461 lines
19 KiB
Python
461 lines
19 KiB
Python
"""
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Ultra-Fast Scalping Dashboard (500x Leverage) - Real Market Data
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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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- 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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"""
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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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from datetime import datetime, timedelta
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from threading import Thread
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from typing import Dict, List, Optional, Any
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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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from core.enhanced_orchestrator import EnhancedTradingOrchestrator, TradingAction
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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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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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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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# 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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'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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'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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},
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'BTC/USDT': {
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'1s': None # Small chart
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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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# Create Dash app
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self.app = dash.Dash(__name__)
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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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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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def _setup_layout(self):
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"""Setup the 5-chart dashboard layout"""
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self.app.layout = html.Div([
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# Header with real-time 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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# Real-time 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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], 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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], 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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], 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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], 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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], 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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], 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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html.Div([
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html.H4("ETH/USDT 1s Real-Time Chart (Main Trading Signal)",
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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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], className="mb-4"),
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# Row of 4 small charts
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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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], 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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], 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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], 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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], className="col-md-3")
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], className="row mb-4"),
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# Recent 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.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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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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n_intervals=0
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)
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], className="container-fluid")
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def _setup_callbacks(self):
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"""Setup dashboard callbacks with real market data"""
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@self.app.callback(
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[
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Output('live-pnl', 'children'),
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Output('win-rate', 'children'),
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Output('total-trades', 'children'),
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Output('last-action', 'children'),
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Output('eth-price', 'children'),
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Output('btc-price', 'children'),
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Output('main-eth-1s-chart', 'figure'),
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Output('eth-1m-chart', 'figure'),
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Output('eth-1h-chart', 'figure'),
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Output('eth-1d-chart', 'figure'),
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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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)
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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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try:
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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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# 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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# Refresh market data periodically (every 10 updates)
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if n_intervals % 10 == 0:
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self._refresh_market_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 actions log
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actions_log = self._create_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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main_eth_chart, eth_1m_chart, eth_1h_chart, eth_1d_chart, btc_1s_chart,
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actions_log
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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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return (
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"$0.00", "0%", "0", "ERROR", "$0", "$0",
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{}, {}, {}, {}, {}, "Loading real market 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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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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except Exception as e:
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logger.warning(f"Error refreshing market data: {e}")
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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:
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current_price = data['close'].iloc[-1]
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return f"${current_price:.2f}"
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return "$0.00"
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except Exception as e:
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logger.warning(f"Error getting current price for {symbol}: {e}")
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return "$0.00"
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def _create_real_chart(self, symbol: str, timeframe: str, main_chart: bool = False):
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"""Create chart using real market data"""
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try:
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data = self.market_data[symbol][timeframe]
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if data is None or data.empty:
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# Return empty chart with message
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fig = go.Figure()
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fig.add_annotation(
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text=f"Loading real market data for {symbol} {timeframe}...",
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xref="paper", yref="paper",
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x=0.5, y=0.5, showarrow=False,
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font=dict(size=16, color="red")
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)
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fig.update_layout(
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title=f"{symbol} {timeframe} - Real Market Data",
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template="plotly_dark",
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height=500 if main_chart else 250
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)
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return fig
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# Create candlestick chart from real data
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fig = go.Figure()
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if main_chart:
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# Main chart with candlesticks and volume
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fig.add_trace(go.Candlestick(
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x=data['timestamp'],
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open=data['open'],
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high=data['high'],
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low=data['low'],
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close=data['close'],
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name=f"{symbol} {timeframe}",
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increasing_line_color='#00ff88',
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decreasing_line_color='#ff4444'
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))
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# Add volume as secondary plot
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fig.add_trace(go.Bar(
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x=data['timestamp'],
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y=data['volume'],
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name="Volume",
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yaxis='y2',
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opacity=0.3,
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marker_color='lightblue'
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))
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# Main chart layout
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fig.update_layout(
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title=f"{symbol} {timeframe} Real-Time Market Data - Latest: ${data['close'].iloc[-1]:.2f}",
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yaxis_title="Price (USDT)",
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yaxis2=dict(title="Volume", overlaying='y', side='right'),
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template="plotly_dark",
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showlegend=False,
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height=500
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)
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# Add current price line
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current_price = data['close'].iloc[-1]
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fig.add_hline(
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y=current_price,
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line_dash="dash",
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line_color="yellow",
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annotation_text=f"${current_price:.2f}",
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annotation_position="right"
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)
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else:
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# Small chart - simple line chart
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price_change = ((data['close'].iloc[-1] - data['close'].iloc[0]) / data['close'].iloc[0]) * 100
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line_color = '#00ff88' if price_change >= 0 else '#ff4444'
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fig.add_trace(go.Scatter(
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x=data['timestamp'],
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y=data['close'],
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mode='lines',
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name=f"{symbol} {timeframe}",
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line=dict(color=line_color, width=2)
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))
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# Small chart layout
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fig.update_layout(
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template="plotly_dark",
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showlegend=False,
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margin=dict(l=10, r=10, t=30, b=10),
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height=250,
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title=f"{symbol} {timeframe}: ${data['close'].iloc[-1]:.2f}"
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)
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# Add price change annotation
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change_color = "green" if price_change >= 0 else "red"
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fig.add_annotation(
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text=f"{price_change:+.2f}%",
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xref="paper", yref="paper",
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x=0.95, y=0.95,
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showarrow=False,
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font=dict(color=change_color, size=12, weight="bold"),
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bgcolor="rgba(0,0,0,0.7)"
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)
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return fig
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except Exception as e:
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logger.error(f"Error creating chart for {symbol} {timeframe}: {e}")
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# Return error chart
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fig = go.Figure()
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fig.add_annotation(
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text=f"Error loading {symbol} {timeframe}",
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xref="paper", yref="paper",
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x=0.5, y=0.5, showarrow=False,
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font=dict(size=14, color="red")
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)
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fig.update_layout(
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template="plotly_dark",
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height=500 if main_chart else 250
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)
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return fig
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def _create_actions_log(self):
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"""Create trading actions log"""
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if not self.recent_decisions:
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return html.P("Waiting for trading signals from real market data...", className="text-muted text-center")
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log_items = []
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for action in self.recent_decisions[-5:]: # Show last 5 actions
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log_items.append(
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html.P(
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f"🔥 {action.action} {action.symbol} @ ${action.price:.2f} "
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f"(Confidence: {action.confidence:.1%}) - Real Market Data",
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className="text-center mb-1"
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)
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)
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return html.Div(log_items)
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def add_trading_decision(self, decision: TradingAction):
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"""Add a new trading decision based on real market data"""
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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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self.scalping_metrics['total_trades'] += 1
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self.scalping_metrics['last_action'] = f"{decision.action} {decision.symbol}"
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logger.info(f"📊 Added real market trading decision: {decision.action} {decision.symbol} @ ${decision.price:.2f}")
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def run(self, host: str = '127.0.0.1', port: int = 8050, debug: bool = False):
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"""Run the real market data dashboard"""
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logger.info(f"🚀 Starting Real Market Data Dashboard at http://{host}:{port}")
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logger.info("📊 Dashboard Features:")
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logger.info(" • Main 1s ETH/USDT chart with real market data")
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logger.info(" • 4 small charts: 1m/1h/1d ETH + 1s BTC")
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logger.info(" • 500 candles preloaded from Binance API")
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logger.info(" • Real-time updates every second")
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logger.info(" • NO GENERATED DATA - 100% real market feeds")
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self.app.run(host=host, port=port, debug=debug)
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def create_scalping_dashboard(data_provider=None, orchestrator=None):
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"""Create dashboard instance with real market data"""
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return ScalpingDashboard(data_provider, orchestrator) |