth_chart = self._create_real_chart('ETH/USDT', '1s', main_chart=True)
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eth_1m_chart = self._create_real_chart('ETH/USDT', '1m')
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eth_1h_chart = self._create_real_chart('ETH/USDT', '1h')
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eth_1d_chart = self._create_real_chart('ETH/USDT', '1d')
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btc_1s_chart = self._create_real_chart('BTC/USDT', '1s')
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# Create real-time charts
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main_eth_chart = self._create_live_chart('ETH/USDT', '1s', main_chart=True)
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eth_1m_chart = self._create_live_chart('ETH/USDT', '1m')
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eth_1h_chart = self._create_live_chart('ETH/USDT', '1h')
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eth_1d_chart = self._create_live_chart('ETH/USDT', '1d')
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btc_1s_chart = self._create_live_chart('BTC/USDT', '1s')
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# Create actions log
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actions_log = self._create_actions_log()
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# Live actions log
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actions_log = self._create_live_actions_log()
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return (
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pnl, win_rate, total_trades, last_action, eth_price, btc_price,
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@ -259,71 +236,161 @@ class ScalpingDashboard:
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)
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except Exception as e:
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logger.error(f"Error updating dashboard: {e}")
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# Return safe defaults
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logger.error(f"Error in real-time update: {e}")
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return (
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"$0.00", "0%", "0", "ERROR", "$0", "$0",
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{}, {}, {}, {}, {}, "Loading real market data..."
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"$0.00", "0%", "0", "ERROR", "🔄 Loading...", "🔄 Loading...",
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{}, {}, {}, {}, {}, "🔄 Loading real-time data..."
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)
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def _refresh_market_data(self):
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"""Refresh market data from APIs"""
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def _start_real_time_streaming(self):
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"""Start WebSocket streaming for real-time price updates"""
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logger.info("🚀 Starting real-time WebSocket price streaming...")
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self.streaming = True
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# Start WebSocket streams for each symbol
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for symbol in ['ETHUSDT', 'BTCUSDT']:
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thread = Thread(target=self._websocket_price_stream, args=(symbol,), daemon=True)
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thread.start()
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self.websocket_threads.append(thread)
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logger.info("📡 WebSocket streams started for ETH/USDT and BTC/USDT")
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def _websocket_price_stream(self, symbol: str):
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"""WebSocket stream for real-time price updates"""
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url = f"wss://stream.binance.com:9443/ws/{symbol.lower()}@ticker"
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while self.streaming:
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try:
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# Get latest data for each chart (last 100 candles for efficiency)
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for symbol in self.market_data:
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for timeframe in self.market_data[symbol]:
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latest_data = self.data_provider.get_latest_candles(symbol, timeframe, limit=100)
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if latest_data is not None and not latest_data.empty:
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# Update our cache with latest data
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if self.market_data[symbol][timeframe] is not None:
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# Append new data and keep last 500 candles
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combined = pd.concat([self.market_data[symbol][timeframe], latest_data])
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combined = combined.drop_duplicates(subset=['timestamp'], keep='last')
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self.market_data[symbol][timeframe] = combined.tail(500)
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else:
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self.market_data[symbol][timeframe] = latest_data.tail(500)
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async def stream_prices():
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async with websockets.connect(url) as websocket:
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logger.info(f"📡 WebSocket connected for {symbol}")
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async for message in websocket:
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if not self.streaming:
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break
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try:
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data = json.loads(message)
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price = float(data.get('c', 0))
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# Update live prices
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with self.data_lock:
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formatted_symbol = f"{symbol[:3]}/{symbol[3:]}"
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self.live_prices[formatted_symbol] = price
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logger.debug(f"💰 {formatted_symbol}: ${price:.2f}")
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except Exception as e:
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logger.warning(f"Error refreshing market data: {e}")
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logger.warning(f"Error processing WebSocket data for {symbol}: {e}")
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# Run the async stream
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asyncio.new_event_loop().run_until_complete(stream_prices())
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def _get_current_price(self, symbol: str) -> str:
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"""Get current price from real market data"""
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try:
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data = self.market_data[symbol]['1s']
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if data is not None and not data.empty:
|
||||
current_price = data['close'].iloc[-1]
|
||||
return f"${current_price:.2f}"
|
||||
return "$0.00"
|
||||
except Exception as e:
|
||||
logger.warning(f"Error getting current price for {symbol}: {e}")
|
||||
return "$0.00"
|
||||
logger.error(f"WebSocket error for {symbol}: {e}")
|
||||
if self.streaming:
|
||||
logger.info(f"🔄 Reconnecting WebSocket for {symbol} in 5 seconds...")
|
||||
time.sleep(5)
|
||||
|
||||
def _create_real_chart(self, symbol: str, timeframe: str, main_chart: bool = False):
|
||||
"""Create chart using real market data"""
|
||||
def _refresh_live_data(self):
|
||||
"""Refresh chart data with fresh API calls (NO CACHING)"""
|
||||
try:
|
||||
data = self.market_data[symbol][timeframe]
|
||||
logger.info("🔄 Fetching fresh market data (NO CACHE)...")
|
||||
|
||||
if data is None or data.empty:
|
||||
# Return empty chart with message
|
||||
# Force fresh API calls for all timeframes
|
||||
for symbol, timeframes in self.chart_data.items():
|
||||
for timeframe in timeframes:
|
||||
try:
|
||||
# FORCE fresh data - explicitly set refresh=True
|
||||
fresh_data = self._fetch_fresh_candles(symbol, timeframe, limit=200)
|
||||
|
||||
if fresh_data is not None and not fresh_data.empty:
|
||||
with self.data_lock:
|
||||
self.chart_data[symbol][timeframe] = fresh_data
|
||||
logger.debug(f"✅ Fresh data loaded: {symbol} {timeframe} - {len(fresh_data)} candles")
|
||||
|
||||
except Exception as e:
|
||||
logger.warning(f"Error fetching fresh data for {symbol} {timeframe}: {e}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in live data refresh: {e}")
|
||||
|
||||
def _fetch_fresh_candles(self, symbol: str, timeframe: str, limit: int = 200) -> pd.DataFrame:
|
||||
"""Fetch fresh candles directly from Binance API (bypass all caching)"""
|
||||
try:
|
||||
# Convert symbol format
|
||||
binance_symbol = symbol.replace('/', '').upper()
|
||||
|
||||
# Convert timeframe
|
||||
timeframe_map = {
|
||||
'1s': '1s', '1m': '1m', '1h': '1h', '1d': '1d'
|
||||
}
|
||||
binance_timeframe = timeframe_map.get(timeframe, '1m')
|
||||
|
||||
# Direct API call to Binance
|
||||
url = "https://api.binance.com/api/v3/klines"
|
||||
params = {
|
||||
'symbol': binance_symbol,
|
||||
'interval': binance_timeframe,
|
||||
'limit': limit
|
||||
}
|
||||
|
||||
response = requests.get(url, params=params, timeout=5)
|
||||
response.raise_for_status()
|
||||
|
||||
data = response.json()
|
||||
|
||||
# Convert to DataFrame
|
||||
df = pd.DataFrame(data, columns=[
|
||||
'timestamp', 'open', 'high', 'low', 'close', 'volume',
|
||||
'close_time', 'quote_volume', 'trades', 'taker_buy_base',
|
||||
'taker_buy_quote', 'ignore'
|
||||
])
|
||||
|
||||
# Process columns with Sofia timezone
|
||||
df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms').dt.tz_localize('UTC').dt.tz_convert(self.timezone)
|
||||
for col in ['open', 'high', 'low', 'close', 'volume']:
|
||||
df[col] = df[col].astype(float)
|
||||
|
||||
# Keep only OHLCV columns
|
||||
df = df[['timestamp', 'open', 'high', 'low', 'close', 'volume']]
|
||||
df = df.sort_values('timestamp').reset_index(drop=True)
|
||||
|
||||
logger.debug(f"📊 Fresh API data: {symbol} {timeframe} - {len(df)} candles")
|
||||
return df
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching fresh candles from API: {e}")
|
||||
return pd.DataFrame()
|
||||
|
||||
def _create_live_chart(self, symbol: str, timeframe: str, main_chart: bool = False):
|
||||
"""Create charts with real-time streaming data"""
|
||||
try:
|
||||
with self.data_lock:
|
||||
data = self.chart_data[symbol][timeframe]
|
||||
|
||||
if data.empty:
|
||||
# Return loading chart
|
||||
fig = go.Figure()
|
||||
fig.add_annotation(
|
||||
text=f"Loading real market data for {symbol} {timeframe}...",
|
||||
text=f"🔄 Loading real-time data for {symbol} {timeframe}...",
|
||||
xref="paper", yref="paper",
|
||||
x=0.5, y=0.5, showarrow=False,
|
||||
font=dict(size=16, color="red")
|
||||
font=dict(size=16, color="#00ff88")
|
||||
)
|
||||
fig.update_layout(
|
||||
title=f"{symbol} {timeframe} - Real Market Data",
|
||||
title=f"📡 {symbol} {timeframe} - Live Stream",
|
||||
template="plotly_dark",
|
||||
height=500 if main_chart else 250
|
||||
height=600 if main_chart else 300,
|
||||
paper_bgcolor='#1e1e1e',
|
||||
plot_bgcolor='#1e1e1e'
|
||||
)
|
||||
return fig
|
||||
|
||||
# Create candlestick chart from real data
|
||||
# Create real-time chart
|
||||
fig = go.Figure()
|
||||
|
||||
if main_chart:
|
||||
# Main chart with candlesticks and volume
|
||||
# Main chart with candlesticks, volume, and live price
|
||||
fig.add_trace(go.Candlestick(
|
||||
x=data['timestamp'],
|
||||
open=data['open'],
|
||||
@ -335,127 +402,157 @@ class ScalpingDashboard:
|
||||
decreasing_line_color='#ff4444'
|
||||
))
|
||||
|
||||
# Add volume as secondary plot
|
||||
# Volume subplot
|
||||
fig.add_trace(go.Bar(
|
||||
x=data['timestamp'],
|
||||
y=data['volume'],
|
||||
name="Volume",
|
||||
yaxis='y2',
|
||||
opacity=0.3,
|
||||
marker_color='lightblue'
|
||||
opacity=0.4,
|
||||
marker_color='#4CAF50'
|
||||
))
|
||||
|
||||
# Main chart layout
|
||||
# Current live price line
|
||||
current_price = self.live_prices.get(symbol, data['close'].iloc[-1] if not data.empty else 0)
|
||||
if current_price > 0:
|
||||
fig.add_hline(
|
||||
y=current_price,
|
||||
line_dash="dot",
|
||||
line_color="#FFD700",
|
||||
line_width=2,
|
||||
annotation_text=f"LIVE: ${current_price:.2f}",
|
||||
annotation_position="right"
|
||||
)
|
||||
|
||||
# Sofia time in title
|
||||
sofia_time = datetime.now(self.timezone).strftime("%H:%M:%S %Z")
|
||||
fig.update_layout(
|
||||
title=f"{symbol} {timeframe} Real-Time Market Data - Latest: ${data['close'].iloc[-1]:.2f}",
|
||||
title=f"📈 {symbol} {timeframe} LIVE | Sofia Time: {sofia_time} | Current: ${current_price:.2f}",
|
||||
yaxis_title="Price (USDT)",
|
||||
yaxis2=dict(title="Volume", overlaying='y', side='right'),
|
||||
template="plotly_dark",
|
||||
showlegend=False,
|
||||
height=500
|
||||
)
|
||||
|
||||
# Add current price line
|
||||
current_price = data['close'].iloc[-1]
|
||||
fig.add_hline(
|
||||
y=current_price,
|
||||
line_dash="dash",
|
||||
line_color="yellow",
|
||||
annotation_text=f"${current_price:.2f}",
|
||||
annotation_position="right"
|
||||
height=600,
|
||||
paper_bgcolor='#1e1e1e',
|
||||
plot_bgcolor='#1e1e1e'
|
||||
)
|
||||
|
||||
else:
|
||||
# Small chart - simple line chart
|
||||
price_change = ((data['close'].iloc[-1] - data['close'].iloc[0]) / data['close'].iloc[0]) * 100
|
||||
line_color = '#00ff88' if price_change >= 0 else '#ff4444'
|
||||
|
||||
# Small chart - line chart with live updates
|
||||
fig.add_trace(go.Scatter(
|
||||
x=data['timestamp'],
|
||||
y=data['close'],
|
||||
mode='lines',
|
||||
name=f"{symbol} {timeframe}",
|
||||
line=dict(color=line_color, width=2)
|
||||
line=dict(color='#00ff88', width=2)
|
||||
))
|
||||
|
||||
# Live price point
|
||||
current_price = self.live_prices.get(symbol, data['close'].iloc[-1] if not data.empty else 0)
|
||||
if current_price > 0:
|
||||
fig.add_trace(go.Scatter(
|
||||
x=[data['timestamp'].iloc[-1]] if not data.empty else [datetime.now(self.timezone)],
|
||||
y=[current_price],
|
||||
mode='markers',
|
||||
marker=dict(color='#FFD700', size=8),
|
||||
name="Live Price"
|
||||
))
|
||||
|
||||
# Small chart layout
|
||||
fig.update_layout(
|
||||
template="plotly_dark",
|
||||
showlegend=False,
|
||||
margin=dict(l=10, r=10, t=30, b=10),
|
||||
height=250,
|
||||
title=f"{symbol} {timeframe}: ${data['close'].iloc[-1]:.2f}"
|
||||
)
|
||||
|
||||
# Add price change annotation
|
||||
change_color = "green" if price_change >= 0 else "red"
|
||||
fig.add_annotation(
|
||||
text=f"{price_change:+.2f}%",
|
||||
xref="paper", yref="paper",
|
||||
x=0.95, y=0.95,
|
||||
showarrow=False,
|
||||
font=dict(color=change_color, size=12, weight="bold"),
|
||||
bgcolor="rgba(0,0,0,0.7)"
|
||||
margin=dict(l=10, r=10, t=40, b=10),
|
||||
height=300,
|
||||
title=f"📊 {symbol} {timeframe} | ${current_price:.2f}",
|
||||
paper_bgcolor='#1e1e1e',
|
||||
plot_bgcolor='#1e1e1e'
|
||||
)
|
||||
|
||||
return fig
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error creating chart for {symbol} {timeframe}: {e}")
|
||||
logger.error(f"Error creating live chart for {symbol} {timeframe}: {e}")
|
||||
# Return error chart
|
||||
fig = go.Figure()
|
||||
fig.add_annotation(
|
||||
text=f"Error loading {symbol} {timeframe}",
|
||||
text=f"❌ Error loading {symbol} {timeframe}",
|
||||
xref="paper", yref="paper",
|
||||
x=0.5, y=0.5, showarrow=False,
|
||||
font=dict(size=14, color="red")
|
||||
font=dict(size=14, color="#ff4444")
|
||||
)
|
||||
fig.update_layout(
|
||||
template="plotly_dark",
|
||||
height=500 if main_chart else 250
|
||||
height=600 if main_chart else 300,
|
||||
paper_bgcolor='#1e1e1e',
|
||||
plot_bgcolor='#1e1e1e'
|
||||
)
|
||||
return fig
|
||||
|
||||
def _create_actions_log(self):
|
||||
"""Create trading actions log"""
|
||||
def _create_live_actions_log(self):
|
||||
"""Create live trading actions log"""
|
||||
if not self.recent_decisions:
|
||||
return html.P("Waiting for trading signals from real market data...", className="text-muted text-center")
|
||||
return html.P("⏳ Waiting for live trading signals from real-time stream...",
|
||||
className="text-muted text-center")
|
||||
|
||||
log_items = []
|
||||
for action in self.recent_decisions[-5:]: # Show last 5 actions
|
||||
for action in self.recent_decisions[-5:]:
|
||||
sofia_time = action.timestamp.astimezone(self.timezone).strftime("%H:%M:%S")
|
||||
log_items.append(
|
||||
html.P(
|
||||
f"🔥 {action.action} {action.symbol} @ ${action.price:.2f} "
|
||||
f"(Confidence: {action.confidence:.1%}) - Real Market Data",
|
||||
className="text-center mb-1"
|
||||
f"🔥 {sofia_time} | {action.action} {action.symbol} @ ${action.price:.2f} "
|
||||
f"(Confidence: {action.confidence:.1%}) | 📡 LIVE STREAM",
|
||||
className="text-center mb-1 text-light"
|
||||
)
|
||||
)
|
||||
|
||||
return html.Div(log_items)
|
||||
|
||||
def add_trading_decision(self, decision: TradingAction):
|
||||
"""Add a new trading decision based on real market data"""
|
||||
"""Add trading decision with Sofia timezone"""
|
||||
decision.timestamp = decision.timestamp.astimezone(self.timezone)
|
||||
self.recent_decisions.append(decision)
|
||||
|
||||
if len(self.recent_decisions) > 50:
|
||||
self.recent_decisions.pop(0)
|
||||
|
||||
self.scalping_metrics['total_trades'] += 1
|
||||
self.scalping_metrics['last_action'] = f"{decision.action} {decision.symbol}"
|
||||
|
||||
logger.info(f"📊 Added real market trading decision: {decision.action} {decision.symbol} @ ${decision.price:.2f}")
|
||||
sofia_time = decision.timestamp.strftime("%H:%M:%S %Z")
|
||||
logger.info(f"🔥 {sofia_time} | Live trading decision: {decision.action} {decision.symbol} @ ${decision.price:.2f}")
|
||||
|
||||
def run(self, host: str = '127.0.0.1', port: int = 8050, debug: bool = False):
|
||||
"""Run the real market data dashboard"""
|
||||
logger.info(f"🚀 Starting Real Market Data Dashboard at http://{host}:{port}")
|
||||
logger.info("📊 Dashboard Features:")
|
||||
logger.info(" • Main 1s ETH/USDT chart with real market data")
|
||||
logger.info(" • 4 small charts: 1m/1h/1d ETH + 1s BTC")
|
||||
logger.info(" • 500 candles preloaded from Binance API")
|
||||
logger.info(" • Real-time updates every second")
|
||||
logger.info(" • NO GENERATED DATA - 100% real market feeds")
|
||||
def stop_streaming(self):
|
||||
"""Stop all WebSocket streams"""
|
||||
logger.info("🛑 Stopping real-time WebSocket streams...")
|
||||
self.streaming = False
|
||||
|
||||
for thread in self.websocket_threads:
|
||||
if thread.is_alive():
|
||||
thread.join(timeout=2)
|
||||
|
||||
logger.info("📡 WebSocket streams stopped")
|
||||
|
||||
def run(self, host: str = '127.0.0.1', port: int = 8051, debug: bool = False):
|
||||
"""Run the real-time dashboard"""
|
||||
try:
|
||||
logger.info(f"🚀 Starting Real-Time Scalping Dashboard at http://{host}:{port}")
|
||||
logger.info("📡 Features:")
|
||||
logger.info(" • WebSocket price streaming (100ms updates)")
|
||||
logger.info(" • NO CACHED DATA - Always fresh API calls")
|
||||
logger.info(f" • Sofia timezone: {self.timezone}")
|
||||
logger.info(" • Ultra-low latency real-time charts")
|
||||
logger.info(" • Live P&L and trading metrics")
|
||||
|
||||
self.app.run(host=host, port=port, debug=debug)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
logger.info("👋 Shutting down real-time dashboard...")
|
||||
finally:
|
||||
self.stop_streaming()
|
||||
|
||||
def create_scalping_dashboard(data_provider=None, orchestrator=None):
|
||||
"""Create dashboard instance with real market data"""
|
||||
return ScalpingDashboard(data_provider, orchestrator)
|
||||
"""Create real-time dashboard instance"""
|
||||
return RealTimeScalpingDashboard(data_provider, orchestrator)
|
||||
|
||||
# For backward compatibility
|
||||
ScalpingDashboard = RealTimeScalpingDashboard
|
Loading…
x
Reference in New Issue
Block a user