341 lines
11 KiB
Python
341 lines
11 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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技术分析服务模块
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处理趋势分析、共振分析、交易建议生成等业务逻辑
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"""
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from datetime import datetime
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from typing import Dict, List, Optional
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from ..models import KlineData, TechTrendState, TechTrendChange, TechResonanceResult, TechTradeSuggestion
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from ..store import TechStore, KlineStore, PivotStore
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from .tech_indicators import calculate_ma, calculate_adx
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class TechService:
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"""技术分析服务（处理业务逻辑）"""
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# 支持的周期
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PERIODS = ['H4', 'H1', 'M15', 'M5', 'M1']
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# ADX 阈值
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ADX_TREND_THRESHOLD = 25
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ADX_STRONG_THRESHOLD = 40
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# 均线周期
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MA_FAST = 10
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MA_SLOW = 20
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# 最小 K 线数量
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MIN_KLINES = 30
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def __init__(self, tech_store: TechStore, kline_store: KlineStore, pivot_store: PivotStore):
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self.tech_store = tech_store
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self.kline_store = kline_store
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self.pivot_store = pivot_store
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# 统计服务引用（用于获取价差）
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self._statistics_service = None
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print("[TechService] 技术分析服务已初始化")
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def set_statistics_service(self, statistics_service):
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"""设置统计服务引用"""
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self._statistics_service = statistics_service
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def _get_symbol_spread(self, symbol: str) -> Optional[float]:
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"""获取品种价差"""
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if not self._statistics_service:
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return None
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return self._statistics_service.get_spread(symbol)
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# ==================== 趋势分析 ====================
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def analyze_trend(self, symbol: str, period: str) -> Dict:
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"""
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分析单个周期的趋势
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Args:
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symbol: 交易品种
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period: 周期
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Returns:
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趋势状态字典
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"""
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period = period.upper()
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# 从 store 获取 K 线数据
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klines_dict = self.kline_store.get_all_klines(symbol, period)
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if not klines_dict:
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return self._create_unknown_state(symbol, period, "无K线数据")
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# 转换为 KlineData 对象
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klines = [
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KlineData(
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symbol=k.get('symbol', symbol),
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period=k.get('period', period),
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timestamp=k.get('timestamp'),
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open_price=float(k.get('open', 0)),
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high=float(k.get('high', 0)),
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low=float(k.get('low', 0)),
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close=float(k.get('close', 0)),
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volume=float(k.get('volume', 0))
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)
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for k in klines_dict
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]
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if len(klines) < self.MIN_KLINES:
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return self._create_unknown_state(symbol, period, f"K线数据不足(需≥{self.MIN_KLINES}根)")
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# 计算技术指标
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closes = [k.close for k in klines]
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ma_fast = calculate_ma(closes, self.MA_FAST)
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ma_slow = calculate_ma(closes, self.MA_SLOW)
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current_price = closes[-1]
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adx = calculate_adx(klines)
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# 判断趋势
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trend, reason = self._determine_trend(adx, ma_fast, ma_slow, current_price)
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# 计算强度
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strength = self._calculate_strength(adx)
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# 获取之前的状态
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previous_state = self.tech_store.get_trend_state_object(symbol, period)
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previous_trend = previous_state.trend if previous_state else None
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change_signal = previous_trend and previous_trend != "unknown" and previous_trend != trend
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# 创建状态对象
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state = TechTrendState(
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symbol=symbol,
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period=period,
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trend=trend,
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strength=strength,
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adx=round(adx, 2),
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ma_fast=round(ma_fast, 4),
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ma_slow=round(ma_slow, 4),
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price=current_price,
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reason=reason,
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timestamp=datetime.now().isoformat(),
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previous_trend=previous_trend,
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change_signal=change_signal
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)
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# 保存状态
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self.tech_store.save_trend_state(state)
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# 记录趋势转换
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if change_signal:
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change = TechTrendChange(
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period=period,
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from_trend=previous_trend,
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to_trend=trend,
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price=current_price,
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timestamp=datetime.now().isoformat()
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)
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self.tech_store.add_trend_change(symbol, change)
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return state.to_dict()
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def _create_unknown_state(self, symbol: str, period: str, reason: str) -> Dict:
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"""创建未知状态"""
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state = TechTrendState(
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symbol=symbol,
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period=period,
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trend="unknown",
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reason=reason,
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timestamp=datetime.now().isoformat()
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)
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return state.to_dict()
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def _determine_trend(self, adx: float, ma_fast: float, ma_slow: float, price: float) -> tuple:
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"""判断趋势方向"""
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reason_parts = []
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if adx < self.ADX_TREND_THRESHOLD:
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trend = "sideways"
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reason_parts.append(f"ADX={adx:.1f}<25 无明显趋势")
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else:
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if ma_fast > ma_slow and price > ma_fast:
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trend = "up"
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reason_parts.append(f"MA{self.MA_FAST}({ma_fast:.2f}) > MA{self.MA_SLOW}({ma_slow:.2f})")
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reason_parts.append(f"价格({price:.2f}) > MA{self.MA_FAST}")
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reason_parts.append(f"ADX={adx:.1f}≥25 确认趋势")
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elif ma_fast < ma_slow and price < ma_fast:
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trend = "down"
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reason_parts.append(f"MA{self.MA_FAST}({ma_fast:.2f}) < MA{self.MA_SLOW}({ma_slow:.2f})")
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reason_parts.append(f"价格({price:.2f}) < MA{self.MA_FAST}")
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reason_parts.append(f"ADX={adx:.1f}≥25 确认趋势")
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else:
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trend = "sideways"
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if ma_fast > ma_slow:
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reason_parts.append(f"MA{self.MA_FAST}({ma_fast:.2f}) > MA{self.MA_SLOW}({ma_slow:.2f})")
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reason_parts.append(f"但价格({price:.2f})低于MA{self.MA_FAST}")
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else:
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reason_parts.append(f"MA{self.MA_FAST}({ma_fast:.2f}) < MA{self.MA_SLOW}({ma_slow:.2f})")
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reason_parts.append(f"且价格({price:.2f})高于MA{self.MA_FAST}")
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reason_parts.append("信号矛盾，判定震荡")
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return trend, "；".join(reason_parts)
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def _calculate_strength(self, adx: float) -> int:
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"""计算趋势强度"""
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if adx >= self.ADX_STRONG_THRESHOLD:
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return min(100, int(adx + 20))
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elif adx >= self.ADX_TREND_THRESHOLD:
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return int(adx + 10)
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else:
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return int(adx)
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# ==================== 共振分析 ====================
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def analyze_resonance(self, symbol: str) -> Dict:
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"""
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分析多周期共振
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Args:
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symbol: 交易品种
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Returns:
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共振分析结果
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"""
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states = self.tech_store.get_all_trend_states(symbol)
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if not states:
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result = TechResonanceResult(symbol=symbol)
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return result.to_dict()
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# 统计各趋势数量
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up_count = sum(1 for s in states.values() if s.trend == 'up')
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down_count = sum(1 for s in states.values() if s.trend == 'down')
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sideways_count = sum(1 for s in states.values() if s.trend == 'sideways')
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# 计算平均强度
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strengths = [s.strength for s in states.values() if s.trend != 'sideways']
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avg_strength = sum(strengths) / len(strengths) if strengths else 0
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# 判断共振
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total = len(states)
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if up_count >= total * 0.6:
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resonance = "up"
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aligned_count = up_count
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signal = f"多周期向上共振 ({up_count}/{total})"
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elif down_count >= total * 0.6:
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resonance = "down"
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aligned_count = down_count
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signal = f"多周期向下共振 ({down_count}/{total})"
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else:
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resonance = "none"
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aligned_count = max(up_count, down_count)
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signal = f"趋势分歧 (↑{up_count} ↓{down_count} →{sideways_count})"
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result = TechResonanceResult(
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symbol=symbol,
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resonance=resonance,
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strength=int(avg_strength),
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aligned_count=aligned_count,
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up_count=up_count,
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down_count=down_count,
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sideways_count=sideways_count,
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signal=signal,
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periods={p: s.to_dict() for p, s in states.items()}
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)
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return result.to_dict()
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# ==================== 交易建议 ====================
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def generate_trade_suggestion(self, symbol: str, current_price: float) -> Optional[Dict]:
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"""
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基于趋势和转折点生成交易建议
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Args:
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symbol: 交易品种
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current_price: 当前实时价格
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Returns:
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交易建议 或 None
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"""
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# 获取共振分析
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resonance = self.analyze_resonance(symbol)
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if resonance['resonance'] == 'none':
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return None
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if resonance['strength'] < 30:
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return None
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trend = resonance['resonance']
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# 从 pivot_store 获取转折点
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pivots = self.pivot_store.get_pivot_objects(symbol)
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if not pivots:
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return None
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# 按时间排序
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recent_pivots = sorted(
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[p.to_dict() for p in pivots],
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key=lambda x: str(x.get('timestamp', '')),
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reverse=True
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)[:10]
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sl = None
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tp = None
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action = None
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reason = ""
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if trend == "up":
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action = "b"
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low_pivots = [p for p in recent_pivots if p.get('direction') == 'low']
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if low_pivots:
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sl = low_pivots[0].get('price')
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if sl and current_price > sl:
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distance = current_price - sl
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tp = current_price + distance * 1.5
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reason = f"多周期向上共振，建议买入，止损参考最近低点 {sl}"
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else:
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return None
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elif trend == "down":
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action = "s"
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high_pivots = [p for p in recent_pivots if p.get('direction') == 'high']
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if high_pivots:
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sl = high_pivots[0].get('price')
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if sl and current_price < sl:
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distance = sl - current_price
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tp = current_price - distance * 1.5
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reason = f"多周期向下共振，建议卖出，止损参考最近高点 {sl}"
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else:
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return None
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if not all([action, sl, tp]):
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return None
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suggestion = TechTradeSuggestion(
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symbol=symbol,
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action=action,
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price=current_price,
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sl=round(sl, 4),
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tp=round(tp, 4),
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reason=reason,
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trend_strength=resonance['strength'],
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resonance_periods=resonance['aligned_count'],
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generated_at=datetime.now().isoformat()
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)
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return suggestion.to_dict()
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# ==================== 查询 ====================
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def get_trend_state(self, symbol: str, period: str = None) -> Dict:
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"""获取趋势状态"""
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return self.tech_store.get_trend_state(symbol, period)
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def get_trend_changes(self, symbol: str, count: int = 10) -> List[Dict]:
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"""获取趋势转换历史"""
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return self.tech_store.get_trend_changes(symbol, count)
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def get_status(self) -> Dict:
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"""获取状态"""
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return self.tech_store.get_status()
|