初始化提交：价值投资盯盘系统

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# 虚拟环境
+venv/
+ENV/
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# 项目特定
+config.json
+*.log
+.env
+.DS_Store 

README.md

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+# 价值投资盯盘系统
+
+一个基于 Python FastAPI 开发的智能股票分析与监控平台。
+
+## 功能特点
+
+- 实时股票数据监控
+- AI 智能分析
+- 财务指标分析
+- 价值投资建议
+- 股东信息查询
+- 指数行情展示
+
+## 技术栈
+
+- 后端：FastAPI + Python
+- 前端：Bootstrap 5 + ECharts
+- 数据源：Tushare API
+- 部署：Uvicorn
+
+## 安装使用
+
+1. 克隆项目
+```bash
+git clone https://github.com/你的用户名/stock-monitor.git
+cd stock-monitor
+```
+
+2. 安装依赖
+```bash
+pip install -r requirements.txt
+```
+
+3. 配置
+- 复制 `config.json.example` 为 `config.json`
+- 在 `config.json` 中配置你的 Tushare Token
+
+4. 运行
+```bash
+python run.py
+```
+
+5. 访问
+打开浏览器访问 `http://localhost:8000`
+
+## 配置说明
+
+主要配置项在 `app/config.py` 中：
+- TUSHARE_TOKEN：Tushare API Token
+- 其他配置项...
+
+## 开发说明
+
+- 遵循 PEP 8 编码规范
+- 使用 Python 3.8 或以上版本
+- 保持代码简洁清晰
+
+## 贡献指南
+
+欢迎提交 Issue 和 Pull Request
+
+## 许可证
+
+MIT License 

app/__init__.py

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+from fastapi import FastAPI
+from fastapi.staticfiles import StaticFiles
+from fastapi.templating import Jinja2Templates
+import tushare as ts
+from app.config import Config
+
+# 确保必要的目录和文件存在
+Config.ensure_directories()
+
+# 创建FastAPI实例
+app = FastAPI()
+
+# 设置tushare token
+ts.set_token(Config.TUSHARE_TOKEN)
+pro = ts.pro_api()
+
+# Mount static files
+app.mount("/static", StaticFiles(directory=Config.STATIC_DIR), name="static")
+
+# Set up templates
+templates = Jinja2Templates(directory=Config.TEMPLATES_DIR)
+
+# 导入路由
+from app.api import stock_routes
+app.include_router(stock_routes.router) 

app/api/stock_routes.py

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+from fastapi import APIRouter, Request, Form
+from typing import Optional
+from app.services.stock_service import StockService
+from app.services.ai_analysis_service import AIAnalysisService
+from app import templates
+
+router = APIRouter(prefix="")
+stock_service = StockService()
+ai_service = AIAnalysisService()
+
+@router.get("/")
+async def home(request: Request):
+    return templates.TemplateResponse("index.html", {"request": request})
+
+@router.get("/api/stock_info/{stock_code}")
+async def get_stock_info(stock_code: str, force_refresh: bool = False):
+    return stock_service.get_stock_info(stock_code, force_refresh)
+
+@router.get("/api/watchlist")
+async def get_watchlist():
+    return stock_service.get_watchlist()
+
+@router.post("/api/add_watch")
+async def add_watch(
+    stock_code: str = Form(...),
+    target_market_value_min: Optional[float] = Form(None),
+    target_market_value_max: Optional[float] = Form(None)
+):
+    return stock_service.add_watch(stock_code, target_market_value_min, target_market_value_max)
+
+@router.delete("/api/remove_watch/{stock_code}")
+async def remove_watch(stock_code: str):
+    return stock_service.remove_watch(stock_code)
+
+@router.get("/api/index_info")
+async def get_index_info():
+    return stock_service.get_index_info()
+
+@router.get("/market")
+async def market(request: Request):
+    return templates.TemplateResponse("market.html", {"request": request})
+
+@router.get("/api/company_detail/{stock_code}")
+async def get_company_detail(stock_code: str):
+    return stock_service.get_company_detail(stock_code)
+
+@router.get("/api/holders/{stock_code}")
+async def get_top_holders(stock_code: str):
+    """获取前十大股东数据"""
+    return stock_service.get_top_holders(stock_code)
+
+@router.get("/api/performance_forecast/{stock_code}")
+async def get_performance_forecast(stock_code: str):
+    """获取业绩预告数据"""
+    # 处理股票代码格式
+    if stock_code.startswith('6'):
+        ts_code = f"{stock_code}.SH"
+    elif stock_code.startswith(('0', '3')):
+        ts_code = f"{stock_code}.SZ"
+    else:
+        return {"error": "不支持的股票代码"}
+        
+    return stock_service.get_forecast_data(ts_code)
+
+@router.get("/api/value_analysis/{stock_code}")
+async def get_value_analysis(stock_code: str):
+    """获取价值投资分析数据"""
+    return stock_service.get_value_analysis_data(stock_code)
+
+@router.get("/api/ai_analysis/{stock_code}")
+async def get_ai_analysis(stock_code: str):
+    """获取AI价值投资分析结果"""
+    try:
+        # 首先获取价值分析数据
+        analysis_data = stock_service.get_value_analysis_data(stock_code)
+        if "error" in analysis_data:
+            return analysis_data
+            
+        # 使用AI服务进行分析
+        return ai_service.analyze_value_investment(analysis_data)
+    except Exception as e:
+        return {"error": f"AI分析失败: {str(e)}"} 

app/config.py

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+import os
+
+# 基础配置
+class Config:
+    # 项目根目录
+    BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+    
+    # Tushare API配置
+    TUSHARE_TOKEN = '90f8a141125e1decb952cd49032b7b8409a2d7fa370745f6c9f45c96'
+    
+    # 配置文件路径
+    CONFIG_FILE = os.path.join(BASE_DIR, "config.json")
+    
+    # 模板目录
+    TEMPLATES_DIR = os.path.join(BASE_DIR, "app", "templates")
+    
+    # 静态文件目录
+    STATIC_DIR = os.path.join(BASE_DIR, "app", "static")
+    
+    # 确保目录存在
+    @classmethod
+    def ensure_directories(cls):
+        os.makedirs(cls.STATIC_DIR, exist_ok=True)
+        os.makedirs(cls.TEMPLATES_DIR, exist_ok=True)
+        
+        # 确保配置文件存在
+        if not os.path.exists(cls.CONFIG_FILE):
+            with open(cls.CONFIG_FILE, 'w', encoding='utf-8') as f:
+                f.write('{"watchlist": {}}') 

app/models/stock.py

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+from pydantic import BaseModel
+from typing import Dict, Optional, Union, List
+
+class MarketValueTarget(BaseModel):
+    min: Optional[float] = None
+    max: Optional[float] = None
+
+class StockTarget(BaseModel):
+    target_market_value: Optional[MarketValueTarget] = None
+
+class StockInfo(BaseModel):
+    code: str
+    name: str
+    market_value: float
+    pe_ratio: float
+    pb_ratio: float
+    ps_ratio: float
+    dividend_yield: float
+    price: float
+    change_percent: float
+    roe: float
+    gross_profit_margin: float
+    net_profit_margin: float
+    debt_to_assets: float
+    revenue_yoy: float
+    net_profit_yoy: float
+    bps: float
+    ocfps: float
+
+class StockResponse(BaseModel):
+    stock_info: StockInfo
+    targets: StockTarget 

app/services/ai_analysis_service.py

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+import json
+import os
+import re
+from openai import OpenAI
+
+class AIAnalysisService:
+    def __init__(self):
+        self.model = "ep-20250111143839-vn8l8"  # endpoint ID
+        self.client = OpenAI(
+            api_key = "cf4edd4d-55cd-4e0f-82f6-49072660bdaf",  # 直接使用API Key
+            base_url = "https://ark.cn-beijing.volces.com/api/v3"
+        )
+        
+    def analyze_value_investment(self, analysis_data):
+        """
+        对股票进行价值投资分析
+        :param analysis_data: 包含各项财务指标的字典
+        :return: AI分析结果
+        """
+        try:
+            # 打印输入数据用于调试
+            print(f"输入的分析数据: {json.dumps(analysis_data, ensure_ascii=False, indent=2)}")
+            
+            # 构建提示词
+            prompt = self._build_analysis_prompt(analysis_data)
+            
+            # 打印提示词用于调试
+            print(f"AI分析提示词: {prompt}")
+            
+            # 调用API
+            response = self.client.chat.completions.create(
+                model=self.model,
+                messages=[
+                    {
+                        "role": "user",
+                        "content": [
+                            {
+                                "type": "text",
+                                "text": prompt
+                            }
+                        ]
+                    }
+                ]
+            )
+            
+            # 获取分析结果
+            analysis_text = response.choices[0].message.content
+            print(f"AI原始返回结果: {analysis_text}")
+            
+            try:
+                # 尝试解析JSON
+                analysis_result = json.loads(analysis_text)
+                print(f"解析后的JSON结果: {json.dumps(analysis_result, ensure_ascii=False, indent=2)}")
+                
+                # 构建完整的返回结果
+                result = analysis_result
+                
+                print(f"最终返回结果: {json.dumps(result, ensure_ascii=False, indent=2)}")
+                return result
+                
+            except json.JSONDecodeError as e:
+                print(f"JSON解析失败: {str(e)}")
+                # 如果JSON解析失败，返回错误信息
+                return {
+                    'stock_info': analysis_data.get('stock_info', {}),
+                    'valuation': analysis_data.get('valuation', {}),
+                    'profitability': analysis_data.get('profitability', {}),
+                    'growth': analysis_data.get('growth', {}),
+                    'operation': analysis_data.get('operation', {}),
+                    'solvency': analysis_data.get('solvency', {}),
+                    'cash_flow': analysis_data.get('cash_flow', {}),
+                    'per_share': analysis_data.get('per_share', {}),
+                    'analysis_result': {
+                        "error": "AI返回的结果不是有效的JSON格式",
+                        "raw_text": analysis_text
+                    }
+                }
+            
+        except Exception as e:
+            print(f"AI分析失败: {str(e)}")
+            print(f"错误详情: {e.__class__.__name__}")
+            import traceback
+            print(f"错误堆栈: {traceback.format_exc()}")
+            return {"error": f"AI分析失败: {str(e)}"}
+    
+    def _parse_analysis_result(self, analysis_text, current_price):
+        """
+        解析AI返回的分析文本，提取结构化信息
+        """
+        try:
+            print(f"开始解析分析文本...")
+            
+            # 提取投资建议
+            suggestion_pattern = r"投资建议[：:]([\s\S]*?)(?=\n\n|$)"
+            suggestion_match = re.search(suggestion_pattern, analysis_text, re.MULTILINE | re.DOTALL)
+            investment_suggestion = suggestion_match.group(1).strip() if suggestion_match else ""
+            print(f"提取到的投资建议: {investment_suggestion}")
+            
+            # 提取合理价格区间
+            price_pattern = r"合理股价区间[：:]\s*(\d+\.?\d*)\s*[元-]\s*(\d+\.?\d*)[元]"
+            price_match = re.search(price_pattern, analysis_text)
+            if price_match:
+                price_min = float(price_match.group(1))
+                price_max = float(price_match.group(2))
+            else:
+                price_min = current_price * 0.8
+                price_max = current_price * 1.2
+            print(f"提取到的价格区间: {price_min}-{price_max}")
+            
+            # 提取目标市值区间（单位：亿元）
+            market_value_pattern = r"目标市值区间[：:]\s*(\d+\.?\d*)\s*[亿-]\s*(\d+\.?\d*)[亿]"
+            market_value_match = re.search(market_value_pattern, analysis_text)
+            if market_value_match:
+                market_value_min = float(market_value_match.group(1))
+                market_value_max = float(market_value_match.group(2))
+            else:
+                # 尝试从文本中提取计算得出的市值
+                calc_pattern = r"最低市值[=≈约]*(\d+\.?\d*)[亿].*最高市值[=≈约]*(\d+\.?\d*)[亿]"
+                calc_match = re.search(calc_pattern, analysis_text)
+                if calc_match:
+                    market_value_min = float(calc_match.group(1))
+                    market_value_max = float(calc_match.group(2))
+                else:
+                    market_value_min = 0
+                    market_value_max = 0
+            print(f"提取到的市值区间: {market_value_min}-{market_value_max}")
+            
+            # 提取各个分析维度的内容
+            analysis_patterns = {
+                "valuation_analysis": r"估值分析([\s\S]*?)(?=###\s*财务状况分析|###\s*成长性分析|$)",
+                "financial_health": r"财务状况分析([\s\S]*?)(?=###\s*成长性分析|###\s*风险评估|$)",
+                "growth_potential": r"成长性分析([\s\S]*?)(?=###\s*风险评估|###\s*投资建议|$)",
+                "risk_assessment": r"风险评估([\s\S]*?)(?=###\s*投资建议|$)"
+            }
+            
+            analysis_results = {}
+            for key, pattern in analysis_patterns.items():
+                match = re.search(pattern, analysis_text, re.MULTILINE | re.DOTALL)
+                content = match.group(1).strip() if match else ""
+                # 移除markdown标记和多余的空白字符
+                content = re.sub(r'[#\-*]', '', content).strip()
+                analysis_results[key] = content
+                print(f"提取到的{key}: {content[:100]}...")
+            
+            return {
+                "investment_suggestion": investment_suggestion,
+                "analysis": analysis_results,
+                "price_analysis": {
+                    "reasonable_price_range": {
+                        "min": price_min,
+                        "max": price_max
+                    },
+                    "target_market_value": {
+                        "min": market_value_min,
+                        "max": market_value_max
+                    }
+                }
+            }
+            
+        except Exception as e:
+            print(f"解析分析结果失败: {str(e)}")
+            print(f"错误详情: {e.__class__.__name__}")
+            import traceback
+            print(f"错误堆栈: {traceback.format_exc()}")
+            return {
+                "investment_suggestion": "分析结果解析失败",
+                "analysis": {
+                    "valuation_analysis": "解析失败",
+                    "financial_health": "解析失败",
+                    "growth_potential": "解析失败",
+                    "risk_assessment": "解析失败"
+                },
+                "price_analysis": {
+                    "reasonable_price_range": {
+                        "min": current_price * 0.8,
+                        "max": current_price * 1.2
+                    },
+                    "target_market_value": {
+                        "min": 0,
+                        "max": 0
+                    }
+                }
+            }
+    
+    def _build_analysis_prompt(self, data):
+        """
+        构建AI分析提示词
+        """
+        stock_info = data.get('stock_info', {})
+        valuation = data.get('valuation', {})
+        profitability = data.get('profitability', {})
+        growth = data.get('growth', {})
+        operation = data.get('operation', {})
+        solvency = data.get('solvency', {})
+        cash_flow = data.get('cash_flow', {})
+        per_share = data.get('per_share', {})
+        
+        # 格式化数值，保留4位小数
+        def format_number(value):
+            try:
+                if value is None:
+                    return "0.0000"
+                if isinstance(value, (int, float)):
+                    if abs(value) < 0.0001:  # 对于非常小的数值
+                        return "0.0000"
+                    return f"{value:.4f}"
+                if isinstance(value, str):
+                    try:
+                        value = float(value)
+                        if abs(value) < 0.0001:
+                            return "0.0000"
+                        return f"{value:.4f}"
+                    except:
+                        pass
+                return str(value)
+            except:
+                return "0.0000"
+        
+        # 格式化百分比，保留2位小数
+        def format_percent(value):
+            try:
+                if value is None:
+                    return "0.00%"
+                if isinstance(value, (int, float)):
+                    # 如果值已经是小数形式（如0.5代表50%），则乘以100
+                    if abs(value) <= 1:
+                        value = value * 100
+                    return f"{value:.2f}%"
+                if isinstance(value, str):
+                    try:
+                        value = float(value)
+                        if abs(value) <= 1:
+                            value = value * 100
+                        return f"{value:.2f}%"
+                    except:
+                        pass
+                return "0.00%"
+            except:
+                return "0.00%"
+
+        # 构建数据部分
+        data_section = f"""请作为一位专业的价值投资分析师，对{stock_info.get('name', '')}({stock_info.get('code', '')})进行深入的价值投资分析。
+
+当前市场信息：
+- 市盈率(PE)：{format_number(valuation.get('pe_ratio'))}
+- 市净率(PB)：{format_number(valuation.get('pb_ratio'))}
+- 市销率(PS)：{format_number(valuation.get('ps_ratio'))}
+- 股息率：{format_percent(valuation.get('dividend_yield'))}
+- 总市值(亿元)：{format_number(valuation.get('total_market_value'))}
+- 当前股价：{format_number(stock_info.get('current_price'))}元
+
+盈利能力指标：
+- ROE：{format_percent(profitability.get('roe'))}
+- 毛利率：{format_percent(profitability.get('gross_margin'))}
+- 净利率：{format_percent(profitability.get('net_margin'))}
+
+成长能力指标：
+- 净利润增长率：{format_percent(growth.get('net_profit_growth'))}
+- 扣非净利润增长率：{format_percent(growth.get('deducted_net_profit_growth'))}
+- 营收增长率：{format_percent(growth.get('revenue_growth'))}
+
+运营能力指标：
+- 总资产周转率：{format_number(operation.get('asset_turnover'))}次/年
+- 存货周转率：{format_number(operation.get('inventory_turnover'))}次/年
+- 应收账款周转率：{format_number(operation.get('receivables_turnover'))}次/年
+
+偿债能力指标：
+- 流动比率：{format_number(solvency.get('current_ratio'))}
+- 速动比率：{format_number(solvency.get('quick_ratio'))}
+- 资产负债率：{format_percent(solvency.get('debt_to_assets'))}
+
+现金流指标：
+- 经营现金流/营收比：{format_percent(cash_flow.get('ocf_to_revenue'))}
+- 经营现金流同比增长：{format_percent(cash_flow.get('ocf_growth'))}
+
+每股指标：
+- 每股收益(EPS)：{format_number(per_share.get('eps'))}元
+- 每股净资产(BPS)：{format_number(per_share.get('bps'))}元
+- 每股现金流(CFPS)：{format_number(per_share.get('cfps'))}元
+- 每股经营现金流(OCFPS)：{format_number(per_share.get('ocfps'))}元
+- 每股未分配利润：{format_number(per_share.get('retained_eps'))}元"""
+
+        # 构建分析要求部分
+        analysis_requirements = """
+请基于以上数据，从价值投资的角度进行分析。请特别注意：
+1. 结合行业特点、公司竞争力、成长性等因素，给出合理的估值区间
+2. 存货周转率为0可能表示数据缺失，分析时需要谨慎对待
+3. 考虑当前市场环境和行业整体估值水平
+
+在给出估值区间时，请充分考虑：
+1. 公司所处行业特点和竞争格局
+2. 公司的竞争优势和市场地位
+3. 当前的盈利能力和成长性
+4. 财务健康状况和风险因素
+5. 宏观经济环境和行业周期
+6. 可比公司的估值水平
+
+请以JSON格式返回分析结果，包含以下内容：
+1. investment_suggestion: 投资建议，包含summary(总体建议)、action(具体操作建议)和key_points(关注重点)
+2. analysis: 详细分析，包含估值分析、财务健康状况、成长潜力和风险评估
+3. price_analysis: 价格分析，包含合理价格区间和目标市值区间
+
+请确保返回的是一个有效的JSON格式，数值使用数字而不是字符串（价格、市值等），文本分析使用字符串。分析要客观、专业、详细。"""
+
+        # 组合完整的提示词
+        prompt = data_section + analysis_requirements
+        
+        return prompt 

app/services/stock_service.py

@@ -0,0 +1,573 @@
+import json
+import os
+from datetime import datetime
+import pandas as pd
+from app import pro
+from app.config import Config
+import numpy as np
+
+class StockService:
+    def __init__(self):
+        self.watchlist = {}
+        self.cache_file = os.path.join(Config.BASE_DIR, "stock_cache.json")
+        self.load_watchlist()
+        self.load_cache()
+
+    def load_watchlist(self):
+        try:
+            if os.path.exists(Config.CONFIG_FILE):
+                with open(Config.CONFIG_FILE, 'r', encoding='utf-8') as f:
+                    data = json.load(f)
+                    self.watchlist = data.get('watchlist', {})
+        except Exception as e:
+            print(f"Error loading watchlist: {str(e)}")
+            self.watchlist = {}
+
+    def _save_watchlist(self):
+        try:
+            with open(Config.CONFIG_FILE, 'w', encoding='utf-8') as f:
+                json.dump({'watchlist': self.watchlist}, f, ensure_ascii=False, indent=4)
+        except Exception as e:
+            print(f"Error saving watchlist: {str(e)}")
+
+    def load_cache(self):
+        try:
+            if os.path.exists(self.cache_file):
+                with open(self.cache_file, 'r', encoding='utf-8') as f:
+                    self.cache_data = json.load(f)
+            else:
+                self.cache_data = {}
+        except Exception as e:
+            print(f"Error loading cache: {str(e)}")
+            self.cache_data = {}
+
+    def save_cache(self, stock_code, data):
+        try:
+            self.cache_data[stock_code] = {
+                'data': data,
+                'timestamp': datetime.now().strftime('%Y-%m-%d')
+            }
+            with open(self.cache_file, 'w', encoding='utf-8') as f:
+                json.dump(self.cache_data, f, ensure_ascii=False, indent=4)
+        except Exception as e:
+            print(f"Error saving cache: {str(e)}")
+
+    def get_stock_info(self, stock_code: str, force_refresh: bool = False):
+        try:
+            # 检查缓存
+            today = datetime.now().strftime('%Y-%m-%d')
+            if not force_refresh and stock_code in self.cache_data and self.cache_data[stock_code]['timestamp'] == today:
+                print(f"从缓存获取股票 {stock_code} 的数据")
+                cached_data = self.cache_data[stock_code]['data']
+                cached_data['stock_info']['from_cache'] = True
+                return cached_data
+
+            # 如果强制刷新或缓存不存在或已过期，从API获取数据
+            print(f"从API获取股票 {stock_code} 的数据...")
+
+            # 处理股票代码格式
+            if len(stock_code) != 6:
+                return {"error": "股票代码格式错误"}
+                
+            # 确定交易所
+            if stock_code.startswith('6'):
+                ts_code = f"{stock_code}.SH"
+            elif stock_code.startswith(('0', '3')):
+                ts_code = f"{stock_code}.SZ"
+            else:
+                return {"error": "不支持的股票代码"}
+
+            # 获取基本信息和总市值
+            basic_info = pro.daily_basic(ts_code=ts_code, fields='ts_code,total_mv', limit=1)
+            if basic_info.empty:
+                return {"error": "股票代码不存在"}
+
+            # 获取股票名称
+            stock_name = pro.stock_basic(ts_code=ts_code, fields='name').iloc[0]['name']
+
+            # 获取最新财务指标
+            fina_indicator = pro.fina_indicator(ts_code=ts_code, period=datetime.now().strftime('%Y%m%d'), fields='roe,grossprofit_margin,netprofit_margin,debt_to_assets,op_income_yoy,netprofit_yoy,bps,ocfps')
+            if fina_indicator.empty:
+                fina_indicator = pro.fina_indicator(ts_code=ts_code, limit=1)
+                
+            # 获取实时行情
+            today = datetime.now().strftime('%Y%m%d')
+            daily_data = pro.daily(ts_code=basic_info['ts_code'].iloc[0], start_date=today, end_date=today)
+            if daily_data.empty:
+                daily_data = pro.daily(ts_code=basic_info['ts_code'].iloc[0], limit=1)
+                if daily_data.empty:
+                    return {"error": "无法获取股票行情数据"}
+
+            # 获取市值信息（用于其他指标）
+            daily_basic = pro.daily_basic(ts_code=basic_info['ts_code'].iloc[0], 
+                                        fields='ts_code,trade_date,pe,pb,ps,dv_ratio',
+                                        limit=1)
+            
+            if daily_basic.empty:
+                return {"error": "无法获取股票基础数据"}
+                
+            latest_basic = daily_basic.iloc[0]
+            latest_fina = fina_indicator.iloc[0] if not fina_indicator.empty else pd.Series()
+            
+            # 计算实时总市值（单位：亿元）
+            current_price = float(daily_data['close'].iloc[0])
+            market_value = float(basic_info['total_mv'].iloc[0]) / 10000  # 转换为亿元
+            print(f"市值计算: 当前价格={current_price}, 总市值={market_value}亿元")
+            
+            # 处理股息率：tushare返回的是百分比值，需要转换为小数
+            dv_ratio = float(latest_basic['dv_ratio']) if pd.notna(latest_basic['dv_ratio']) else 0
+            dividend_yield = round(dv_ratio / 100, 4)  # 转换为小数
+            
+            # 处理财务指标，确保所有值都有默认值0，转换为小数
+            roe = round(float(latest_fina['roe']) / 100, 4) if pd.notna(latest_fina.get('roe')) else 0
+            gross_profit_margin = round(float(latest_fina['grossprofit_margin']) / 100, 4) if pd.notna(latest_fina.get('grossprofit_margin')) else 0
+            net_profit_margin = round(float(latest_fina['netprofit_margin']) / 100, 4) if pd.notna(latest_fina.get('netprofit_margin')) else 0
+            debt_to_assets = round(float(latest_fina['debt_to_assets']) / 100, 4) if pd.notna(latest_fina.get('debt_to_assets')) else 0
+            revenue_yoy = round(float(latest_fina['op_income_yoy']) / 100, 4) if pd.notna(latest_fina.get('op_income_yoy')) else 0
+            net_profit_yoy = round(float(latest_fina['netprofit_yoy']) / 100, 4) if pd.notna(latest_fina.get('netprofit_yoy')) else 0
+            bps = round(float(latest_fina['bps']), 3) if pd.notna(latest_fina.get('bps')) else 0  # 保留3位小数
+            ocfps = round(float(latest_fina['ocfps']), 3) if pd.notna(latest_fina.get('ocfps')) else 0  # 保留3位小数
+            
+            stock_info = {
+                "code": stock_code,
+                "name": stock_name,
+                "market_value": round(market_value, 2),  # 总市值（亿元）
+                "pe_ratio": round(float(latest_basic['pe']), 2) if pd.notna(latest_basic['pe']) else 0,  # 市盈率
+                "pb_ratio": round(float(latest_basic['pb']), 2) if pd.notna(latest_basic['pb']) else 0,  # 市净率
+                "ps_ratio": round(float(latest_basic['ps']), 2) if pd.notna(latest_basic['ps']) else 0,  # 市销率
+                "dividend_yield": dividend_yield,  # 股息率（小数）
+                "price": round(current_price, 2),  # 股价保留2位小数
+                "change_percent": round(float(daily_data['pct_chg'].iloc[0]) / 100, 4),  # 涨跌幅转换为小数
+                # 财务指标（全部转换为小数）
+                "roe": roe,  # ROE（小数）
+                "gross_profit_margin": gross_profit_margin,  # 毛利率（小数）
+                "net_profit_margin": net_profit_margin,  # 净利率（小数）
+                "debt_to_assets": debt_to_assets,  # 资产负债率（小数）
+                "revenue_yoy": revenue_yoy,  # 营收增长率（小数）
+                "net_profit_yoy": net_profit_yoy,  # 净利润增长率（小数）
+                "bps": bps,  # 每股净资产
+                "ocfps": ocfps,  # 每股经营现金流
+                "from_cache": False
+            }
+
+            # 获取目标值
+            targets = self.watchlist.get(stock_code, {})
+
+            result = {
+                "stock_info": stock_info,
+                "targets": targets
+            }
+
+            # 保存到缓存
+            self.save_cache(stock_code, result)
+
+            return result
+        except Exception as e:
+            print(f"Error fetching stock info: {str(e)}")
+            import traceback
+            print(f"详细错误: {traceback.format_exc()}")
+            return {"error": f"获取股票数据失败: {str(e)}"}
+
+    def get_watchlist(self):
+        result = []
+        for stock_code, targets in self.watchlist.items():
+            try:
+                # 从缓存获取数据
+                today = datetime.now().strftime('%Y-%m-%d')
+                if stock_code in self.cache_data and self.cache_data[stock_code]['timestamp'] == today:
+                    result.append(self.cache_data[stock_code]['data'])
+                    continue
+
+                # 如果没有缓存，只获取基本信息
+                if stock_code.startswith('6'):
+                    ts_code = f"{stock_code}.SH"
+                elif stock_code.startswith(('0', '3')):
+                    ts_code = f"{stock_code}.SZ"
+                else:
+                    print(f"不支持的股票代码: {stock_code}")
+                    continue
+                    
+                # 获取股票名称
+                stock_name = pro.stock_basic(ts_code=ts_code, fields='name').iloc[0]['name']
+                
+                result.append({
+                    "stock_info": {
+                        "code": stock_code,
+                        "name": stock_name
+                    },
+                    "targets": targets
+                })
+            except Exception as e:
+                print(f"Error getting watchlist info for {stock_code}: {str(e)}")
+                continue
+        return result
+
+    def add_watch(self, stock_code: str, target_market_value_min: float = None, target_market_value_max: float = None):
+        self.watchlist[stock_code] = {
+            "target_market_value": {
+                "min": target_market_value_min,
+                "max": target_market_value_max
+            }
+        }
+        self._save_watchlist()
+        return {"status": "success"}
+
+    def remove_watch(self, stock_code: str):
+        if stock_code in self.watchlist:
+            del self.watchlist[stock_code]
+            # 同时删除缓存
+            if stock_code in self.cache_data:
+                del self.cache_data[stock_code]
+                try:
+                    with open(self.cache_file, 'w', encoding='utf-8') as f:
+                        json.dump(self.cache_data, f, ensure_ascii=False, indent=4)
+                except Exception as e:
+                    print(f"Error saving cache after removal: {str(e)}")
+        self._save_watchlist()
+        return {"status": "success"}
+
+    def get_index_info(self):
+        """获取主要指数数据"""
+        try:
+            # 主要指数代码列表
+            index_codes = {
+                '000001.SH': '上证指数',
+                '399001.SZ': '深证成指',
+                '399006.SZ': '创业板指',
+                '000016.SH': '上证50',
+                '000300.SH': '沪深300',
+                '000905.SH': '中证500',
+                '000852.SH': '中证1000',
+                '899050.BJ': '北证50',
+            }
+            
+            result = []
+            for ts_code, name in index_codes.items():
+                try:
+                    # 获取指数基本信息
+                    df = pro.index_daily(ts_code=ts_code, limit=1)
+                    if not df.empty:
+                        data = df.iloc[0]
+                        # 获取K线数据(最近20天)
+                        kline_df = pro.index_daily(ts_code=ts_code, limit=20)
+                        kline_data = []
+                        if not kline_df.empty:
+                            for _, row in kline_df.iterrows():
+                                kline_data.append({
+                                    'date': row['trade_date'],
+                                    'open': float(row['open']),
+                                    'close': float(row['close']),
+                                    'high': float(row['high']),
+                                    'low': float(row['low']),
+                                    'vol': float(row['vol'])
+                                })
+                        
+                        result.append({
+                            'code': ts_code,
+                            'name': name,
+                            'price': float(data['close']),
+                            'change': float(data['pct_chg']),
+                            'kline_data': kline_data
+                        })
+                except Exception as e:
+                    print(f"获取指数 {ts_code} 数据失败: {str(e)}")
+                    continue
+            
+            return result
+        except Exception as e:
+            print(f"获取指数数据失败: {str(e)}")
+            return [] 
+
+    def get_company_detail(self, stock_code: str):
+        try:
+            print(f"开始获取公司详情: {stock_code}")
+            
+            # 处理股票代码格式
+            if stock_code.startswith('6'):
+                ts_code = f"{stock_code}.SH"
+            elif stock_code.startswith(('0', '3')):
+                ts_code = f"{stock_code}.SZ"
+            else:
+                print(f"不支持的股票代码格式: {stock_code}")
+                return {"error": "不支持的股票代码"}
+
+            print(f"转换后的ts_code: {ts_code}")
+
+            # 获取公司基本信息
+            basic = pro.stock_basic(ts_code=ts_code, fields='name,industry,area,list_date')
+            if basic.empty:
+                print(f"无法获取公司基本信息: {ts_code}")
+                return {"error": "无法获取公司信息"}
+            
+            company_info = basic.iloc[0]
+            print(f"获取到的公司基本信息: {company_info.to_dict()}")
+            
+            # 获取公司详细信息
+            try:
+                company_detail = pro.stock_company(ts_code=ts_code)
+                if not company_detail.empty:
+                    detail_info = company_detail.iloc[0]
+                    company_detail_dict = {
+                        "com_name": str(detail_info.get('com_name', '')),
+                        "chairman": str(detail_info.get('chairman', '')),
+                        "manager": str(detail_info.get('manager', '')),
+                        "secretary": str(detail_info.get('secretary', '')),
+                        "reg_capital": float(detail_info.get('reg_capital', 0)) if pd.notna(detail_info.get('reg_capital')) else 0,
+                        "setup_date": str(detail_info.get('setup_date', '')),
+                        "province": str(detail_info.get('province', '')),
+                        "city": str(detail_info.get('city', '')),
+                        "introduction": str(detail_info.get('introduction', '')),
+                        "website": f"http://{str(detail_info.get('website', '')).strip('http://').strip('https://')}" if detail_info.get('website') else "",
+                        "email": str(detail_info.get('email', '')),
+                        "office": str(detail_info.get('office', '')),
+                        "employees": int(detail_info.get('employees', 0)) if pd.notna(detail_info.get('employees')) else 0,
+                        "main_business": str(detail_info.get('main_business', '')),
+                        "business_scope": str(detail_info.get('business_scope', ''))
+                    }
+                else:
+                    company_detail_dict = {
+                        "com_name": "", "chairman": "", "manager": "", "secretary": "",
+                        "reg_capital": 0, "setup_date": "", "province": "", "city": "",
+                        "introduction": "", "website": "", "email": "", "office": "",
+                        "employees": 0, "main_business": "", "business_scope": ""
+                    }
+            except Exception as e:
+                print(f"获取公司详细信息失败: {str(e)}")
+                company_detail_dict = {
+                    "com_name": "", "chairman": "", "manager": "", "secretary": "",
+                    "reg_capital": 0, "setup_date": "", "province": "", "city": "",
+                    "introduction": "", "website": "", "email": "", "office": "",
+                    "employees": 0, "main_business": "", "business_scope": ""
+                }
+            
+            # 获取最新财务指标
+            try:
+                fina = pro.fina_indicator(ts_code=ts_code, period=datetime.now().strftime('%Y%m%d'))
+                if fina.empty:
+                    print("当前期间无财务数据，尝试获取最新一期数据")
+                    fina = pro.fina_indicator(ts_code=ts_code, limit=1)
+                
+                if fina.empty:
+                    print(f"无法获取财务指标数据: {ts_code}")
+                    return {"error": "无法获取财务数据"}
+                    
+                fina_info = fina.iloc[0]
+                print(f"获取到的财务指标: {fina_info.to_dict()}")
+            except Exception as e:
+                print(f"获取财务指标失败: {str(e)}")
+                return {"error": "获取财务指标失败"}
+            
+            # 获取市值信息（用于PE、PB等指标）
+            try:
+                daily_basic = pro.daily_basic(ts_code=ts_code, fields='pe,pb,ps,dv_ratio', limit=1)
+                if not daily_basic.empty:
+                    latest_basic = daily_basic.iloc[0]
+                else:
+                    print("无法获取PE/PB数据")
+                    latest_basic = pd.Series({'pe': 0, 'pb': 0, 'ps': 0, 'dv_ratio': 0})
+            except Exception as e:
+                print(f"获取PE/PB失败: {str(e)}")
+                latest_basic = pd.Series({'pe': 0, 'pb': 0, 'ps': 0, 'dv_ratio': 0})
+            
+            result = {
+                "basic_info": {
+                    "name": str(company_info['name']),
+                    "industry": str(company_info['industry']),
+                    "list_date": str(company_info['list_date']),
+                    "area": str(company_info['area']),
+                    **company_detail_dict
+                },
+                "financial_info": {
+                    # 估值指标
+                    "pe_ratio": float(latest_basic['pe']) if pd.notna(latest_basic['pe']) else 0,
+                    "pb_ratio": float(latest_basic['pb']) if pd.notna(latest_basic['pb']) else 0,
+                    "ps_ratio": float(latest_basic['ps']) if pd.notna(latest_basic['ps']) else 0,
+                    "dividend_yield": float(latest_basic['dv_ratio'])/100 if pd.notna(latest_basic['dv_ratio']) else 0,
+                    
+                    # 盈利能力
+                    "roe": float(fina_info['roe']) if pd.notna(fina_info.get('roe')) else 0,
+                    "roe_dt": float(fina_info['roe_dt']) if pd.notna(fina_info.get('roe_dt')) else 0,
+                    "roa": float(fina_info['roa']) if pd.notna(fina_info.get('roa')) else 0,
+                    "grossprofit_margin": float(fina_info['grossprofit_margin']) if pd.notna(fina_info.get('grossprofit_margin')) else 0,
+                    "netprofit_margin": float(fina_info['netprofit_margin']) if pd.notna(fina_info.get('netprofit_margin')) else 0,
+                    
+                    # 成长能力
+                    "netprofit_yoy": float(fina_info['netprofit_yoy']) if pd.notna(fina_info.get('netprofit_yoy')) else 0,
+                    "dt_netprofit_yoy": float(fina_info['dt_netprofit_yoy']) if pd.notna(fina_info.get('dt_netprofit_yoy')) else 0,
+                    "tr_yoy": float(fina_info['tr_yoy']) if pd.notna(fina_info.get('tr_yoy')) else 0,
+                    "or_yoy": float(fina_info['or_yoy']) if pd.notna(fina_info.get('or_yoy')) else 0,
+                    
+                    # 营运能力
+                    "assets_turn": float(fina_info['assets_turn']) if pd.notna(fina_info.get('assets_turn')) else 0,
+                    "inv_turn": float(fina_info['inv_turn']) if pd.notna(fina_info.get('inv_turn')) else 0,
+                    "ar_turn": float(fina_info['ar_turn']) if pd.notna(fina_info.get('ar_turn')) else 0,
+                    "ca_turn": float(fina_info['ca_turn']) if pd.notna(fina_info.get('ca_turn')) else 0,
+                    
+                    # 偿债能力
+                    "current_ratio": float(fina_info['current_ratio']) if pd.notna(fina_info.get('current_ratio')) else 0,
+                    "quick_ratio": float(fina_info['quick_ratio']) if pd.notna(fina_info.get('quick_ratio')) else 0,
+                    "debt_to_assets": float(fina_info['debt_to_assets']) if pd.notna(fina_info.get('debt_to_assets')) else 0,
+                    "debt_to_eqt": float(fina_info['debt_to_eqt']) if pd.notna(fina_info.get('debt_to_eqt')) else 0,
+                    
+                    # 现金流
+                    "ocf_to_or": float(fina_info['ocf_to_or']) if pd.notna(fina_info.get('ocf_to_or')) else 0,
+                    "ocf_to_opincome": float(fina_info['ocf_to_opincome']) if pd.notna(fina_info.get('ocf_to_opincome')) else 0,
+                    "ocf_yoy": float(fina_info['ocf_yoy']) if pd.notna(fina_info.get('ocf_yoy')) else 0,
+                    
+                    # 每股指标
+                    "eps": float(fina_info['eps']) if pd.notna(fina_info.get('eps')) else 0,
+                    "dt_eps": float(fina_info['dt_eps']) if pd.notna(fina_info.get('dt_eps')) else 0,
+                    "bps": float(fina_info['bps']) if pd.notna(fina_info.get('bps')) else 0,
+                    "ocfps": float(fina_info['ocfps']) if pd.notna(fina_info.get('ocfps')) else 0,
+                    "retainedps": float(fina_info['retainedps']) if pd.notna(fina_info.get('retainedps')) else 0,
+                    "cfps": float(fina_info['cfps']) if pd.notna(fina_info.get('cfps')) else 0,
+                    "ebit_ps": float(fina_info['ebit_ps']) if pd.notna(fina_info.get('ebit_ps')) else 0,
+                    "fcff_ps": float(fina_info['fcff_ps']) if pd.notna(fina_info.get('fcff_ps')) else 0,
+                    "fcfe_ps": float(fina_info['fcfe_ps']) if pd.notna(fina_info.get('fcfe_ps')) else 0
+                }
+            }
+            
+            print(f"返回结果: {result}")
+            return result
+            
+        except Exception as e:
+            print(f"Error getting company detail: {str(e)}")
+            import traceback
+            print(f"详细错误: {traceback.format_exc()}")
+            return {"error": f"获取公司详情失败: {str(e)}"} 
+
+    def get_top_holders(self, stock_code: str):
+        """获取前十大股东数据"""
+        try:
+            # 处理股票代码格式
+            if stock_code.startswith('6'):
+                ts_code = f"{stock_code}.SH"
+            elif stock_code.startswith(('0', '3')):
+                ts_code = f"{stock_code}.SZ"
+            else:
+                return {"error": "不支持的股票代码"}
+
+            # 获取最新一期的股东数据
+            df = pro.top10_holders(ts_code=ts_code, limit=10)
+            if df.empty:
+                return {"error": "暂无股东数据"}
+
+            # 按持股比例降序排序
+            df = df.sort_values('hold_ratio', ascending=False)
+            
+            # 获取最新的报告期
+            latest_end_date = df['end_date'].max()
+            latest_data = df[df['end_date'] == latest_end_date]
+
+            holders = []
+            for _, row in latest_data.iterrows():
+                holders.append({
+                    "holder_name": str(row['holder_name']),
+                    "hold_amount": float(row['hold_amount']) if pd.notna(row['hold_amount']) else 0,
+                    "hold_ratio": float(row['hold_ratio']) if pd.notna(row['hold_ratio']) else 0,
+                    "hold_change": float(row['hold_change']) if pd.notna(row['hold_change']) else 0,
+                    "ann_date": str(row['ann_date']),
+                    "end_date": str(row['end_date'])
+                })
+
+            result = {
+                "holders": holders,
+                "total_ratio": sum(holder['hold_ratio'] for holder in holders),  # 合计持股比例
+                "report_date": str(latest_end_date)  # 报告期
+            }
+            
+            return result
+            
+        except Exception as e:
+            print(f"获取股东数据失败: {str(e)}")
+            import traceback
+            print(f"详细错误: {traceback.format_exc()}")
+            return {"error": f"获取股东数据失败: {str(e)}"} 
+
+    def get_value_analysis_data(self, stock_code: str):
+        """获取价值投资分析所需的关键财务指标"""
+        try:
+            # 处理股票代码格式
+            if stock_code.startswith('6'):
+                ts_code = f"{stock_code}.SH"
+            elif stock_code.startswith(('0', '3')):
+                ts_code = f"{stock_code}.SZ"
+            else:
+                return {"error": "不支持的股票代码"}
+
+            # 获取最新每日指标（估值数据）
+            daily_basic = pro.daily_basic(ts_code=ts_code, fields='pe,pb,ps,dv_ratio,total_mv', limit=1)
+            if daily_basic.empty:
+                return {"error": "无法获取股票估值数据"}
+
+            # 获取最新财务指标
+            fina = pro.fina_indicator(ts_code=ts_code, fields='''roe,grossprofit_margin,netprofit_margin,
+                netprofit_yoy,dt_netprofit_yoy,tr_yoy,or_yoy,assets_turn,inv_turn,ar_turn,current_ratio,
+                quick_ratio,debt_to_assets,ocf_to_or,ocf_yoy,eps,bps,cfps,ocfps,retainedps''', limit=1)
+            if fina.empty:
+                return {"error": "无法获取财务指标数据"}
+
+            # 获取股票名称和当前价格
+            basic_info = pro.daily(ts_code=ts_code, fields='close,trade_date', limit=1)
+            stock_name = pro.stock_basic(ts_code=ts_code, fields='name').iloc[0]['name']
+
+            # 整合数据
+            latest_daily = daily_basic.iloc[0]
+            latest_fina = fina.iloc[0]
+            latest_price = basic_info.iloc[0]
+
+            analysis_data = {
+                "stock_info": {
+                    "code": stock_code,
+                    "name": stock_name,
+                    "current_price": float(latest_price['close']),
+                    "trade_date": str(latest_price['trade_date'])
+                },
+                "valuation": {
+                    "pe_ratio": float(latest_daily['pe']) if pd.notna(latest_daily['pe']) else None,
+                    "pb_ratio": float(latest_daily['pb']) if pd.notna(latest_daily['pb']) else None,
+                    "ps_ratio": float(latest_daily['ps']) if pd.notna(latest_daily['ps']) else None,
+                    "dividend_yield": float(latest_daily['dv_ratio'])/100 if pd.notna(latest_daily['dv_ratio']) else None,
+                    "total_market_value": float(latest_daily['total_mv'])/10000 if pd.notna(latest_daily['total_mv']) else None  # 转换为亿元
+                },
+                "profitability": {
+                    "roe": float(latest_fina['roe'])/100 if pd.notna(latest_fina['roe']) else None,
+                    "gross_margin": float(latest_fina['grossprofit_margin'])/100 if pd.notna(latest_fina['grossprofit_margin']) else None,
+                    "net_margin": float(latest_fina['netprofit_margin'])/100 if pd.notna(latest_fina['netprofit_margin']) else None
+                },
+                "growth": {
+                    "net_profit_growth": float(latest_fina['netprofit_yoy'])/100 if pd.notna(latest_fina['netprofit_yoy']) else None,
+                    "deducted_net_profit_growth": float(latest_fina['dt_netprofit_yoy'])/100 if pd.notna(latest_fina['dt_netprofit_yoy']) else None,
+                    "revenue_growth": float(latest_fina['tr_yoy'])/100 if pd.notna(latest_fina['tr_yoy']) else None,
+                    "operating_revenue_growth": float(latest_fina['or_yoy'])/100 if pd.notna(latest_fina['or_yoy']) else None
+                },
+                "operation": {
+                    "asset_turnover": float(latest_fina['assets_turn']) if pd.notna(latest_fina['assets_turn']) else None,
+                    "inventory_turnover": float(latest_fina['inv_turn']) if pd.notna(latest_fina['inv_turn']) else None,
+                    "receivables_turnover": float(latest_fina['ar_turn']) if pd.notna(latest_fina['ar_turn']) else None
+                },
+                "solvency": {
+                    "current_ratio": float(latest_fina['current_ratio']) if pd.notna(latest_fina['current_ratio']) else None,
+                    "quick_ratio": float(latest_fina['quick_ratio']) if pd.notna(latest_fina['quick_ratio']) else None,
+                    "debt_to_assets": float(latest_fina['debt_to_assets'])/100 if pd.notna(latest_fina['debt_to_assets']) else None
+                },
+                "cash_flow": {
+                    "ocf_to_revenue": float(latest_fina['ocf_to_or'])/100 if pd.notna(latest_fina['ocf_to_or']) else None,
+                    "ocf_growth": float(latest_fina['ocf_yoy'])/100 if pd.notna(latest_fina['ocf_yoy']) else None
+                },
+                "per_share": {
+                    "eps": float(latest_fina['eps']) if pd.notna(latest_fina['eps']) else None,
+                    "bps": float(latest_fina['bps']) if pd.notna(latest_fina['bps']) else None,
+                    "cfps": float(latest_fina['cfps']) if pd.notna(latest_fina['cfps']) else None,
+                    "ocfps": float(latest_fina['ocfps']) if pd.notna(latest_fina['ocfps']) else None,
+                    "retained_eps": float(latest_fina['retainedps']) if pd.notna(latest_fina['retainedps']) else None
+                }
+            }
+
+            return analysis_data
+
+        except Exception as e:
+            print(f"获取价值投资分析数据失败: {str(e)}")
+            import traceback
+            print(f"详细错误: {traceback.format_exc()}")
+            return {"error": f"获取价值投资分析数据失败: {str(e)}"} 

app/templates/market.html

@@ -0,0 +1,223 @@
+<!DOCTYPE html>
+<html lang="zh">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>指数行情 - 价值投资盯盘系统</title>
+    <link href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css" rel="stylesheet">
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap-icons@1.7.2/font/bootstrap-icons.css">
+    <style>
+        body {
+            background-color: #f8f9fa;
+        }
+        .navbar {
+            background: linear-gradient(135deg, #1e3c72 0%, #2a5298 100%);
+            height: 50px;
+            padding: 0;
+        }
+        .navbar-brand {
+            color: white;
+            font-size: 16px;
+            text-decoration: none;
+            margin-right: 50px;
+        }
+        .navbar-nav {
+            display: flex;
+            list-style: none;
+            margin: 0;
+            padding: 0;
+        }
+        .nav-item {
+            margin-right: 30px;
+        }
+        .nav-link {
+            color: white !important;
+            text-decoration: none;
+            font-size: 14px;
+            line-height: 50px;
+            padding: 0;
+        }
+        .nav-link.active {
+            font-weight: bold;
+        }
+        .iconfont {
+            font-size: 14px;
+            margin-right: 4px;
+        }
+        .index-container {
+            padding: 20px;
+        }
+        .index-grid {
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
+            gap: 20px;
+            margin: 0 auto;
+            max-width: 1400px;
+        }
+        .index-card {
+            background: white;
+            border-radius: 12px;
+            padding: 20px;
+            box-shadow: 0 2px 8px rgba(0,0,0,0.1);
+        }
+        .index-name {
+            font-size: 18px;
+            font-weight: 600;
+            margin-bottom: 10px;
+            color: #1e3c72;
+        }
+        .index-price {
+            font-size: 24px;
+            font-weight: bold;
+        }
+        .index-change {
+            font-size: 14px;
+            padding: 4px 10px;
+            border-radius: 6px;
+            background: rgba(0,0,0,0.05);
+        }
+        .index-chart {
+            width: 100%;
+            height: 200px;
+            margin-top: 15px;
+        }
+        .positive-value {
+            color: #28a745;
+        }
+        .negative-value {
+            color: #dc3545;
+        }
+    </style>
+</head>
+<body>
+    <nav class="navbar navbar-expand navbar-dark">
+        <div class="container">
+            <span class="navbar-brand">
+                <i class="bi bi-graph-up"></i>
+                价值投资盯盘系统
+            </span>
+            <div class="navbar-nav">
+                <a class="nav-link" href="/">监控列表</a>
+                <a class="nav-link active" href="/market">指数行情</a>
+            </div>
+        </div>
+    </nav>
+
+    <div class="index-container">
+        <div class="index-grid" id="indexList">
+            <!-- 指数数据将通过JavaScript动态添加 -->
+        </div>
+    </div>
+
+    <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/js/bootstrap.bundle.min.js"></script>
+    <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script>
+    <script>
+        // 获取指数数据
+        async function refreshIndexData() {
+            try {
+                const response = await fetch('/api/index_info');
+                const data = await response.json();
+                updateIndexDisplay(data);
+            } catch (error) {
+                console.error('获取指数数据失败:', error);
+            }
+        }
+
+        // 更新指数显示
+        function updateIndexDisplay(indexData) {
+            const indexList = document.getElementById('indexList');
+            indexList.innerHTML = '';
+            
+            indexData.forEach(index => {
+                const card = document.createElement('div');
+                card.className = 'index-card';
+                
+                const changeClass = index.change >= 0 ? 'positive-value' : 'negative-value';
+                const changeSign = index.change >= 0 ? '+' : '';
+                
+                card.innerHTML = `
+                    <div class="index-name">${index.name}</div>
+                    <div class="d-flex justify-content-between align-items-center">
+                        <div class="index-price">${index.price.toFixed(2)}</div>
+                        <div class="index-change ${changeClass}">${changeSign}${index.change.toFixed(2)}%</div>
+                    </div>
+                    <div class="index-chart" id="chart_${index.code.replace('.', '_')}"></div>
+                `;
+                
+                indexList.appendChild(card);
+                
+                // 创建K线图
+                setTimeout(() => {
+                    createKlineChart(index.code, index.kline_data);
+                }, 0);
+            });
+        }
+
+        // 创建K线图
+        function createKlineChart(code, klineData) {
+            const chartDom = document.getElementById(`chart_${code.replace('.', '_')}`);
+            const myChart = echarts.init(chartDom);
+            
+            const dates = klineData.map(item => item.date);
+            const data = klineData.map(item => [item.open, item.close, item.low, item.high]);
+            
+            const option = {
+                animation: false,
+                grid: {
+                    left: '8%',
+                    right: '8%',
+                    top: '10%',
+                    bottom: '10%'
+                },
+                xAxis: {
+                    type: 'category',
+                    data: dates,
+                    axisLine: {
+                        lineStyle: {
+                            color: '#ddd'
+                        }
+                    },
+                    axisLabel: {
+                        formatter: value => value.substring(4),
+                        color: '#666'
+                    }
+                },
+                yAxis: {
+                    type: 'value',
+                    scale: true,
+                    splitLine: {
+                        lineStyle: {
+                            color: '#eee'
+                        }
+                    },
+                    axisLabel: {
+                        color: '#666'
+                    }
+                },
+                series: [{
+                    type: 'candlestick',
+                    data: data,
+                    itemStyle: {
+                        color: '#ef5350',
+                        color0: '#26a69a',
+                        borderColor: '#ef5350',
+                        borderColor0: '#26a69a'
+                    }
+                }]
+            };
+            
+            myChart.setOption(option);
+            
+            // 监听窗口大小变化
+            window.addEventListener('resize', () => {
+                myChart.resize();
+            });
+        }
+
+        // 页面加载时获取数据
+        document.addEventListener('DOMContentLoaded', refreshIndexData);
+        // 每分钟更新一次数据
+        setInterval(refreshIndexData, 60000);
+    </script>
+</body>
+</html> 

config.json.example

@@ -0,0 +1,4 @@
+{
+    "watchlist": {},
+    "tushare_token": "your_tushare_token_here"
+} 

requirements.txt

@@ -0,0 +1,54 @@
+aiofiles==23.2.1
+akshare==1.11.22
+annotated-types==0.7.0
+anyio==3.7.1
+baostock==0.8.9
+beautifulsoup4==4.12.3
+bs4==0.0.2
+certifi==2024.12.14
+charset-normalizer==3.4.1
+click==8.1.8
+decorator==5.1.1
+efinance==0.4.8
+et_xmlfile==2.0.0
+fastapi==0.104.1
+h11==0.14.0
+html5lib==1.1
+idna==3.10
+Jinja2==3.1.2
+jsonpath==0.82.2
+lxml==5.3.0
+markdown-it-py==3.0.0
+MarkupSafe==3.0.2
+mdurl==0.1.2
+multitasking==0.0.11
+numpy==2.2.1
+openpyxl==3.1.5
+pandas==2.2.3
+py==1.11.0
+py_mini_racer==0.6.0
+pydantic==2.10.4
+pydantic_core==2.27.2
+Pygments==2.19.1
+pypinyin==0.53.0
+python-dateutil==2.9.0.post0
+python-multipart==0.0.6
+pytz==2024.2
+requests==2.32.3
+retry==0.9.2
+rich==13.9.4
+simplejson==3.19.3
+six==1.17.0
+sniffio==1.3.1
+soupsieve==2.6
+starlette==0.27.0
+tabulate==0.9.0
+tqdm==4.67.1
+tushare==1.4.16
+typing_extensions==4.12.2
+tzdata==2024.2
+urllib3==2.3.0
+uvicorn==0.24.0
+webencodings==0.5.1
+websocket-client==1.8.0
+xlrd==2.0.1

run.py

@@ -0,0 +1,12 @@
+import uvicorn
+from app import app
+
+if __name__ == "__main__":
+    uvicorn.run(
+        "app:app",
+        host="0.0.0.0",
+        port=8000,      # 修改为8000端口
+        reload=True,    # 启用热重载
+        log_level="debug",  # 设置日志级别为debug
+        workers=1       # 开发模式使用单个worker
+    ) 

watchlist.json

@@ -0,0 +1,38 @@
+{
+  "sh600601": {
+    "target_market_value": null,
+    "target_pe": null,
+    "target_pb": null,
+    "target_dividend_yield": null
+  },
+  "sz0024515": {
+    "target_market_value": null,
+    "target_pe": null,
+    "target_pb": null,
+    "target_dividend_yield": null
+  },
+  "sz870199": {
+    "target_market_value": null,
+    "target_pe": null,
+    "target_pb": null,
+    "target_dividend_yield": null
+  },
+  "601318": {
+    "target_market_value": null,
+    "target_pe": null,
+    "target_pb": null,
+    "target_dividend_yield": null
+  },
+  "600601": {
+    "target_market_value": null,
+    "target_pe": null,
+    "target_pb": null,
+    "target_dividend_yield": null
+  },
+  "300059": {
+    "target_market_value": null,
+    "target_pe": null,
+    "target_pb": null,
+    "target_dividend_yield": null
+  }
+}