stock/stock-html/services/score_engine.py

"""
综合评分引擎 — 整合所有影响因素到统一评分体系

将技术面（基础50%+）与外部因素（加减分项）整合为最终评分。

权重分配：
- 技术面评分（compute_deep_analysis 原始分）：基础分（0-100）
- P0 资金面：±20
- P1 市场情绪：±10
- P2 北向资金：±10
- P3 美股外盘：±10
- P4 大宗商品：±5
- P5 公告/异动：±15
- P6 政策面：±10
- P7 汇率：±3

最终评分 = 技术面基础分 + 外部因素加减分（上限100，下限0）
"""
import logging

logger = logging.getLogger(__name__)


def compute_comprehensive_score(stock_code, stock_name, technical_score, df=None):
    """
    综合评分引擎 — 整合技术面和所有外部因素

    参数:
        stock_code: 股票代码
        stock_name: 股票名称
        technical_score: float — 技术面基础评分（0-100，来自 compute_deep_analysis）
        df: K线DataFrame（用于异动检测，可选）

    返回:
        dict: {
            'technical_score': float,    # 技术面基础分
            'external_score': int,       # 外部因素总加减分
            'final_score': int,          # 最终综合评分（0-100）
            'verdict': str,              # 最终评级
            'factors': dict,             # 各因素详细数据
            'all_reasons': list,         # 所有评分原因
            'summary': str,              # 综合白话总结
        }
    """
    factors = {}
    all_reasons = []
    external_score = 0
    summaries = []

    # ---- P0: 主力资金进出 ----
    try:
        from services.fund_flow_analyzer import analyze_fund_flow
        fund_result = analyze_fund_flow(stock_code, days=5)
        factors['fund_flow'] = fund_result
        external_score += fund_result.get('score', 0)
        all_reasons.extend(fund_result.get('reasons', []))
        s = fund_result.get('summary', '')
        if s and '暂无' not in s:
            summaries.append(f'资金面：{s}')
    except Exception as e:
        logger.warning(f"P0资金面分析失败: {e}")
        factors['fund_flow'] = {'score': 0, 'summary': '分析失败', 'reasons': []}

    # ---- P1: 市场情绪指标 ----
    try:
        from services.market_sentiment import calc_market_sentiment
        sentiment_result = calc_market_sentiment()
        factors['market_sentiment'] = sentiment_result
        external_score += sentiment_result.get('score', 0)
        all_reasons.extend(sentiment_result.get('reasons', []))
        s = sentiment_result.get('sentiment', '')
        if s and '无数据' not in s:
            summaries.append(f'市场情绪：{s}（涨跌停{sentiment_result.get("limit_up_count",0)}:{sentiment_result.get("limit_down_count",0)}）')
    except Exception as e:
        logger.warning(f"P1市场情绪分析失败: {e}")
        factors['market_sentiment'] = {'score': 0, 'summary': '分析失败', 'reasons': []}

    # ---- P2/P3/P4/P7: 外部因素（北向/美股/商品/汇率）----
    try:
        from services.external_factors import get_all_external_factors
        ext_result = get_all_external_factors()
        factors['external'] = ext_result
        external_score += ext_result.get('total_score', 0)
        all_reasons.extend(ext_result.get('all_reasons', []))
        s = ext_result.get('summary', '')
        if s:
            summaries.append(s)
    except Exception as e:
        logger.warning(f"P2-P7外部因素分析失败: {e}")
        factors['external'] = {'total_score': 0, 'summary': '分析失败', 'all_reasons': []}

    # ---- P5/P6: 公告/异动/政策 ----
    try:
        from services.news_analyzer import analyze_news_factors
        news_result = analyze_news_factors(stock_code, stock_name, df)
        factors['news'] = news_result
        external_score += news_result.get('total_score', 0)
        all_reasons.extend(news_result.get('all_reasons', []))
        s = news_result.get('summary', '')
        if s:
            summaries.append(s)
    except Exception as e:
        logger.warning(f"P5/P6消息面分析失败: {e}")
        factors['news'] = {'total_score': 0, 'summary': '分析失败', 'all_reasons': []}

    # ---- 最终评分 ----
    # 外部因素加减分上限：±40（避免喧宾夺主）
    external_score = max(-40, min(40, external_score))
    final_score = max(0, min(100, int(technical_score + external_score)))

    # 最终评级
    if final_score >= 80:
        verdict = '强烈看多'
    elif final_score >= 65:
        verdict = '看多'
    elif final_score >= 50:
        verdict = '中性偏多'
    elif final_score >= 35:
        verdict = '中性偏空'
    else:
        verdict = '看空'

    # 综合总结
    summary = ' | '.join(summaries) if summaries else '暂无外部因素数据'

    return {
        'technical_score': round(technical_score, 0),
        'external_score': external_score,
        'final_score': final_score,
        'verdict': verdict,
        'factors': factors,
        'all_reasons': all_reasons,
        'summary': summary,
    }