feat: 新增外部因素分析模块+综合评分引擎+算法文档重构

新增模块:
- fund_flow_analyzer.py: 主力资金流向分析(P0, ±20)
- market_sentiment.py: 市场情绪指标(P1, ±10)
- external_factors.py: 北向资金/美股/大宗商品/汇率(P2-P4,P7)
- news_analyzer.py: 公告/并购/政策面LLM分析(P5-P6)
- score_engine.py: 综合评分引擎,整合技术面+外部因素

路由更新:
- analysis.py: deep_analyze接入综合评分,根据最终评级修正买卖建议
- market.py: 新增4个外部因素API端点
- trades.py: 交易路由更新

算法文档重构:
- 章节重排: 技术面(二三)→外部因素(四)→买卖决策(五)→数据源(六)→性能(七)
- 架构图更新为五层,标注章节对应
- 5.1/5.2标注纯技术面,5.3整合外部因素修正推荐
This commit is contained in:
selfrelease
2026-07-17 23:50:42 +08:00
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"""
主力资金流向分析模块(P0
功能:
1. 从数据库读取近N日资金流向数据
2. 计算主力连续净流入/流出天数、累计净流入额
3. 检测量价背离(资金流入+价格不涨 → 吸筹;资金流出+价格不跌 → 出货)
4. 返回资金面评分和信号列表
数据来源:stock_fund_flow_history 表(由 sync_fund_flow.py 每日同步)
"""
import logging
from datetime import datetime, timedelta
logger = logging.getLogger(__name__)
def get_fund_flow_history(stock_code, days=10):
"""
从数据库读取近N日资金流向历史数据
参数:
stock_code: 股票代码
days: 获取天数
返回:
list[dict]: 每日资金流向记录,按日期升序排列
"""
from db import get_db, put_db
conn = get_db()
if not conn:
return []
try:
cur = conn.cursor()
start_date = (datetime.now() - timedelta(days=days + 5)).strftime('%Y-%m-%d')
cur.execute("""
SELECT trade_date, close_price, change_pct,
main_net_inflow, main_net_inflow_pct,
super_net_inflow, super_net_inflow_pct,
big_net_inflow, big_net_inflow_pct,
mid_net_inflow, mid_net_inflow_pct,
small_net_inflow, small_net_inflow_pct
FROM stock_fund_flow_history
WHERE code = %s AND trade_date >= %s
ORDER BY trade_date ASC
""", (stock_code, start_date))
rows = cur.fetchall()
records = []
for row in rows:
records.append({
'date': row[0].strftime('%Y-%m-%d') if row[0] else '',
'close_price': float(row[1] or 0),
'change_pct': float(row[2] or 0),
'main_net_inflow': float(row[3] or 0),
'main_net_inflow_pct': float(row[4] or 0),
'super_net_inflow': float(row[5] or 0),
'super_net_inflow_pct': float(row[6] or 0),
'big_net_inflow': float(row[7] or 0),
'big_net_inflow_pct': float(row[8] or 0),
'mid_net_inflow': float(row[9] or 0),
'mid_net_inflow_pct': float(row[10] or 0),
'small_net_inflow': float(row[11] or 0),
'small_net_inflow_pct': float(row[12] or 0),
})
return records
except Exception as e:
logger.error(f"获取资金流向历史失败({stock_code}): {e}")
return []
finally:
put_db(conn)
def analyze_fund_flow(stock_code, days=5):
"""
分析主力资金流向,返回资金面评分和信号
参数:
stock_code: 股票代码
days: 分析最近几天的资金流向
返回:
dict: {
'score': int, # 资金面评分增减(-20 ~ +20)
'signals': list, # 资金信号列表
'summary': str, # 白话总结
'details': dict, # 详细数据
'reasons': list, # 评分原因列表
}
"""
records = get_fund_flow_history(stock_code, days=days + 5)
if len(records) < 2:
return {
'score': 0,
'signals': [],
'summary': '暂无资金流向数据',
'details': {},
'reasons': [],
}
recent = records[-days:] if len(records) >= days else records
# 计算连续净流入/流出天数
consecutive_inflow = 0
consecutive_outflow = 0
for r in reversed(recent):
if r['main_net_inflow'] > 0:
if consecutive_outflow > 0:
break
consecutive_inflow += 1
elif r['main_net_inflow'] < 0:
if consecutive_inflow > 0:
break
consecutive_outflow += 1
# 累计净流入
total_main_inflow = sum(r['main_net_inflow'] for r in recent)
avg_main_pct = sum(r['main_net_inflow_pct'] for r in recent) / len(recent) if recent else 0
# 超大单累计
total_super_inflow = sum(r['super_net_inflow'] for r in recent)
avg_super_pct = sum(r['super_net_inflow_pct'] for r in recent) / len(recent) if recent else 0
# 量价背离检测
# 吸筹:主力净流入但价格不涨(涨幅<2%)
# 出货:主力净流出但价格不跌(跌幅<2%)
accumulation = False
distribution = False
if total_main_inflow > 0:
price_changes = [r['change_pct'] for r in recent]
avg_price_change = sum(price_changes) / len(price_changes) if price_changes else 0
if avg_price_change < 2:
accumulation = True
if total_main_inflow < 0:
price_changes = [r['change_pct'] for r in recent]
avg_price_change = sum(price_changes) / len(price_changes) if price_changes else 0
if avg_price_change > -2:
distribution = True
# 单日超大单突击
big_surge = False
big_surge_day = None
for r in recent:
if r['super_net_inflow_pct'] > 15:
big_surge = True
big_surge_day = r['date']
break
# 评分计算
score = 0
reasons = []
signals = []
if consecutive_inflow >= 3:
score += 10
reasons.append(f'主力连续{consecutive_inflow}日净流入(+10)')
signals.append({
'type': 'fund_continuous_inflow',
'name': '主力持续流入',
'direction': 'buy',
'strength': 80,
'description': f'主力资金连续{consecutive_inflow}日净流入,累计{total_main_inflow/10000:.0f}万元',
})
if consecutive_outflow >= 3:
score -= 10
reasons.append(f'主力连续{consecutive_outflow}日净流出(-10)')
signals.append({
'type': 'fund_continuous_outflow',
'name': '主力持续流出',
'direction': 'sell',
'strength': 75,
'description': f'主力资金连续{consecutive_outflow}日净流出,累计{total_main_inflow/10000:.0f}万元',
})
if accumulation:
score += 8
reasons.append('主力暗中吸筹(+8)')
signals.append({
'type': 'fund_accumulation',
'name': '主力吸筹',
'direction': 'buy',
'strength': 85,
'description': f'主力净流入但价格未涨,暗中吸筹,可能即将拉升',
})
if distribution:
score -= 8
reasons.append('主力暗中出货(-8)')
signals.append({
'type': 'fund_distribution',
'name': '主力出货',
'direction': 'sell',
'strength': 80,
'description': f'主力净流出但价格未跌,暗中出货,需警惕',
})
if big_surge:
score += 5
reasons.append(f'超大单突击流入({big_surge_day})(+5)')
signals.append({
'type': 'fund_big_surge',
'name': '大单突击',
'direction': 'buy',
'strength': 70,
'description': f'{big_surge_day}超大单净流入占比>15%,大机构突击入场',
})
# 主力净流入占比评分
if avg_main_pct > 10:
score += 5
reasons.append(f'主力净流入占比{avg_main_pct:.1f}%(+5)')
elif avg_main_pct < -10:
score -= 5
reasons.append(f'主力净流出占比{abs(avg_main_pct):.1f}%(-5)')
score = max(-20, min(20, score))
# 白话总结
summary_parts = []
if consecutive_inflow >= 3:
summary_parts.append(f'{consecutive_inflow}天主力持续买入,累计流入{total_main_inflow/10000:.0f}万元')
elif consecutive_outflow >= 3:
summary_parts.append(f'{consecutive_outflow}天主力持续卖出,累计流出{abs(total_main_inflow)/10000:.0f}万元')
elif total_main_inflow > 0:
summary_parts.append(f'近期主力总体净流入{total_main_inflow/10000:.0f}万元')
elif total_main_inflow < 0:
summary_parts.append(f'近期主力总体净流出{abs(total_main_inflow)/10000:.0f}万元')
if accumulation:
summary_parts.append('但价格没怎么涨,像是在暗中吸筹')
if distribution:
summary_parts.append('但价格没怎么跌,像是在暗中出货,要小心')
summary = ''.join(summary_parts) if summary_parts else '资金面无明显方向'
return {
'score': score,
'signals': signals,
'summary': summary,
'details': {
'consecutive_inflow': consecutive_inflow,
'consecutive_outflow': consecutive_outflow,
'total_main_inflow': round(total_main_inflow, 2),
'avg_main_pct': round(avg_main_pct, 2),
'total_super_inflow': round(total_super_inflow, 2),
'avg_super_pct': round(avg_super_pct, 2),
'accumulation': accumulation,
'distribution': distribution,
'recent_days': len(recent),
'daily_data': recent,
},
'reasons': reasons,
}