selfrelease
2b5a32ca1e
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
258 lines
8.9 KiB
Python
258 lines
8.9 KiB
Python
"""
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主力资金流向分析模块（P0）
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功能：
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1. 从数据库读取近N日资金流向数据
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2. 计算主力连续净流入/流出天数、累计净流入额
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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）
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4. 返回资金面评分和信号列表
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数据来源：stock_fund_flow_history 表（由 sync_fund_flow.py 每日同步）
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"""
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import logging
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from datetime import datetime, timedelta
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logger = logging.getLogger(__name__)
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def get_fund_flow_history(stock_code, days=10):
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"""
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从数据库读取近N日资金流向历史数据
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参数:
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stock_code: 股票代码
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days: 获取天数
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返回:
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list[dict]: 每日资金流向记录，按日期升序排列
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"""
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from db import get_db, put_db
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conn = get_db()
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if not conn:
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return []
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try:
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cur = conn.cursor()
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start_date = (datetime.now() - timedelta(days=days + 5)).strftime('%Y-%m-%d')
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cur.execute("""
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SELECT trade_date, close_price, change_pct,
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main_net_inflow, main_net_inflow_pct,
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super_net_inflow, super_net_inflow_pct,
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big_net_inflow, big_net_inflow_pct,
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mid_net_inflow, mid_net_inflow_pct,
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small_net_inflow, small_net_inflow_pct
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FROM stock_fund_flow_history
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WHERE code = %s AND trade_date >= %s
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ORDER BY trade_date ASC
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""", (stock_code, start_date))
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rows = cur.fetchall()
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records = []
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for row in rows:
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records.append({
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'date': row[0].strftime('%Y-%m-%d') if row[0] else '',
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'close_price': float(row[1] or 0),
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'change_pct': float(row[2] or 0),
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'main_net_inflow': float(row[3] or 0),
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'main_net_inflow_pct': float(row[4] or 0),
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'super_net_inflow': float(row[5] or 0),
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'super_net_inflow_pct': float(row[6] or 0),
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'big_net_inflow': float(row[7] or 0),
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'big_net_inflow_pct': float(row[8] or 0),
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'mid_net_inflow': float(row[9] or 0),
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'mid_net_inflow_pct': float(row[10] or 0),
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'small_net_inflow': float(row[11] or 0),
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'small_net_inflow_pct': float(row[12] or 0),
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})
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return records
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except Exception as e:
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logger.error(f"获取资金流向历史失败({stock_code}): {e}")
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return []
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finally:
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put_db(conn)
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def analyze_fund_flow(stock_code, days=5):
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"""
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分析主力资金流向，返回资金面评分和信号
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参数:
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stock_code: 股票代码
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days: 分析最近几天的资金流向
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返回:
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dict: {
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'score': int, # 资金面评分增减（-20 ~ +20）
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'signals': list, # 资金信号列表
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'summary': str, # 白话总结
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'details': dict, # 详细数据
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'reasons': list, # 评分原因列表
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}
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"""
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records = get_fund_flow_history(stock_code, days=days + 5)
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if len(records) < 2:
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return {
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'score': 0,
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'signals': [],
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'summary': '暂无资金流向数据',
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'details': {},
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'reasons': [],
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}
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recent = records[-days:] if len(records) >= days else records
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# 计算连续净流入/流出天数
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consecutive_inflow = 0
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consecutive_outflow = 0
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for r in reversed(recent):
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if r['main_net_inflow'] > 0:
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if consecutive_outflow > 0:
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break
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consecutive_inflow += 1
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elif r['main_net_inflow'] < 0:
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if consecutive_inflow > 0:
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break
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consecutive_outflow += 1
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# 累计净流入
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total_main_inflow = sum(r['main_net_inflow'] for r in recent)
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avg_main_pct = sum(r['main_net_inflow_pct'] for r in recent) / len(recent) if recent else 0
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# 超大单累计
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total_super_inflow = sum(r['super_net_inflow'] for r in recent)
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avg_super_pct = sum(r['super_net_inflow_pct'] for r in recent) / len(recent) if recent else 0
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# 量价背离检测
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# 吸筹：主力净流入但价格不涨（涨幅<2%）
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# 出货：主力净流出但价格不跌（跌幅<2%）
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accumulation = False
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distribution = False
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if total_main_inflow > 0:
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price_changes = [r['change_pct'] for r in recent]
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avg_price_change = sum(price_changes) / len(price_changes) if price_changes else 0
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if avg_price_change < 2:
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accumulation = True
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if total_main_inflow < 0:
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price_changes = [r['change_pct'] for r in recent]
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avg_price_change = sum(price_changes) / len(price_changes) if price_changes else 0
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if avg_price_change > -2:
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distribution = True
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# 单日超大单突击
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big_surge = False
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big_surge_day = None
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for r in recent:
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if r['super_net_inflow_pct'] > 15:
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big_surge = True
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big_surge_day = r['date']
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break
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# 评分计算
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score = 0
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reasons = []
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signals = []
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if consecutive_inflow >= 3:
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score += 10
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reasons.append(f'主力连续{consecutive_inflow}日净流入(+10)')
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signals.append({
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'type': 'fund_continuous_inflow',
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'name': '主力持续流入',
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'direction': 'buy',
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'strength': 80,
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'description': f'主力资金连续{consecutive_inflow}日净流入，累计{total_main_inflow/10000:.0f}万元',
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})
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if consecutive_outflow >= 3:
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score -= 10
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reasons.append(f'主力连续{consecutive_outflow}日净流出(-10)')
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signals.append({
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'type': 'fund_continuous_outflow',
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'name': '主力持续流出',
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'direction': 'sell',
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'strength': 75,
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'description': f'主力资金连续{consecutive_outflow}日净流出，累计{total_main_inflow/10000:.0f}万元',
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})
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if accumulation:
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score += 8
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reasons.append('主力暗中吸筹(+8)')
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signals.append({
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'type': 'fund_accumulation',
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'name': '主力吸筹',
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'direction': 'buy',
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'strength': 85,
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'description': f'主力净流入但价格未涨，暗中吸筹，可能即将拉升',
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})
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if distribution:
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score -= 8
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reasons.append('主力暗中出货(-8)')
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signals.append({
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'type': 'fund_distribution',
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'name': '主力出货',
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'direction': 'sell',
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'strength': 80,
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'description': f'主力净流出但价格未跌，暗中出货，需警惕',
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})
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if big_surge:
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score += 5
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reasons.append(f'超大单突击流入({big_surge_day})(+5)')
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signals.append({
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'type': 'fund_big_surge',
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'name': '大单突击',
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'direction': 'buy',
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'strength': 70,
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'description': f'{big_surge_day}超大单净流入占比>15%，大机构突击入场',
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})
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# 主力净流入占比评分
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if avg_main_pct > 10:
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score += 5
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reasons.append(f'主力净流入占比{avg_main_pct:.1f}%(+5)')
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elif avg_main_pct < -10:
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score -= 5
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reasons.append(f'主力净流出占比{abs(avg_main_pct):.1f}%(-5)')
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score = max(-20, min(20, score))
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# 白话总结
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summary_parts = []
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if consecutive_inflow >= 3:
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summary_parts.append(f'近{consecutive_inflow}天主力持续买入，累计流入{total_main_inflow/10000:.0f}万元')
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elif consecutive_outflow >= 3:
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summary_parts.append(f'近{consecutive_outflow}天主力持续卖出，累计流出{abs(total_main_inflow)/10000:.0f}万元')
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elif total_main_inflow > 0:
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summary_parts.append(f'近期主力总体净流入{total_main_inflow/10000:.0f}万元')
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elif total_main_inflow < 0:
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summary_parts.append(f'近期主力总体净流出{abs(total_main_inflow)/10000:.0f}万元')
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if accumulation:
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summary_parts.append('但价格没怎么涨，像是在暗中吸筹')
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if distribution:
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summary_parts.append('但价格没怎么跌，像是在暗中出货，要小心')
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summary = '，'.join(summary_parts) if summary_parts else '资金面无明显方向'
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return {
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'score': score,
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'signals': signals,
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'summary': summary,
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'details': {
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'consecutive_inflow': consecutive_inflow,
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'consecutive_outflow': consecutive_outflow,
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'total_main_inflow': round(total_main_inflow, 2),
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'avg_main_pct': round(avg_main_pct, 2),
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'total_super_inflow': round(total_super_inflow, 2),
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'avg_super_pct': round(avg_super_pct, 2),
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'accumulation': accumulation,
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'distribution': distribution,
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'recent_days': len(recent),
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'daily_data': recent,
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},
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'reasons': reasons,
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}
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