220 lines
7.6 KiB
Python
220 lines
7.6 KiB
Python
#!/usr/bin/env python3
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"""
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分析ETH过去4小时的市场数据，检查为什么没有开仓
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"""
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import sys
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import os
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import asyncio
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from datetime import datetime, timedelta
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# 添加项目路径
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'backend'))
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from app.services.binance_service import binance_service
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from app.crypto_agent.market_signal_analyzer import MarketSignalAnalyzer
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from app.crypto_agent.trading_decision_maker import TradingDecisionMaker
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from app.services.paper_trading_service import get_paper_trading_service
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from app.utils.logger import logger
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async def analyze_eth_4h():
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"""分析ETH过去4小时的情况"""
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print("=" * 80)
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print("📊 ETH 过去4小时市场分析")
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print("=" * 80)
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print(f"时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
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# 1. 获取服务
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binance = binance_service
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signal_analyzer = MarketSignalAnalyzer()
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decision_maker = TradingDecisionMaker()
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trading_service = get_paper_trading_service()
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# 2. 获取当前行情
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print("\n📈 当前行情:")
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current_price = binance.get_current_price('ETHUSDT')
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stats = binance.get_24h_stats('ETHUSDT')
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if current_price:
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print(f" 价格: ${current_price:,.2f}")
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if stats:
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print(f" 涨跌: {stats.get('priceChangePercent', 0):+.2f}%")
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print(f" 成交量: {stats.get('volume', 0):,.0f}")
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# 3. 获取K线数据（多周期）
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print("\n📊 获取K线数据...")
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data = binance.get_multi_timeframe_data('ETHUSDT')
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if not data:
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print("❌ 无法获取K线数据")
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return
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# 显示各周期数据量
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for tf, df in data.items():
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print(f" {tf}: {len(df)} 条数据")
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# 4. 检查过去4小时的价格波动
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print("\n📊 过去4小时价格波动:")
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df_15m = data.get('15m')
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if df_15m is not None and len(df_15m) > 0:
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# 获取过去4小时的15分钟数据（16根）
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recent_4h = df_15m.tail(16)
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if len(recent_4h) > 0:
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high = recent_4h['high'].max()
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low = recent_4h['low'].min()
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start_price = recent_4h.iloc[0]['close']
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end_price = recent_4h.iloc[-1]['close']
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volatility = ((high - low) / start_price) * 100
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price_change = ((end_price - start_price) / start_price) * 100
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print(f" 最高: ${high:,.2f}")
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print(f" 最低: ${low:,.2f}")
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print(f" 波动幅度: {volatility:.2f}%")
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print(f" 价格变化: {price_change:+.2f}%")
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# 5. 运行信号分析
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print("\n🔍 信号分析:")
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print("-" * 80)
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analysis = await signal_analyzer.analyze('ETHUSDT', data)
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# 显示分析结果
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print(f"\n市场状态: {analysis.get('analysis_summary', 'N/A')}")
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# 新闻情绪
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if analysis.get('news_sentiment'):
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sentiment_map = {'positive': '📈 积极', 'negative': '📉 消极', 'neutral': '➖ 中性'}
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print(f"新闻情绪: {sentiment_map.get(analysis['news_sentiment'], analysis['news_sentiment'])}")
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# 信号
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signals = analysis.get('signals', [])
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if signals:
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print(f"\n🎯 生成 {len(signals)} 个信号:")
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for sig in signals:
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action = sig.get('action', 'wait')
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action_map = {'buy': '🟢 做多', 'sell': '🔴 做空', 'wait': '⏸️ 观望'}
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grade = sig.get('grade', 'D')
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confidence = sig.get('confidence', 0)
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print(f"\n {action_map.get(action, action)} [{grade}级] {confidence}%")
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print(f" 入场: ${sig.get('entry_price', 0):,.2f}")
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print(f" 止损: ${sig.get('stop_loss', 0):,.2f}")
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print(f" 止盈: ${sig.get('take_profit', 0):,.2f}")
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print(f" 入场方式: {sig.get('entry_type', 'N/A')}")
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if sig.get('reason'):
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print(f" 理由: {sig['reason']}")
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if sig.get('risk_warning'):
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print(f" ⚠️ 风险: {sig['risk_warning']}")
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else:
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print("\n⏸️ 无交易信号")
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# 6. 检查当前持仓
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print("\n💼 当前持仓:")
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account = trading_service.get_account_status()
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active_orders = trading_service.get_active_orders()
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print(f" 余额: ${account['current_balance']:,.2f}")
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print(f" 已用保证金: ${account['used_margin']:,.2f}")
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print(f" 持仓数量: {len(active_orders)}")
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if active_orders:
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for order in active_orders:
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print(f"\n {order.symbol} {order.side.value}")
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print(f" 入场价: ${order.filled_price:,.2f}")
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print(f" 当前价: ${current_price:,.2f}")
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print(f" 保证金: ${order.margin:,.2f}")
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print(f" 杠杆: {order.leverage}x")
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else:
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print(" 无持仓")
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# 7. 模拟交易决策
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print("\n🤖 交易决策分析:")
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print("-" * 80)
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if signals:
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# 对每个信号做决策
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for sig in signals[:3]: # 只看前3个
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decision = await decision_maker.make_decision(
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symbol='ETHUSDT',
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signals=[sig],
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current_data=data,
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current_price=current_price
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)
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print(f"\n信号: {sig.get('action', 'wait')} | {sig.get('grade')}级 | {sig.get('confidence')}%")
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print(f"决策: {decision['decision']}")
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print(f"理由: {decision.get('reason', 'N/A')}")
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if decision.get('orders_to_open'):
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print(f"开仓: {len(decision['orders_to_open'])} 个")
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if decision.get('orders_to_close'):
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print(f"平仓: {decision['orders_to_close']}")
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else:
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print("无信号，不生成决策")
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# 8. 检查是否有追涨杀跌的情况
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print("\n⚠️ 追涨杀跌检测:")
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print("-" * 80)
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if df_15m is not None and len(df_15m) >= 5:
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recent = df_15m.tail(5)
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# 计算RSI
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import pandas_ta as ta
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rsi = recent['close'].ta.rsi(length=14)
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current_rsi = rsi.iloc[-1] if not rsi.empty else 50
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# 检查连续大阳线/阴线
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big_moves = 0
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for i in range(1, min(4, len(recent))):
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change = abs((recent.iloc[i]['close'] - recent.iloc[i-1]['close']) / recent.iloc[i-1]['close']) * 100
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if change >= 1.0:
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big_moves += 1
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# 检查价格偏离EMA
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ema5 = recent['close'].ta.ema(length=5)
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current_price = recent.iloc[-1]['close']
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deviation = abs((current_price - ema5.iloc[-1]) / ema5.iloc[-1]) * 100 if not ema5.empty else 0
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print(f" RSI(14): {current_rsi:.1f}")
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print(f" 连续大K线: {big_moves} 根")
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print(f" 偏离EMA5: {deviation:.2f}%")
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# 判断是否满足追涨杀跌条件
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is_chasing = False
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reasons = []
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if current_rsi > 65 or current_rsi < 35:
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is_chasing = True
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reasons.append(f"RSI处于极端区间 ({current_rsi:.1f})")
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if big_moves >= 2:
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is_chasing = True
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reasons.append(f"连续{big_moves}根大K线")
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if deviation > 1.5:
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is_chasing = True
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reasons.append(f"价格偏离EMA5超过1.5%")
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if is_chasing:
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print(f"\n 🚨 检测到追涨杀跌条件！")
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for reason in reasons:
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print(f" - {reason}")
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print(f"\n → 这是防止开仓的原因之一")
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else:
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print(f"\n ✅ 未检测到追涨杀跌条件")
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print("\n" + "=" * 80)
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print("分析完成")
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print("=" * 80)
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if __name__ == "__main__":
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try:
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asyncio.run(analyze_eth_4h())
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except Exception as e:
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print(f"\n❌ 分析失败: {e}")
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import traceback
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traceback.print_exc()
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