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
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selfrelease
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"""
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市场情绪指标模块（P1）
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从 stock_realtime_price 表直接计算市场情绪指标，无需额外数据源。
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指标包括：
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1. 涨停/跌停家数比
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2. 连板高度（最高连板数）
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3. 换手率中位数
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4. 两市成交额
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"""
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import logging
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logger = logging.getLogger(__name__)
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def calc_market_sentiment():
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"""
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从数据库实时行情表计算市场情绪指标
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返回:
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dict: {
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'limit_up_count': int, # 涨停家数
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'limit_down_count': int, # 跌停家数
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'up_down_ratio': float, # 涨跌停比
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'sentiment': str, # 情绪标签
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'consecutive_board': int, # 最高连板数
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'turnover_median': float, # 换手率中位数
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'total_amount': float, # 两市成交额（亿）
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'market_temp': str, # 市场温度（偏热/偏冷/正常）
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'score': int, # 情绪评分增减（-10 ~ +10）
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'reasons': list, # 评分原因
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}
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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 _empty_sentiment()
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try:
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cur = conn.cursor()
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# 涨停跌停统计（涨停：涨幅>=9.8%，跌停：跌幅<=-9.8%）
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cur.execute("""
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SELECT
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COUNT(*) FILTER (WHERE change_pct >= 9.8) AS limit_up,
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COUNT(*) FILTER (WHERE change_pct <= -9.8) AS limit_down,
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COUNT(*) FILTER (WHERE change_pct > 0) AS up_count,
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COUNT(*) FILTER (WHERE change_pct < 0) AS down_count,
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COUNT(*) FILTER (WHERE change_pct = 0) AS flat_count,
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COUNT(*) AS total,
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COALESCE(SUM(amount), 0) AS total_amount,
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COALESCE(PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY turnover), 0) AS turnover_median
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FROM stock_realtime_price
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WHERE volume > 0 AND price > 0
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""")
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row = cur.fetchone()
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if not row:
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return _empty_sentiment()
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limit_up = int(row[0] or 0)
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limit_down = int(row[1] or 0)
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up_count = int(row[2] or 0)
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down_count = int(row[3] or 0)
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flat_count = int(row[4] or 0)
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total = int(row[5] or 1)
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total_amount = float(row[6] or 0) / 1e8 # 转为亿
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turnover_median = float(row[7] or 0)
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# 涨跌停比
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up_down_ratio = round(limit_up / limit_down, 1) if limit_down > 0 else float(limit_up)
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# 情绪标签
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if limit_down == 0 and limit_up > 10:
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sentiment = '极度乐观'
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elif up_down_ratio >= 5:
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sentiment = '乐观'
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elif up_down_ratio >= 2:
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sentiment = '偏多'
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elif up_down_ratio >= 1:
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sentiment = '中性'
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elif up_down_ratio >= 0.5:
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sentiment = '偏空'
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else:
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sentiment = '悲观'
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# 市场温度
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if total_amount > 1.2e4:
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market_temp = '偏热'
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elif total_amount < 6000:
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market_temp = '偏冷'
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else:
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market_temp = '正常'
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# 连板高度：查找连续涨停的股票
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consecutive_board = _calc_max_consecutive_board(cur)
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# 评分
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score = 0
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reasons = []
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if up_down_ratio >= 5:
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score += 5
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reasons.append(f'涨跌停比{up_down_ratio}:1，情绪极度乐观(+5)')
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elif up_down_ratio >= 2:
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score += 3
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reasons.append(f'涨跌停比{up_down_ratio}:1，情绪偏多(+3)')
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elif up_down_ratio < 0.5:
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score -= 5
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reasons.append(f'涨跌停比{up_down_ratio}:1，情绪悲观(-5)')
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elif up_down_ratio < 1:
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score -= 3
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reasons.append(f'涨跌停比{up_down_ratio}:1，情绪偏空(-3)')
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if consecutive_board >= 5:
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score += 3
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reasons.append(f'最高{consecutive_board}连板，市场热度高(+3)')
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if total_amount > 1.2e4:
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score += 2
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reasons.append(f'两市成交额{total_amount:.0f}亿，交投活跃(+2)')
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elif total_amount < 6000:
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score -= 2
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reasons.append(f'两市成交额仅{total_amount:.0f}亿，交投清淡(-2)')
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score = max(-10, min(10, score))
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return {
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'limit_up_count': limit_up,
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'limit_down_count': limit_down,
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'up_count': up_count,
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'down_count': down_count,
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'up_down_ratio': up_down_ratio,
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'sentiment': sentiment,
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'consecutive_board': consecutive_board,
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'turnover_median': round(turnover_median, 2),
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'total_amount': round(total_amount, 0),
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'market_temp': market_temp,
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'score': score,
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'reasons': reasons,
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}
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except Exception as e:
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logger.error(f"计算市场情绪指标失败: {e}")
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return _empty_sentiment()
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finally:
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put_db(conn)
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def _calc_max_consecutive_board(cur):
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"""
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计算最高连板数（需要历史数据辅助判断）
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简化版：通过查找连续涨幅>=9.8%的股票
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由于实时表只有当日数据，这里用近似方法：
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查找涨停股票数量作为市场热度参考
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"""
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try:
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# 查找涨停股票（涨幅>=9.8%）
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cur.execute("""
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SELECT COUNT(*) FROM stock_realtime_price
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WHERE change_pct >= 9.8 AND volume > 0
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""")
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limit_up_count = int(cur.fetchone()[0] or 0)
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# 简化：涨停家数>50视为有高连板可能
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if limit_up_count > 50:
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return 5
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elif limit_up_count > 30:
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return 4
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elif limit_up_count > 15:
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return 3
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elif limit_up_count > 5:
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return 2
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elif limit_up_count > 0:
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return 1
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return 0
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except Exception:
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return 0
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def _empty_sentiment():
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"""返回空情绪数据"""
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return {
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'limit_up_count': 0,
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'limit_down_count': 0,
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'up_count': 0,
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'down_count': 0,
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'up_down_ratio': 0,
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'sentiment': '无数据',
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'consecutive_board': 0,
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'turnover_median': 0,
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'total_amount': 0,
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'market_temp': '无数据',
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'score': 0,
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'reasons': [],
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}
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