348 lines
14 KiB
Python
348 lines
14 KiB
Python
"""
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推荐交易对模块 - 生成交易推荐供手动参考
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"""
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import asyncio
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import logging
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from typing import List, Dict, Optional
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from datetime import datetime, timedelta
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try:
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from .binance_client import BinanceClient
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from .market_scanner import MarketScanner
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from .risk_manager import RiskManager
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from . import config
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except ImportError:
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from binance_client import BinanceClient
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from market_scanner import MarketScanner
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from risk_manager import RiskManager
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import config
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logger = logging.getLogger(__name__)
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# 尝试导入数据库模型
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DB_AVAILABLE = False
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TradeRecommendation = None
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try:
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import sys
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from pathlib import Path
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project_root = Path(__file__).parent.parent
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backend_path = project_root / 'backend'
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if backend_path.exists():
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sys.path.insert(0, str(backend_path))
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from database.models import TradeRecommendation
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DB_AVAILABLE = True
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logger.info("✓ 数据库模型导入成功，推荐记录将保存到数据库")
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else:
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logger.warning("⚠ backend目录不存在，无法使用数据库功能")
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DB_AVAILABLE = False
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except ImportError as e:
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logger.warning(f"⚠ 无法导入数据库模型: {e}")
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DB_AVAILABLE = False
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except Exception as e:
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logger.warning(f"⚠ 数据库初始化失败: {e}")
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DB_AVAILABLE = False
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class TradeRecommender:
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"""推荐交易对生成器"""
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def __init__(
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self,
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client: BinanceClient,
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scanner: MarketScanner,
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risk_manager: RiskManager
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):
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"""
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初始化推荐器
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Args:
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client: 币安客户端
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scanner: 市场扫描器
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risk_manager: 风险管理器
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"""
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self.client = client
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self.scanner = scanner
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self.risk_manager = risk_manager
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async def generate_recommendations(
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self,
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min_signal_strength: int = 5,
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max_recommendations: int = 20
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) -> List[Dict]:
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"""
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生成交易推荐
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Args:
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min_signal_strength: 最小信号强度（默认5，低于此强度的不推荐）
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max_recommendations: 最大推荐数量
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Returns:
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推荐列表
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"""
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logger.info("开始生成交易推荐...")
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# 1. 扫描市场
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top_symbols = await self.scanner.scan_market()
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if not top_symbols:
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logger.warning("未找到符合条件的交易对")
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return []
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recommendations = []
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# 2. 对每个交易对进行分析
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for symbol_info in top_symbols:
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if len(recommendations) >= max_recommendations:
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break
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symbol = symbol_info['symbol']
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current_price = symbol_info['price']
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change_percent = symbol_info.get('changePercent', 0)
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# 3. 分析交易信号（使用策略模块的逻辑）
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trade_signal = await self._analyze_trade_signal(symbol_info)
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# 4. 如果信号强度足够，生成推荐
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if trade_signal['should_trade'] and trade_signal['strength'] >= min_signal_strength:
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recommendation = await self._create_recommendation(
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symbol_info, trade_signal
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)
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if recommendation:
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recommendations.append(recommendation)
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logger.info(f"生成了 {len(recommendations)} 个交易推荐")
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return recommendations
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async def _analyze_trade_signal(self, symbol_info: Dict) -> Dict:
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"""
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分析交易信号（复用策略模块的逻辑）
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Args:
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symbol_info: 交易对信息
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Returns:
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交易信号字典
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"""
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symbol = symbol_info['symbol']
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current_price = symbol_info['price']
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rsi = symbol_info.get('rsi')
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macd = symbol_info.get('macd')
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bollinger = symbol_info.get('bollinger')
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market_regime = symbol_info.get('marketRegime', 'unknown')
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ema20 = symbol_info.get('ema20')
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ema50 = symbol_info.get('ema50')
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ema20_4h = symbol_info.get('ema20_4h')
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price_4h = symbol_info.get('price_4h', current_price)
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# 判断4H周期趋势方向
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trend_4h = None
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if ema20_4h is not None:
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if price_4h > ema20_4h:
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trend_4h = 'up'
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elif price_4h < ema20_4h:
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trend_4h = 'down'
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else:
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trend_4h = 'neutral'
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signal_strength = 0
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reasons = []
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direction = None
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# 策略1：均值回归（震荡市场）
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if market_regime == 'ranging':
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if rsi and rsi < 30:
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if trend_4h in ('up', 'neutral', None):
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signal_strength += 4
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reasons.append(f"RSI超卖({rsi:.1f})")
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if direction is None:
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direction = 'BUY'
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elif rsi and rsi > 70:
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if trend_4h in ('down', 'neutral', None):
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signal_strength += 4
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reasons.append(f"RSI超买({rsi:.1f})")
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if direction is None:
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direction = 'SELL'
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if bollinger and current_price <= bollinger.get('lower'):
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if trend_4h in ('up', 'neutral', None):
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signal_strength += 3
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reasons.append("触及布林带下轨")
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if direction is None:
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direction = 'BUY'
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elif bollinger and current_price >= bollinger.get('upper'):
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if trend_4h in ('down', 'neutral', None):
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signal_strength += 3
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reasons.append("触及布林带上轨")
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if direction is None:
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direction = 'SELL'
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# 策略2：趋势跟踪（趋势市场）
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elif market_regime == 'trending':
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if macd and macd.get('macd', 0) > macd.get('signal', 0) and macd.get('histogram', 0) > 0:
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if trend_4h in ('up', 'neutral', None):
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signal_strength += 3
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reasons.append("MACD金叉")
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if direction is None:
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direction = 'BUY'
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elif macd and macd.get('macd', 0) < macd.get('signal', 0) and macd.get('histogram', 0) < 0:
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if trend_4h in ('down', 'neutral', None):
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signal_strength += 3
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reasons.append("MACD死叉")
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if direction is None:
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direction = 'SELL'
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if ema20 and ema50:
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if current_price > ema20 > ema50:
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if trend_4h in ('up', 'neutral', None):
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signal_strength += 2
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reasons.append("价格在均线之上")
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if direction is None:
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direction = 'BUY'
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elif current_price < ema20 < ema50:
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if trend_4h in ('down', 'neutral', None):
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signal_strength += 2
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reasons.append("价格在均线之下")
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if direction is None:
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direction = 'SELL'
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# 多周期共振加分
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if direction and trend_4h:
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if (direction == 'BUY' and trend_4h == 'up') or (direction == 'SELL' and trend_4h == 'down'):
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signal_strength += 2
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reasons.append("4H周期共振确认")
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# 判断是否应该交易
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min_signal_strength = config.TRADING_CONFIG.get('MIN_SIGNAL_STRENGTH', 7)
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should_trade = signal_strength >= min_signal_strength
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# 禁止逆4H趋势交易
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if direction and trend_4h:
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if (direction == 'BUY' and trend_4h == 'down') or (direction == 'SELL' and trend_4h == 'up'):
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should_trade = False
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reasons.append("❌ 禁止逆4H趋势交易")
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return {
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'should_trade': should_trade,
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'direction': direction,
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'reason': ', '.join(reasons) if reasons else '无明确信号',
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'strength': signal_strength,
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'trend_4h': trend_4h
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}
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async def _create_recommendation(
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self,
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symbol_info: Dict,
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trade_signal: Dict
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) -> Optional[Dict]:
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"""
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创建推荐记录
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Args:
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symbol_info: 交易对信息
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trade_signal: 交易信号
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Returns:
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推荐字典
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"""
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try:
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symbol = symbol_info['symbol']
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current_price = symbol_info['price']
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direction = trade_signal['direction']
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# 计算建议的止损止盈
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entry_price = current_price
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stop_loss_price = self.risk_manager.get_stop_loss_price(
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entry_price,
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direction,
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klines=symbol_info.get('klines'),
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bollinger=symbol_info.get('bollinger'),
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atr=symbol_info.get('atr')
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)
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# 计算止损百分比
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if direction == 'BUY':
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stop_loss_pct = (entry_price - stop_loss_price) / entry_price
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else:
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stop_loss_pct = (stop_loss_price - entry_price) / entry_price
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# 第一目标：盈亏比1:1
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if direction == 'BUY':
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take_profit_1 = entry_price + (entry_price - stop_loss_price)
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else:
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take_profit_1 = entry_price - (stop_loss_price - entry_price)
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# 第二目标：止损的2.5倍
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take_profit_2_pct = stop_loss_pct * 2.5
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take_profit_2 = self.risk_manager.get_take_profit_price(
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entry_price, direction, take_profit_pct=take_profit_2_pct
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)
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# 建议仓位（根据信号强度调整）
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base_position_pct = config.TRADING_CONFIG.get('MAX_POSITION_PERCENT', 0.05)
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signal_strength = trade_signal['strength']
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# 信号强度越高，建议仓位可以适当增加（但不超过1.5倍）
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position_multiplier = min(1.0 + (signal_strength - 5) * 0.1, 1.5)
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suggested_position_pct = base_position_pct * position_multiplier
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# 计算建议的挂单价（使用限价单，而不是市价单）
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# 对于做多：建议价格略低于当前价格（当前价格的99.5%），以便在回调时买入
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# 对于做空：建议价格略高于当前价格（当前价格的100.5%），以便在反弹时卖出
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limit_price_offset_pct = config.TRADING_CONFIG.get('LIMIT_ORDER_OFFSET_PCT', 0.5) # 默认0.5%
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if direction == 'BUY':
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suggested_limit_price = current_price * (1 - limit_price_offset_pct / 100)
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else: # SELL
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suggested_limit_price = current_price * (1 + limit_price_offset_pct / 100)
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# 准备推荐数据
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recommendation_data = {
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'symbol': symbol,
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'direction': direction,
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'current_price': current_price,
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'change_percent': symbol_info.get('changePercent', 0),
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'recommendation_reason': trade_signal['reason'],
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'signal_strength': signal_strength,
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'market_regime': symbol_info.get('marketRegime'),
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'trend_4h': trade_signal.get('trend_4h'),
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'rsi': symbol_info.get('rsi'),
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'macd_histogram': symbol_info.get('macd', {}).get('histogram') if symbol_info.get('macd') else None,
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'bollinger_upper': symbol_info.get('bollinger', {}).get('upper') if symbol_info.get('bollinger') else None,
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'bollinger_middle': symbol_info.get('bollinger', {}).get('middle') if symbol_info.get('bollinger') else None,
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'bollinger_lower': symbol_info.get('bollinger', {}).get('lower') if symbol_info.get('bollinger') else None,
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'ema20': symbol_info.get('ema20'),
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'ema50': symbol_info.get('ema50'),
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'ema20_4h': symbol_info.get('ema20_4h'),
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'atr': symbol_info.get('atr'),
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'suggested_stop_loss': stop_loss_price,
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'suggested_take_profit_1': take_profit_1,
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'suggested_take_profit_2': take_profit_2,
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'suggested_position_percent': suggested_position_pct,
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'suggested_leverage': config.TRADING_CONFIG.get('LEVERAGE', 10),
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'volume_24h': symbol_info.get('volume24h'),
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'volatility': symbol_info.get('volatility'),
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'order_type': 'LIMIT', # 使用限价单
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'suggested_limit_price': suggested_limit_price # 建议的挂单价
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}
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# 不再自动保存到数据库，只返回推荐数据
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# 只有用户在前端点击"标记"时才会保存到数据库（用于复盘）
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logger.debug(
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f"✓ 生成推荐: {symbol} {direction} "
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f"(信号强度: {signal_strength}/10)"
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)
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return recommendation_data
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except Exception as e:
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logger.error(f"创建推荐失败 {symbol_info.get('symbol', 'unknown')}: {e}")
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return None
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async def get_active_recommendations(self) -> List[Dict]:
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"""获取当前有效的推荐"""
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if DB_AVAILABLE and TradeRecommendation:
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return TradeRecommendation.get_active()
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return []
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async def mark_recommendation_executed(self, recommendation_id: int, trade_id: int = None):
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"""标记推荐已执行"""
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if DB_AVAILABLE and TradeRecommendation:
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TradeRecommendation.mark_executed(recommendation_id, trade_id)
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logger.info(f"推荐 {recommendation_id} 已标记为已执行")
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