claude强化功能

backend/financial_analysis.py

@@ -0,0 +1,495 @@
+"""财报深度解读 — 关键指标趋势、AI摘要、同行对比、异常预警。
+
+功能：
+1. 财报关键指标趋势
+2. AI财报摘要
+3. 同行对比
+4. 财报异常预警
+5. 财报发布日历
+"""
+import datetime as dt
+import json
+from typing import List, Dict, Any, Optional
+from collections import defaultdict
+import numpy as np
+from sqlalchemy import select, and_, func, desc
+
+from db import get_session
+from models import FinancialReport, Security, StockMetric
+import llm
+
+
+def seed_sample_reports():
+    """生成示例财报数据（用于演示）"""
+    with get_session() as s:
+        stocks = s.execute(
+            select(Security.code, Security.name).limit(50)
+        ).all()
+        
+        saved = 0
+        for code, name in stocks:
+            # 生成最近4个季度的财报
+            base_date = dt.date(2023, 12, 31)
+            
+            for i in range(4):
+                report_date = base_date - dt.timedelta(days=i * 90)
+                publish_date = report_date + dt.timedelta(days=30)
+                
+                # 检查是否已存在
+                exists = s.execute(
+                    select(FinancialReport).where(
+                        and_(
+                            FinancialReport.code == code,
+                            FinancialReport.report_date == report_date
+                        )
+                    )
+                ).scalar_one_or_none()
+                
+                if exists:
+                    continue
+                
+                # 模拟财务数据
+                base_revenue = np.random.uniform(10, 500)
+                growth = np.random.uniform(-20, 50)
+                
+                report = FinancialReport(
+                    code=code,
+                    name=name,
+                    report_date=report_date,
+                    publish_date=publish_date,
+                    report_type='Q' + str((report_date.month // 3) or 4),
+                    revenue=round(base_revenue * (1 + i * 0.1), 2),
+                    net_profit=round(base_revenue * np.random.uniform(0.05, 0.2), 2),
+                    roe=round(np.random.uniform(5, 25), 2),
+                    gross_margin=round(np.random.uniform(20, 60), 2),
+                    revenue_growth=round(growth, 2),
+                    profit_growth=round(growth + np.random.uniform(-10, 10), 2),
+                    inventory=round(base_revenue * np.random.uniform(0.1, 0.3), 2),
+                    receivable=round(base_revenue * np.random.uniform(0.15, 0.4), 2),
+                    debt_ratio=round(np.random.uniform(30, 70), 2)
+                )
+                s.add(report)
+                saved += 1
+        
+        s.commit()
+    
+    return {"ok": True, "saved": saved}
+
+
+def get_report_trend(code: str, periods: int = 8) -> Dict[str, Any]:
+    """获取财报关键指标趋势
+    
+    Args:
+        code: 股票代码
+        periods: 统计期数
+    
+    Returns:
+        趋势数据
+    """
+    with get_session() as s:
+        reports = s.execute(
+            select(FinancialReport)
+            .where(FinancialReport.code == code)
+            .order_by(desc(FinancialReport.report_date))
+            .limit(periods)
+        ).scalars().all()
+        
+        if not reports:
+            return {"ok": False, "msg": "暂无财报数据"}
+        
+        # 反转顺序（从旧到新）
+        reports = list(reversed(reports))
+        
+        # 提取趋势数据
+        dates = [r.report_date.isoformat() for r in reports]
+        
+        trend_data = {
+            "revenue": [r.revenue for r in reports],
+            "net_profit": [r.net_profit for r in reports],
+            "roe": [r.roe for r in reports],
+            "gross_margin": [r.gross_margin for r in reports],
+            "revenue_growth": [r.revenue_growth for r in reports],
+            "profit_growth": [r.profit_growth for r in reports],
+            "debt_ratio": [r.debt_ratio for r in reports]
+        }
+        
+        # 计算趋势（上升/下降/平稳）
+        def calc_trend(values):
+            if len(values) < 2:
+                return "平稳"
+            recent = np.mean(values[-2:])
+            previous = np.mean(values[:2]) if len(values) >= 4 else values[0]
+            change = (recent - previous) / previous if previous != 0 else 0
+            if change > 0.1:
+                return "上升"
+            elif change < -0.1:
+                return "下降"
+            else:
+                return "平稳"
+        
+        trends = {
+            key: calc_trend(values)
+            for key, values in trend_data.items()
+        }
+        
+        return {
+            "ok": True,
+            "code": code,
+            "name": reports[0].name,
+            "dates": dates,
+            "data": trend_data,
+            "trends": trends,
+            "latest": {
+                "revenue": reports[-1].revenue,
+                "net_profit": reports[-1].net_profit,
+                "roe": reports[-1].roe,
+                "gross_margin": reports[-1].gross_margin,
+                "revenue_growth": reports[-1].revenue_growth,
+                "profit_growth": reports[-1].profit_growth
+            }
+        }
+
+
+def generate_ai_summary(code: str) -> Dict[str, Any]:
+    """生成AI财报摘要
+    
+    Args:
+        code: 股票代码
+    
+    Returns:
+        AI摘要
+    """
+    with get_session() as s:
+        # 获取最新财报
+        report = s.execute(
+            select(FinancialReport)
+            .where(FinancialReport.code == code)
+            .order_by(desc(FinancialReport.report_date))
+            .limit(1)
+        ).scalar_one_or_none()
+        
+        if not report:
+            return {"ok": False, "msg": "暂无财报数据"}
+        
+        # 如果已有摘要，直接返回
+        if report.ai_summary:
+            return {
+                "ok": True,
+                "summary": report.ai_summary,
+                "report_date": report.report_date.isoformat()
+            }
+        
+        # 构建提示词
+        prompt = f"""请用一句话总结以下财报数据（40字以内）：
+
+公司：{report.name}（{report.code}）
+报告期：{report.report_date}
+营业收入：{report.revenue}亿元，同比增长{report.revenue_growth:+.1f}%
+净利润：{report.net_profit}亿元，同比增长{report.profit_growth:+.1f}%
+ROE：{report.roe}%
+毛利率：{report.gross_margin}%
+
+要求：
+1. 一句话说明业绩是增长还是下降
+2. 提及最亮眼或最担忧的指标
+3. 给出简短评价（优秀/良好/一般/较差）
+4. 不超过40字
+
+示例：业绩稳步增长，ROE达20%创新高，盈利能力优秀。
+"""
+        
+        # 调用AI
+        if llm.enabled():
+            try:
+                summary = llm.ask(prompt, max_tokens=100)
+                # 保存摘要
+                report.ai_summary = summary
+                s.commit()
+            except Exception as e:
+                summary = f"营收{report.revenue}亿元({report.revenue_growth:+.1f}%)，净利润{report.net_profit}亿元({report.profit_growth:+.1f}%)"
+        else:
+            summary = f"营收{report.revenue}亿元({report.revenue_growth:+.1f}%)，净利润{report.net_profit}亿元({report.profit_growth:+.1f}%)"
+        
+        return {
+            "ok": True,
+            "summary": summary,
+            "report_date": report.report_date.isoformat()
+        }
+
+
+def compare_with_peers(code: str, sector: str = None) -> Dict[str, Any]:
+    """同行对比
+    
+    Args:
+        code: 股票代码
+        sector: 行业（可选）
+    
+    Returns:
+        对比结果
+    """
+    with get_session() as s:
+        # 获取目标股票最新财报
+        target = s.execute(
+            select(FinancialReport)
+            .where(FinancialReport.code == code)
+            .order_by(desc(FinancialReport.report_date))
+            .limit(1)
+        ).scalar_one_or_none()
+        
+        if not target:
+            return {"ok": False, "msg": "暂无财报数据"}
+        
+        # 获取同行业股票（简化：随机选取）
+        peers = s.execute(
+            select(FinancialReport)
+            .where(
+                and_(
+                    FinancialReport.code != code,
+                    FinancialReport.report_date == target.report_date
+                )
+            )
+            .limit(20)
+        ).scalars().all()
+        
+        if not peers:
+            return {"ok": False, "msg": "暂无同行数据"}
+        
+        # 计算行业均值
+        industry_avg = {
+            "roe": np.mean([p.roe for p in peers]),
+            "gross_margin": np.mean([p.gross_margin for p in peers]),
+            "revenue_growth": np.mean([p.revenue_growth for p in peers]),
+            "profit_growth": np.mean([p.profit_growth for p in peers]),
+            "debt_ratio": np.mean([p.debt_ratio for p in peers])
+        }
+        
+        # 计算差异
+        comparison = {
+            "roe": {
+                "value": target.roe,
+                "industry_avg": round(industry_avg["roe"], 2),
+                "diff": round(target.roe - industry_avg["roe"], 2),
+                "better": target.roe > industry_avg["roe"]
+            },
+            "gross_margin": {
+                "value": target.gross_margin,
+                "industry_avg": round(industry_avg["gross_margin"], 2),
+                "diff": round(target.gross_margin - industry_avg["gross_margin"], 2),
+                "better": target.gross_margin > industry_avg["gross_margin"]
+            },
+            "revenue_growth": {
+                "value": target.revenue_growth,
+                "industry_avg": round(industry_avg["revenue_growth"], 2),
+                "diff": round(target.revenue_growth - industry_avg["revenue_growth"], 2),
+                "better": target.revenue_growth > industry_avg["revenue_growth"]
+            },
+            "profit_growth": {
+                "value": target.profit_growth,
+                "industry_avg": round(industry_avg["profit_growth"], 2),
+                "diff": round(target.profit_growth - industry_avg["profit_growth"], 2),
+                "better": target.profit_growth > industry_avg["profit_growth"]
+            },
+            "debt_ratio": {
+                "value": target.debt_ratio,
+                "industry_avg": round(industry_avg["debt_ratio"], 2),
+                "diff": round(target.debt_ratio - industry_avg["debt_ratio"], 2),
+                "better": target.debt_ratio < industry_avg["debt_ratio"]  # 负债率越低越好
+            }
+        }
+        
+        # 综合评分
+        better_count = sum(1 for v in comparison.values() if v["better"])
+        
+        return {
+            "ok": True,
+            "code": code,
+            "name": target.name,
+            "report_date": target.report_date.isoformat(),
+            "comparison": comparison,
+            "better_count": better_count,
+            "total_metrics": len(comparison),
+            "conclusion": "优于行业" if better_count >= 3 else ("持平行业" if better_count == 2 else "弱于行业")
+        }
+
+
+def detect_abnormalities(code: str) -> Dict[str, Any]:
+    """财报异常预警
+    
+    Args:
+        code: 股票代码
+    
+    Returns:
+        异常预警
+    """
+    with get_session() as s:
+        # 获取最近2期财报
+        reports = s.execute(
+            select(FinancialReport)
+            .where(FinancialReport.code == code)
+            .order_by(desc(FinancialReport.report_date))
+            .limit(2)
+        ).scalars().all()
+        
+        if len(reports) < 2:
+            return {"ok": False, "msg": "数据不足"}
+        
+        current, previous = reports[0], reports[1]
+        
+        warnings = []
+        
+        # 1. 存货激增
+        if current.inventory > 0 and previous.inventory > 0:
+            inventory_growth = (current.inventory / previous.inventory - 1) * 100
+            if inventory_growth > 50:
+                warnings.append({
+                    "type": "存货激增",
+                    "severity": "high",
+                    "description": f"存货增长{inventory_growth:.1f}%，可能存在滞销风险",
+                    "current": current.inventory,
+                    "previous": previous.inventory
+                })
+        
+        # 2. 应收账款占比过高
+        receivable_ratio = current.receivable / current.revenue * 100 if current.revenue > 0 else 0
+        if receivable_ratio > 50:
+            warnings.append({
+                "type": "应收账款占比过高",
+                "severity": "medium",
+                "description": f"应收账款占营收{receivable_ratio:.1f}%，回款压力较大",
+                "ratio": round(receivable_ratio, 2)
+            })
+        
+        # 3. 毛利率大幅下降
+        if current.gross_margin > 0 and previous.gross_margin > 0:
+            margin_change = current.gross_margin - previous.gross_margin
+            if margin_change < -5:
+                warnings.append({
+                    "type": "毛利率大幅下降",
+                    "severity": "high",
+                    "description": f"毛利率下降{abs(margin_change):.1f}个百分点，盈利能力恶化",
+                    "current": current.gross_margin,
+                    "previous": previous.gross_margin
+                })
+        
+        # 4. 资产负债率过高
+        if current.debt_ratio > 70:
+            warnings.append({
+                "type": "资产负债率过高",
+                "severity": "medium",
+                "description": f"资产负债率{current.debt_ratio}%，财务风险较高",
+                "value": current.debt_ratio
+            })
+        
+        # 5. 增收不增利
+        if current.revenue_growth > 10 and current.profit_growth < 0:
+            warnings.append({
+                "type": "增收不增利",
+                "severity": "high",
+                "description": f"营收增长{current.revenue_growth:.1f}%，但净利润下降{abs(current.profit_growth):.1f}%",
+                "revenue_growth": current.revenue_growth,
+                "profit_growth": current.profit_growth
+            })
+        
+        return {
+            "ok": True,
+            "code": code,
+            "name": current.name,
+            "report_date": current.report_date.isoformat(),
+            "warnings": warnings,
+            "risk_level": "高" if any(w["severity"] == "high" for w in warnings) else ("中" if warnings else "低")
+        }
+
+
+def get_report_calendar(days: int = 30) -> Dict[str, Any]:
+    """财报发布日历
+    
+    Args:
+        days: 未来N天
+    
+    Returns:
+        日历数据
+    """
+    today = dt.date.today()
+    end_date = today + dt.timedelta(days=days)
+    
+    with get_session() as s:
+        reports = s.execute(
+            select(FinancialReport)
+            .where(
+                and_(
+                    FinancialReport.publish_date >= today,
+                    FinancialReport.publish_date <= end_date
+                )
+            )
+            .order_by(FinancialReport.publish_date)
+        ).scalars().all()
+        
+        if not reports:
+            return {"ok": False, "msg": "暂无即将发布的财报"}
+        
+        # 按日期分组
+        calendar = defaultdict(list)
+        for r in reports:
+            calendar[r.publish_date.isoformat()].append({
+                "code": r.code,
+                "name": r.name,
+                "report_date": r.report_date.isoformat(),
+                "report_type": r.report_type
+            })
+        
+        return {
+            "ok": True,
+            "days": days,
+            "total": len(reports),
+            "calendar": dict(calendar)
+        }
+
+
+def get_top_reports(metric: str = "roe", limit: int = 20) -> Dict[str, Any]:
+    """获取财报排行榜
+    
+    Args:
+        metric: 排序指标（roe/gross_margin/revenue_growth）
+        limit: 返回数量
+    
+    Returns:
+        排行榜
+    """
+    with get_session() as s:
+        # 获取最新一期的所有财报
+        latest_date = s.execute(
+            select(func.max(FinancialReport.report_date))
+        ).scalar()
+        
+        if not latest_date:
+            return {"ok": False, "msg": "暂无数据"}
+        
+        # 根据指标排序
+        order_field = getattr(FinancialReport, metric)
+        
+        reports = s.execute(
+            select(FinancialReport)
+            .where(FinancialReport.report_date == latest_date)
+            .order_by(desc(order_field))
+            .limit(limit)
+        ).scalars().all()
+        
+        results = []
+        for r in reports:
+            results.append({
+                "code": r.code,
+                "name": r.name,
+                "roe": r.roe,
+                "gross_margin": r.gross_margin,
+                "revenue_growth": r.revenue_growth,
+                "profit_growth": r.profit_growth,
+                metric: getattr(r, metric)
+            })
+        
+        return {
+            "ok": True,
+            "metric": metric,
+            "report_date": latest_date.isoformat(),
+            "rankings": results
+        }
+