diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..4a9bb9f --- /dev/null +++ b/.env.example @@ -0,0 +1,7 @@ +# Tushare API配置 +TUSHARE_TOKEN=your_tushare_token_here + +# Volces API配置 +VOLCES_MODEL_ID=your_model_id_here +VOLCES_API_KEY=your_api_key_here +VOLCES_BASE_URL=https://ark.cn-beijing.volces.com/api/v3 \ No newline at end of file diff --git a/.gitignore b/.gitignore index 5724d8b..a5949cf 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,7 @@ +# 环境配置 +.env +config.py + # Python __pycache__/ *.py[cod] @@ -16,14 +20,16 @@ lib64/ parts/ sdist/ var/ -wheels/ *.egg-info/ .installed.cfg *.egg -# 虚拟环境 -venv/ -ENV/ +# 项目特定文件 +stock_cache.json +watchlist.json +ai_stock_analysis/ +dao_analysis/ +daka_analysis/ # IDE .idea/ @@ -31,10 +37,6 @@ ENV/ *.swp *.swo -# 项目特定 -config.json -*.log -.env +# 系统文件 .DS_Store -stock_cache.json -watchlist.json \ No newline at end of file +Thumbs.db \ No newline at end of file diff --git a/README.md b/README.md index b3d4607..4747129 100644 --- a/README.md +++ b/README.md @@ -1,238 +1,158 @@ -# 价值投资盯盘系统 +# AI价值投资盯盘系统 -一个专注于中国 A 股市场的智能股票分析与监控平台，基于 Python FastAPI 开发，集成实时行情监控、AI 智能分析和价值投资建议等功能，助力投资者进行理性的价值投资决策。 +一个基于Python的A股智能监控和AI分析系统，集成了多维度的投资分析功能，包括传统价值投资分析、道德经智慧分析以及知名投资大师的视角分析。 -## 功能特点 +## 系统界面预览 +![系统主界面](docs/images/main.png) -### 1. A股实时监控 -- 支持所有 A 股上市公司的实时监控 -- 沪深两市实时价格和涨跌幅更新 -- 自定义市值目标区间预警 -- 个股交易状态实时提示 +## 🚀 核心功能 -### 2. AI 智能分析 -- 基于中国市场特点的智能投资建议 -- A股市场合理价格区间估算 -- 结合中国经济环境的目标市值评估 -- 多维度分析报告： - - A股市场估值分析 - - 中国特色财务健康状况评估 - - 行业对标成长潜力评估 - - 系统性风险评估 +### 1. 股票监控 +- 实时股票数据监控 +- 自定义目标市值设置 +- 价格和市值预警 +- 多维度指标展示（PE、PB、ROE等） -### 3. A股财务指标分析 -- 估值指标：PE（市盈率）、PB（市净率）、PS（市销率）等 -- 盈利能力：ROE（净资产收益率）、毛利率、净利率 -- 成长能力：营收增长、利润增长、研发投入 -- 运营效率：资产周转率、存货周转率等 -- 偿债能力：资产负债率、流动比率等 -- 现金流指标：经营现金流、自由现金流等 +### 2. 指数行情 +- 主要指数实时行情展示 +- K线图技术分析 +- 大盘趋势分析 -### 4. 中国市场行情 -- 上证指数、深证成指、创业板指等主要指数实时行情 -- 专业K线图技术分析 -- A股市场涨跌分布分析 -- 行业板块轮动分析 +### 3. AI智能分析 +- 基础价值投资分析 + - 财务指标分析 + - 估值分析 + - 风险评估 + - 投资建议 +- 道德经分析视角 + - 企业道德评估 + - 可持续发展分析 + - 长期投资价值判断 +- 价值投资大咖分析 + - 巴菲特视角 + - 格雷厄姆视角 + - 林园视角 + - 李大霄视角 + - 段永平视角 -### 5. 上市公司详情 -- 工商登记信息 -- 十大股东持股变动 -- A股特色财务报表分析 -- 公司公告与重大事项 -- 行业地位分析 +### 4. 数据管理 +- 本地数据缓存 +- 历史数据查询 +- 分析报告导出 +- 自动数据更新 -## 技术架构 +## 🛠️ 技术栈 -### 后端技术栈 -- Web框架：FastAPI -- 数据处理：Pandas -- A股数据源：Tushare API（提供专业的 A 股数据） -- 服务器：Uvicorn -- 数据存储：JSON文件 - -### 前端技术栈 -- 框架：Bootstrap 5 -- 图表：ECharts -- 交互：JavaScript -- 样式：CSS3 - -### 主要模块 -``` -项目结构 -├── app/ -│ ├── __init__.py -│ ├── api/ -│ │ └── stock_routes.py # API路由 -│ ├── models/ -│ │ └── stock.py # 数据模型 -│ ├── services/ -│ │ ├── stock_service.py # 股票服务 -│ │ └── ai_analysis_service.py # AI分析服务 -│ ├── templates/ -│ │ ├── index.html # 主页面 -│ │ └── market.html # 市场页面 -│ └── config.py # 配置文件 -├── run.py # 启动文件 -└── requirements.txt # 依赖包 -``` - -## 安装部署 - -### 环境要求 +### 后端 - Python 3.8+ -- pip 包管理器 -- 网络连接（访问 Tushare API） +- FastAPI：高性能Web框架 +- Tushare：金融数据API +- 豆包大模型：AI分析引擎 +- SQLite：本地数据存储 -### 安装步骤 +### 前端 +- Bootstrap 5：响应式UI框架 +- ECharts：数据可视化 +- jQuery：DOM操作 +- WebSocket：实时数据推送 -1. 克隆项目 +## 📦 安装部署 + +### 1. 环境准备 ```bash -git clone https://github.com/693696817/stock-monitor.git +# 克隆项目 +git clone https://gitee.com/your-username/stock-monitor.git cd stock-monitor -``` -2. 创建虚拟环境（推荐） -```bash +# 创建虚拟环境 python -m venv venv source venv/bin/activate # Linux/Mac -venv\Scripts\activate # Windows -``` +venv\\Scripts\\activate # Windows -3. 安装依赖 -```bash +# 安装依赖 pip install -r requirements.txt ``` -4. 配置 -- 复制 `config.json.example` 为 `config.json` -- 在 `config.json` 中配置你的 Tushare Token -```json -{ - "watchlist": {}, - "tushare_token": "your_tushare_token_here" -} +### 2. API配置获取 + +#### Tushare API +1. 访问 [Tushare官网](https://tushare.pro/) +2. 注册并获取Token +3. 可选：充值获取更高级别权限 + +#### 豆包大模型API +1. 访问 [豆包大模型控制台](https://ark.cn-beijing.volces.com/) +2. 注册企业账号 +3. 创建API Key和Model ID + +### 3. 环境配置 +1. 复制配置文件 +```bash +cp .env.example .env +cp config.template.py config.py ``` -5. 运行 +2. 修改配置文件 +```bash +# 编辑.env文件，填入API密钥 +TUSHARE_TOKEN=your_token_here +VOLCES_MODEL_ID=your_model_id_here +VOLCES_API_KEY=your_api_key_here +``` + +### 4. 启动系统 ```bash python run.py ``` +访问 http://localhost:8000 即可使用系统 -6. 访问 -- 打开浏览器访问 `http://localhost:8000` -- 默认端口为 8000，可在 `run.py` 中修改 +## 🤝 联系作者 -## 使用指南 +如果您对系统有任何问题或建议，欢迎联系： -### 添加监控股票 -1. 在主页面顶部输入 A 股股票代码（6位数字，如：000001） -2. 可选择设置目标市值区间 -3. 点击"添加"按钮开始监控 +- 微信：zyj118 +- QQ：693696817 +- Email：693696817@qq.com -### 查看股票详情 -1. 点击股票名称进入详情页 -2. 查看完整的 A 股特色财务指标 -3. 获取针对中国市场的 AI 投资建议 +## 📝 使用说明 -### 指数行情 -- 实时展示沪深主要指数行情 -- 提供大盘趋势分析 -- 行业板块表现对比 +### 1. 添加监控股票 +1. 在主界面输入股票代码 +2. 设置目标市值范围 +3. 点击添加即可 -### 数据更新频率 -- A股交易时段（9:30-11:30, 13:00-15:00）实时更新 -- 盘后自动更新财务数据 -- 可手动强制刷新最新数据 +### 2. 查看AI分析 +1. 点击股票行右侧的分析按钮 +2. 选择需要的分析维度（基础/道德经/大咖） +3. 等待AI分析结果 -## 开发指南 +### 3. 指数行情查看 +1. 点击顶部导航栏的"指数行情" +2. 查看实时指数数据和K线图 -### 代码规范 -- 遵循 PEP 8 编码规范 -- 使用类型注解 -- 保持代码简洁清晰 +## ⚠️ 注意事项 -### 目录结构说明 -- `api/`: API路由和接口定义 -- `models/`: 数据模型和结构定义 -- `services/`: 业务逻辑和服务实现 -- `templates/`: 前端页面模板 +1. API使用限制 + - Tushare免费账号有调用频率限制 + - 豆包大模型API有Token限制 -### 扩展开发 -1. 添加新的数据源 - - 在 `services` 中添加新的服务类 - - 实现数据获取和处理方法 +2. 数据时效性 + - 行情数据实时更新 + - AI分析结果默认缓存1小时 -2. 扩展AI分析 - - 修改 `ai_analysis_service.py` - - 添加新的分析维度和方法 +3. 系统性能 + - 建议监控股票数量不超过30只 + - 定时刷新间隔建议60秒以上 -3. 自定义UI - - 修改 `templates` 中的HTML文件 - - 更新样式和交互逻辑 - -## 维护说明 - -### 数据更新 -- A股交易时段实时行情更新 -- 每日收盘后自动更新财务数据 -- 定期同步公司公告信息 -- 可配置更新频率 - -### 错误处理 -- 完善的错误提示 -- 异常捕获和处理 -- 日志记录 - -## 贡献指南 - -欢迎提交 Issue 和 Pull Request： -1. Fork 本仓库 -2. 创建特性分支 -3. 提交变更 -4. 发起 Pull Request - -## 许可证 +## 📄 许可证 MIT License -## 联系方式 +## 🤝 贡献指南 -- 作者：ZYJ -- 邮箱：693696817@qq.com +1. Fork 本仓库 +2. 新建 feature_xxx 分支 +3. 提交代码 +4. 新建 Pull Request -## 更新日志 - -### v1.0.0 (2024-03) -- 支持全部 A 股上市公司监控 -- 实现核心功能：实时行情、AI 分析、财务分析 -- 完成基础框架搭建 -- 优化 A 股特色分析逻辑 - -## 配置说明 - -在运行系统之前，需要配置以下API密钥： - -1. **Tushare API Token** - - 访问 [Tushare官网](https://tushare.pro/) - - 注册并登录账号 - - 在个人中心获取Token - - 将Token填入 `config.json` 的 `tushare_token` 字段 - -2. **豆包大模型 API Key** - - 访问 [豆包大模型](https://www.doubao.com/) - - 注册并登录账号 - - 在控制台获取API Key和模型ID - - 将API Key填入 `config.json` 的 `ai_api_key` 字段 - - 将模型ID填入 `config.json` 的 `ai_model_id` 字段 - -配置文件示例 (`config.json`): -```json -{ - "watchlist": {}, - "tushare_token": "your_tushare_token_here", - "ai_api_key": "your_ai_api_key_here", - "ai_model_id": "your_ai_model_id_here" -} -``` - -注意：请妥善保管你的API密钥，不要将其提交到代码仓库中。 \ No newline at end of file +欢迎提交Issue和Pull Request！ \ No newline at end of file diff --git a/app/__init__.py b/app/__init__.py index fb76ee6..c8e2d15 100644 --- a/app/__init__.py +++ b/app/__init__.py @@ -11,7 +11,7 @@ Config.ensure_directories() app = FastAPI() # 设置tushare token -ts.set_token(Config.get_tushare_token()) +ts.set_token(Config.TUSHARE_TOKEN) pro = ts.pro_api() # Mount static files diff --git a/app/api/stock_routes.py b/app/api/stock_routes.py index b908a32..cceaa0d 100644 --- a/app/api/stock_routes.py +++ b/app/api/stock_routes.py @@ -68,7 +68,7 @@ async def get_value_analysis(stock_code: str): return stock_service.get_value_analysis_data(stock_code) @router.get("/api/ai_analysis/{stock_code}") -async def get_ai_analysis(stock_code: str): +async def get_ai_analysis(stock_code: str, force_refresh: bool = False): """获取AI价值投资分析结果""" try: # 首先获取价值分析数据 @@ -77,6 +77,47 @@ async def get_ai_analysis(stock_code: str): return analysis_data # 使用AI服务进行分析 - return ai_service.analyze_value_investment(analysis_data) + return ai_service.analyze_value_investment(analysis_data, force_refresh) except Exception as e: - return {"error": f"AI分析失败: {str(e)}"} \ No newline at end of file + return {"error": f"AI分析失败: {str(e)}"} + +@router.post("/api/update_target") +async def update_target( + stock_code: str = Form(...), + target_market_value_min: Optional[float] = Form(None), + target_market_value_max: Optional[float] = Form(None) +): + """更新股票的目标市值""" + return stock_service.update_target(stock_code, target_market_value_min, target_market_value_max) + +@router.get("/api/tao_analysis/{stock_code}") +async def get_tao_analysis(stock_code: str): + """获取基于道德经的公司分析""" + try: + # 首先获取公司详细信息 + company_info = stock_service.get_company_detail(stock_code) + if "error" in company_info: + return company_info + + # 使用AI服务进行道德经分析 + return ai_service.analyze_tao_philosophy(company_info) + except Exception as e: + return {"error": f"道德经分析失败: {str(e)}"} + +@router.get("/api/master_analysis/{stock_code}") +async def get_master_analysis(stock_code: str): + """获取价值投资大咖的分析结果""" + try: + # 首先获取公司详细信息和财务数据 + company_info = stock_service.get_company_detail(stock_code) + if "error" in company_info: + return company_info + + value_analysis = stock_service.get_value_analysis_data(stock_code) + if "error" in value_analysis: + return value_analysis + + # 使用AI服务进行大咖分析 + return ai_service.analyze_by_masters(company_info, value_analysis) + except Exception as e: + return {"error": f"价值投资大咖分析失败: {str(e)}"} \ No newline at end of file diff --git a/app/config.py b/app/config.py index 2ef8fa0..7ea0fc3 100644 --- a/app/config.py +++ b/app/config.py @@ -1,11 +1,13 @@ import os -import json # 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") @@ -15,29 +17,6 @@ class Config: # 静态文件目录 STATIC_DIR = os.path.join(BASE_DIR, "app", "static") - # API配置 - @classmethod - def load_config(cls): - if os.path.exists(cls.CONFIG_FILE): - with open(cls.CONFIG_FILE, 'r', encoding='utf-8') as f: - return json.load(f) - return {"watchlist": {}} - - @classmethod - def get_tushare_token(cls): - config = cls.load_config() - return config.get('tushare_token') - - @classmethod - def get_ai_api_key(cls): - config = cls.load_config() - return config.get('ai_api_key') - - @classmethod - def get_ai_model_id(cls): - config = cls.load_config() - return config.get('ai_model_id') - # 确保目录存在 @classmethod def ensure_directories(cls): diff --git a/app/services/ai_analysis_service.py b/app/services/ai_analysis_service.py index b6fa63f..a8de894 100644 --- a/app/services/ai_analysis_service.py +++ b/app/services/ai_analysis_service.py @@ -1,24 +1,115 @@ import json import os -import re from openai import OpenAI from app.config import Config class AIAnalysisService: def __init__(self): - self.model = Config.get_ai_model_id() # 从配置获取 model ID + # 配置OpenAI客户端连接到Volces API + self.model = os.getenv('VOLCES_MODEL_ID', 'your_model_id_here') # 从环境变量获取 self.client = OpenAI( - api_key = Config.get_ai_api_key(), # 从配置获取 API Key - base_url = "https://ark.cn-beijing.volces.com/api/v3" + api_key = os.getenv('VOLCES_API_KEY', 'your_api_key_here'), # 从环境变量获取 + base_url = os.getenv('VOLCES_BASE_URL', 'https://ark.cn-beijing.volces.com/api/v3') ) + # 创建AI分析结果缓存目录 + self.cache_dir = os.path.join(Config.BASE_DIR, "ai_stock_analysis") + self.dao_cache_dir = os.path.join(Config.BASE_DIR, "dao_analysis") + self.daka_cache_dir = os.path.join(Config.BASE_DIR, "daka_analysis") - def analyze_value_investment(self, analysis_data): + # 确保所有缓存目录存在 + for directory in [self.cache_dir, self.dao_cache_dir, self.daka_cache_dir]: + if not os.path.exists(directory): + os.makedirs(directory) + + def get_cache_path(self, stock_code: str) -> str: + """获取缓存文件路径""" + return os.path.join(self.cache_dir, f"{stock_code}.json") + + def get_dao_cache_path(self, stock_code: str) -> str: + """获取道德经分析缓存文件路径""" + return os.path.join(self.dao_cache_dir, f"{stock_code}.json") + + def get_daka_cache_path(self, stock_code: str) -> str: + """获取大咖分析缓存文件路径""" + return os.path.join(self.daka_cache_dir, f"{stock_code}.json") + + def load_cache(self, stock_code: str): + """加载缓存的AI分析结果""" + cache_path = self.get_cache_path(stock_code) + if os.path.exists(cache_path): + try: + with open(cache_path, 'r', encoding='utf-8') as f: + return json.load(f) + except Exception as e: + print(f"读取AI分析缓存失败: {str(e)}") + return None + + def save_cache(self, stock_code: str, analysis_result: dict): + """保存AI分析结果到缓存""" + cache_path = self.get_cache_path(stock_code) + try: + with open(cache_path, 'w', encoding='utf-8') as f: + json.dump(analysis_result, f, ensure_ascii=False, indent=4) + except Exception as e: + print(f"保存AI分析缓存失败: {str(e)}") + + def load_dao_cache(self, stock_code: str): + """加载缓存的道德经分析结果""" + cache_path = self.get_dao_cache_path(stock_code) + if os.path.exists(cache_path): + try: + with open(cache_path, 'r', encoding='utf-8') as f: + return json.load(f) + except Exception as e: + print(f"读取道德经分析缓存失败: {str(e)}") + return None + + def save_dao_cache(self, stock_code: str, analysis_result: dict): + """保存道德经分析结果到缓存""" + cache_path = self.get_dao_cache_path(stock_code) + try: + with open(cache_path, 'w', encoding='utf-8') as f: + json.dump(analysis_result, f, ensure_ascii=False, indent=4) + except Exception as e: + print(f"保存道德经分析缓存失败: {str(e)}") + + def load_daka_cache(self, stock_code: str): + """加载缓存的大咖分析结果""" + cache_path = self.get_daka_cache_path(stock_code) + if os.path.exists(cache_path): + try: + with open(cache_path, 'r', encoding='utf-8') as f: + return json.load(f) + except Exception as e: + print(f"读取大咖分析缓存失败: {str(e)}") + return None + + def save_daka_cache(self, stock_code: str, analysis_result: dict): + """保存大咖分析结果到缓存""" + cache_path = self.get_daka_cache_path(stock_code) + try: + with open(cache_path, 'w', encoding='utf-8') as f: + json.dump(analysis_result, f, ensure_ascii=False, indent=4) + except Exception as e: + print(f"保存大咖分析缓存失败: {str(e)}") + + def analyze_value_investment(self, analysis_data: dict, force_refresh: bool = False): """ 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 + :param force_refresh: 是否强制刷新分析结果 :return: AI分析结果 """ try: + stock_code = analysis_data["stock_info"]["code"] + + # 如果不是强制刷新，尝试从缓存加载 + if not force_refresh: + cached_result = self.load_cache(stock_code) + if cached_result: + print(f"从缓存加载AI分析结果: {stock_code}") + return cached_result + # 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)}") @@ -53,16 +144,15 @@ class AIAnalysisService: 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 + # 保存到缓存 + self.save_cache(stock_code, analysis_result) - print(f"最终返回结果: {json.dumps(result, ensure_ascii=False, indent=2)}") - return result + return analysis_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 { + error_result = { 'stock_info': analysis_data.get('stock_info', {}), 'valuation': analysis_data.get('valuation', {}), 'profitability': analysis_data.get('profitability', {}), @@ -76,12 +166,10 @@ class AIAnalysisService: "raw_text": analysis_text } } - + return error_result + 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): @@ -285,7 +373,7 @@ class AIAnalysisService: 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 +2. 某些数据可能缺失或异常，分析时需要谨慎对待，或者从东财choice获取 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： @@ -300,10 +388,332 @@ class AIAnalysisService: 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 +实例： + "price_analysis": { + "合理价格区间": [ + xxx, + xxx + ], + "目标市值区间": [ + xxx, + xxx + ] 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 + + def analyze_tao_philosophy(self, company_info: dict, force_refresh: bool = False): + """ + 基于道德经理念分析公司 + :param company_info: 公司信息 + :param force_refresh: 是否强制刷新分析结果 + :return: AI分析结果 + """ + try: + stock_code = company_info.get('basic_info', {}).get('code') + + # 如果不是强制刷新，尝试从缓存加载 + if not force_refresh and stock_code: + cached_result = self.load_dao_cache(stock_code) + if cached_result: + print(f"从缓存加载道德经分析结果: {stock_code}") + return cached_result + + # 构建提示词 + prompt = self._build_tao_analysis_prompt(company_info) + + # 调用API + response = self.client.chat.completions.create( + model=self.model, + messages=[ + { + "role": "user", + "content": prompt + } + ] + ) + + # 获取分析结果 + analysis_text = response.choices[0].message.content + + try: + # 解析JSON结果 + analysis_result = json.loads(analysis_text) + + # 保存到缓存 + if stock_code: + self.save_dao_cache(stock_code, analysis_result) + + return analysis_result + except json.JSONDecodeError as e: + print(f"道德经分析结果JSON解析失败: {str(e)}") + return {"error": "分析结果格式错误"} + + except Exception as e: + print(f"道德经分析失败: {str(e)}") + return {"error": f"道德经分析失败: {str(e)}"} + + def _build_tao_analysis_prompt(self, company_info: dict): + """ + 构建道德经分析提示词 + """ + basic_info = company_info.get('basic_info', {}) + + prompt = f"""请作为一位精通道德经的智者，运用道德经的智慧来分析{basic_info.get('name', '')}({basic_info.get('code', '')})这家公司。 + +公司基本信息： +- 公司名称：{basic_info.get('name', '')} +- 所属行业：{basic_info.get('industry', '')} +- 主营业务：{basic_info.get('main_business', '')} +- 经营范围：{basic_info.get('business_scope', '')} +- 公司简介：{basic_info.get('introduction', '')} + +请从道德经的智慧角度，分析以下几个方面： + +1. 道德经视角： +- 公司的经营理念是否符合"道法自然"的原则 +- 企业的发展是否遵循"无为而治"的智慧 +- 公司是否体现"上善若水"的品质 +- 管理方式是否符合"柔弱胜刚强"的道理 + +2. 企业道德评估： +- 公司对待员工、客户、供应商的态度 +- 企业的社会责任感和可持续发展理念 +- 公司的价值观和企业文化 +- 经营中的道德风险评估 + +3. 投资建议： +- 基于道德经智慧的投资建议 +- 长期发展潜力分析 +- 需要关注的风险点 +- 持有建议 + +请以JSON格式返回分析结果，包含以下字段： +1. tao_philosophy: 道德经视角的分析 +2. business_ethics: 企业道德评估 +3. investment_advice: 投资建议 + +分析要客观、专业、深入，同时体现道德经的智慧。""" + + return prompt + + def analyze_by_masters(self, company_info: dict, value_analysis: dict, force_refresh: bool = False): + """ + 基于各位价值投资大咖的理念分析公司 + :param company_info: 公司信息 + :param value_analysis: 价值分析数据 + :param force_refresh: 是否强制刷新分析结果 + :return: AI分析结果 + """ + try: + stock_code = company_info.get('basic_info', {}).get('code') + + # 如果不是强制刷新，尝试从缓存加载 + if not force_refresh and stock_code: + cached_result = self.load_daka_cache(stock_code) + if cached_result: + print(f"从缓存加载大咖分析结果: {stock_code}") + return cached_result + + # 打印输入数据用于调试 + print(f"公司信息: {json.dumps(company_info, ensure_ascii=False, indent=2)}") + print(f"价值分析数据: {json.dumps(value_analysis, ensure_ascii=False, indent=2)}") + + # 构建提示词 + prompt = self._build_masters_analysis_prompt(company_info, value_analysis) + + # 打印提示词用于调试 + print(f"大咖分析提示词: {prompt}") + + # 调用API + response = self.client.chat.completions.create( + model=self.model, + messages=[ + { + "role": "user", + "content": 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: + # 解析JSON结果 + analysis_result = json.loads(analysis_text) + print(f"解析后的JSON结果: {json.dumps(analysis_result, ensure_ascii=False, indent=2)}") + + # 保存到缓存 + if stock_code: + self.save_daka_cache(stock_code, analysis_result) + + return analysis_result + except json.JSONDecodeError as e: + print(f"大咖分析结果JSON解析失败: {str(e)}") + return {"error": "分析结果格式错误"} + + except Exception as e: + print(f"价值投资大咖分析失败: {str(e)}") + return {"error": f"价值投资大咖分析失败: {str(e)}"} + + def _build_masters_analysis_prompt(self, company_info: dict, value_analysis: dict): + """ + 构建价值投资大咖分析提示词 + """ + basic_info = company_info.get('basic_info', {}) + + # 从value_analysis中获取财务数据 + valuation = value_analysis.get('valuation', {}) + profitability = value_analysis.get('profitability', {}) + growth = value_analysis.get('growth', {}) + operation = value_analysis.get('operation', {}) + solvency = value_analysis.get('solvency', {}) + cash_flow = value_analysis.get('cash_flow', {}) + per_share = value_analysis.get('per_share', {}) + stock_info = value_analysis.get('stock_info', {}) + + # 格式化百分比 + def format_percent(value): + if value is None: + return '-' + try: + if isinstance(value, str): + value = float(value) + if abs(value) <= 1: + value = value * 100 + return f"{value:.2f}%" + except: + return '-' + + # 格式化数字 + def format_number(value): + if value is None: + return '-' + try: + if isinstance(value, str): + value = float(value) + return f"{value:.4f}" + except: + return '-' + + prompt = f"""请分别以五位价值投资大咖的视角，分析{basic_info.get('name', '')}({basic_info.get('code', '')})这家公司。 + +公司基本信息： +- 公司名称：{basic_info.get('name', '')} +- 所属行业：{basic_info.get('industry', '')} +- 主营业务：{basic_info.get('main_business', '')} +- 经营范围：{basic_info.get('business_scope', '')} +- 公司简介：{basic_info.get('introduction', '')} +- 法人代表：{basic_info.get('chairman', '')} +- 总经理：{basic_info.get('manager', '')} +- 注册资本：{basic_info.get('reg_capital', '')}万元 +- 员工人数：{basic_info.get('employees', '')}人 +- 成立日期：{basic_info.get('setup_date', '')} +- 上市日期：{basic_info.get('list_date', '')} + +当前市场信息： +- 当前股价：{format_number(stock_info.get('current_price'))}元 +- 总市值：{format_number(valuation.get('total_market_value'))}亿元 +- 流通市值：{format_number(valuation.get('circulating_market_value'))}亿元 +- 流通比例：{format_percent(valuation.get('circulating_ratio'))} +- 换手率：{format_percent(stock_info.get('turnover_ratio'))} + +估值指标： +- 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'))} + +盈利能力指标： +- ROE：{format_percent(profitability.get('roe'))} +- ROE(扣非)：{format_percent(profitability.get('deducted_roe'))} +- ROA：{format_percent(profitability.get('roa'))} +- 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'))} +- 营业总收入增长率：{format_percent(growth.get('revenue_growth'))} +- 营业收入增长率：{format_percent(growth.get('operating_revenue_growth'))} + +运营能力指标： +- 总资产周转率：{format_number(operation.get('asset_turnover'))} +- 存货周转率：{format_number(operation.get('inventory_turnover'))} +- 应收账款周转率：{format_number(operation.get('receivables_turnover'))} +- 流动资产周转率：{format_number(operation.get('current_asset_turnover'))} + +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'))} +- 产权比率：{format_number(solvency.get('equity_ratio'))} + +现金流指标： +- 经营现金流/营收：{format_percent(cash_flow.get('ocf_to_revenue'))} +- 经营现金流/经营利润：{format_percent(cash_flow.get('ocf_to_operating_profit'))} +- 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 +- 每股收益(扣非)：{format_number(per_share.get('deducted_eps'))}元 +- 每股净资产：{format_number(per_share.get('bps'))}元 +- 每股经营现金流：{format_number(per_share.get('ocfps'))}元 +- 每股留存收益：{format_number(per_share.get('retained_eps'))}元 +- 每股现金流量：{format_number(per_share.get('cfps'))}元 +- 每股息税前利润：{format_number(per_share.get('ebit_ps'))}元 + +请分别从以下五位投资大师的视角进行分析： + +1. 巴菲特视角： +- 是否具有护城河（品牌优势、规模效应、专利技术等） +- 管理层能力和诚信（从财务指标、现金流等反映的经营能力） +- 业务是否容易理解（商业模式的清晰度） +- 长期竞争优势（市场地位、核心竞争力） +- 是否是好生意（盈利能力、现金流状况） +- 以合理价格购买优秀企业的原则（估值分析） + +2. 格雷厄姆视角： +- 安全边际分析（基于净资产、市盈率等） +- 内在价值计算（基于盈利能力和资产价值） +- 财务安全性（偿债能力、资产质量） +- 是否具有投资价值（基于定量分析） +- 基于定量分析的结论（综合财务指标评估） + +3. 林园视角： +- 行业成长性（收入增长、利润增长） +- 公司治理结构（股权结构、管理层背景） +- 研发创新能力（技术优势、产品创新） +- 市场竞争格局（市场份额、竞争态势） +- 估值是否合理（相对估值和绝对估值） + +4. 李大霄视角： +- 市场地位和品牌价值（行业地位、品牌影响力） +- 行业发展趋势（产业政策、市场空间） +- 政策影响分析（行业政策、监管环境） +- 投资时机把握（技术面和基本面） +- 投资建议（综合分析结论） + +5. 段永平视角： +- 商业模式分析（盈利模式、竞争优势） +- 用户价值（产品力、客户粘性） +- 企业文化（管理理念、团队建设） +- 长期发展潜力（成长空间、持续经营能力） +- 是否值得长期持有（投资价值判断） + +请以JSON格式返回分析结果，包含以下字段： +1. buffett_analysis: 巴菲特的分析观点 +2. graham_analysis: 格雷厄姆的分析观点 +3. lin_yuan_analysis: 林园的分析观点 +4. li_daxiao_analysis: 李大霄的分析观点 +5. duan_yongping_analysis: 段永平的分析观点 + +分析要客观、专业、深入，并体现每位投资大师的独特投资理念。请基于上述详细的财务数据进行分析（如果指标缺失或异常，请联网获取），尤其是定量指标的解读。""" + return prompt \ No newline at end of file diff --git a/app/services/stock_service.py b/app/services/stock_service.py index 7fa008a..a24fa6a 100644 --- a/app/services/stock_service.py +++ b/app/services/stock_service.py @@ -226,6 +226,20 @@ class StockService: self._save_watchlist() return {"status": "success"} + def update_target(self, stock_code: str, target_market_value_min: float = None, target_market_value_max: float = None): + """更新股票的目标市值""" + if stock_code not in self.watchlist: + return {"error": "股票不在监控列表中"} + + self.watchlist[stock_code] = { + "target_market_value": { + "min": target_market_value_min, + "max": target_market_value_max + } + } + self._save_watchlist() + return {"status": "success"} + def get_index_info(self): """获取主要指数数据""" try: diff --git a/app/templates/index.html b/app/templates/index.html index 5928e94..c976c2d 100644 --- a/app/templates/index.html +++ b/app/templates/index.html @@ -642,8 +642,13 @@
-
- AI价值投资分析 +
+
+ AI价值投资分析 +
+
@@ -785,6 +790,203 @@
+ + + + + + + + + \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..f3dfc8e --- /dev/null +++ b/config.json @@ -0,0 +1,178 @@ +{ + "watchlist": { + "300059": { + "target_market_value": { + "min": 2500.0, + "max": 2800.0 + } + }, + "601318": { + "target_market_value": { + "min": 8000.0, + "max": 9500.0 + } + }, + "000963": { + "target_market_value": { + "min": 500.0, + "max": 650.0 + } + }, + "002415": { + "target_market_value": { + "min": 2000.0, + "max": 2200.0 + } + }, + "000423": { + "target_market_value": { + "min": 270.0, + "max": 330.0 + } + }, + "000538": { + "target_market_value": { + "min": 807.0, + "max": 1210.0 + } + }, + "600085": { + "target_market_value": { + "min": 336.0, + "max": 429.0 + } + }, + "002714": { + "target_market_value": { + "min": 1650.0, + "max": 2200.0 + } + }, + "002007": { + "target_market_value": { + "min": 240.0, + "max": 288.0 + } + }, + "600132": { + "target_market_value": { + "min": 220.0, + "max": 290.0 + } + }, + "002049": { + "target_market_value": { + "min": 360.0, + "max": 480.0 + } + }, + "600436": { + "target_market_value": { + "min": 960.0, + "max": 1080.0 + } + }, + "002216": { + "target_market_value": { + "min": 72.0, + "max": 97.0 + } + }, + "601966": { + "target_market_value": { + "min": 220.0, + "max": 280.0 + } + }, + "603195": { + "target_market_value": { + "min": 730.0, + "max": 950.0 + } + }, + "000001": { + "target_market_value": { + "min": 1800.0, + "max": 2500.0 + } + }, + "600867": { + "target_market_value": { + "min": 120.0, + "max": 160.0 + } + }, + "603087": { + "target_market_value": { + "min": 170.0, + "max": 283.0 + } + }, + "603290": { + "target_market_value": { + "min": 150.0, + "max": 200.0 + } + }, + "600332": { + "target_market_value": { + "min": 380.0, + "max": 460.0 + } + }, + "300124": { + "target_market_value": { + "min": 1200.0, + "max": 1400.0 + } + }, + "300146": { + "target_market_value": { + "min": 150.0, + "max": 200.0 + } + }, + "000999": { + "target_market_value": { + "min": 450.0, + "max": 580.0 + } + }, + "002466": { + "target_market_value": { + "min": 330.0, + "max": 415.0 + } + }, + "300009": { + "target_market_value": { + "min": 120.0, + "max": 160.0 + } + }, + "300743": { + "target_market_value": { + "min": null, + "max": null + } + }, + "603511": { + "target_market_value": { + "min": null, + "max": null + } + }, + "688553": { + "target_market_value": { + "min": null, + "max": null + } + }, + "600030": { + "target_market_value": { + "min": 3200.0, + "max": 3600.0 + } + } + } +} \ No newline at end of file diff --git a/config.json.example b/config.json.example deleted file mode 100644 index 53ceb1c..0000000 --- a/config.json.example +++ /dev/null @@ -1,6 +0,0 @@ -{ - "watchlist": {}, - "tushare_token": "your_tushare_token_here", - "ai_api_key": "your_ai_api_key_here", - "ai_model_id": "your_ai_model_id_here" -} \ No newline at end of file diff --git a/config.template.py b/config.template.py new file mode 100644 index 0000000..1a31d78 --- /dev/null +++ b/config.template.py @@ -0,0 +1,12 @@ +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 = 'your_tushare_token_here' + + # 配置文件路径 + CONFIG_FILE = os.path.join(BASE_DIR, "config.json") \ No newline at end of file diff --git a/docs/images/main.png b/docs/images/main.png new file mode 100644 index 0000000..7340536 Binary files /dev/null and b/docs/images/main.png differ diff --git a/requirements.txt b/requirements.txt index 3740e72..f0ff2a2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,11 +1,51 @@ +aiofiles==23.2.1 +annotated-types==0.7.0 +anyio==3.7.1 +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 +et_xmlfile==1.0.0 fastapi==0.104.1 -uvicorn==0.24.0 -python-multipart==0.0.6 -pydantic==2.10.4 -requests==2.32.3 -pandas==2.2.3 -numpy==2.2.1 -tushare==1.4.16 +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 diff --git a/stock_cache.json b/stock_cache.json index 6f39f01..7167ba4 100644 --- a/stock_cache.json +++ b/stock_cache.json @@ -4,13 +4,13 @@ "stock_info": { "code": "300059", "name": "东方财富", - "market_value": 3491.76, - "pe_ratio": 42.62, - "pb_ratio": 4.54, - "ps_ratio": 89.81, - "dividend_yield": 0.0018, - "price": 22.12, - "change_percent": 0.011, + "market_value": 3766.43, + "pe_ratio": 45.97, + "pb_ratio": 4.9, + "ps_ratio": 96.88, + "dividend_yield": 0.0017, + "price": 23.86, + "change_percent": 0.0787, "roe": 0.0811, "gross_profit_margin": 0.8372, "net_profit_margin": 2.694, @@ -28,20 +28,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "601318": { "data": { "stock_info": { "code": "601318", "name": "中国平安", - "market_value": 8848.35, - "pe_ratio": 10.33, - "pb_ratio": 0.99, - "ps_ratio": 0.97, - "dividend_yield": 0.0498, - "price": 48.59, - "change_percent": -0.0074, + "market_value": 8988.57, + "pe_ratio": 10.49, + "pb_ratio": 1.01, + "ps_ratio": 0.98, + "dividend_yield": 0.0491, + "price": 49.36, + "change_percent": 0.0158, "roe": 0.1319, "gross_profit_margin": 0, "net_profit_margin": 0.1806, @@ -59,20 +59,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "600085": { "data": { "stock_info": { "code": "600085", "name": "同仁堂", - "market_value": 507.86, - "pe_ratio": 30.43, - "pb_ratio": 4.13, - "ps_ratio": 2.84, - "dividend_yield": 0.027, - "price": 37.03, - "change_percent": 0.0082, + "market_value": 519.24, + "pe_ratio": 31.11, + "pb_ratio": 4.22, + "ps_ratio": 2.91, + "dividend_yield": 0.0264, + "price": 37.86, + "change_percent": 0.0224, "roe": 0.1037, "gross_profit_margin": 0.437, "net_profit_margin": 0.1435, @@ -90,20 +90,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "002714": { "data": { "stock_info": { "code": "002714", "name": "牧原股份", - "market_value": 1980.25, + "market_value": 2023.41, "pe_ratio": 0, - "pb_ratio": 2.97, - "ps_ratio": 1.79, - "dividend_yield": 0.0227, - "price": 36.25, - "change_percent": 0.0014, + "pb_ratio": 3.04, + "ps_ratio": 1.83, + "dividend_yield": 0.0223, + "price": 37.04, + "change_percent": 0.0218, "roe": 0.1552, "gross_profit_margin": 0.1727, "net_profit_margin": 0.1162, @@ -121,20 +121,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "000538": { "data": { "stock_info": { "code": "000538", "name": "云南白药", - "market_value": 1001.86, - "pe_ratio": 24.47, - "pb_ratio": 2.61, - "ps_ratio": 2.56, - "dividend_yield": 0.0586, - "price": 56.15, - "change_percent": -0.0083, + "market_value": 1024.17, + "pe_ratio": 25.02, + "pb_ratio": 2.67, + "ps_ratio": 2.62, + "dividend_yield": 0.0573, + "price": 57.4, + "change_percent": 0.0223, "roe": 0.1076, "gross_profit_margin": 0.284, "net_profit_margin": 0.1447, @@ -152,20 +152,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "000423": { "data": { "stock_info": { "code": "000423", "name": "东阿阿胶", - "market_value": 391.86, - "pe_ratio": 34.05, - "pb_ratio": 3.95, - "ps_ratio": 8.31, - "dividend_yield": 0.0481, - "price": 60.85, - "change_percent": -0.0178, + "market_value": 398.75, + "pe_ratio": 34.65, + "pb_ratio": 4.02, + "ps_ratio": 8.46, + "dividend_yield": 0.0472, + "price": 61.92, + "change_percent": 0.0176, "roe": 0.1117, "gross_profit_margin": 0.7413, "net_profit_margin": 0.2661, @@ -183,20 +183,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "000963": { "data": { "stock_info": { "code": "000963", "name": "华东医药", - "market_value": 567.33, - "pe_ratio": 19.98, - "pb_ratio": 2.57, - "ps_ratio": 1.4, - "dividend_yield": 0.0288, - "price": 32.34, - "change_percent": -0.0089, + "market_value": 582.24, + "pe_ratio": 20.51, + "pb_ratio": 2.64, + "ps_ratio": 1.43, + "dividend_yield": 0.028, + "price": 33.19, + "change_percent": 0.0263, "roe": 0.1189, "gross_profit_margin": 0.3255, "net_profit_margin": 0.0814, @@ -214,20 +214,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "002415": { "data": { "stock_info": { "code": "002415", "name": "海康威视", - "market_value": 2554.83, - "pe_ratio": 18.11, - "pb_ratio": 3.33, - "ps_ratio": 2.86, - "dividend_yield": 0.0329, - "price": 27.67, - "change_percent": -0.0047, + "market_value": 2618.54, + "pe_ratio": 18.56, + "pb_ratio": 3.41, + "ps_ratio": 2.93, + "dividend_yield": 0.0321, + "price": 28.36, + "change_percent": 0.0249, "roe": 0.1059, "gross_profit_margin": 0.4476, "net_profit_margin": 0.1371, @@ -245,20 +245,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "002007": { "data": { "stock_info": { "code": "002007", "name": "华兰生物", - "market_value": 284.92, - "pe_ratio": 19.23, - "pb_ratio": 2.44, - "ps_ratio": 5.33, - "dividend_yield": 0.0193, - "price": 15.58, - "change_percent": -0.0133, + "market_value": 291.32, + "pe_ratio": 19.66, + "pb_ratio": 2.49, + "ps_ratio": 5.45, + "dividend_yield": 0.0188, + "price": 15.93, + "change_percent": 0.0225, "roe": 0.0801, "gross_profit_margin": 0.6177, "net_profit_margin": 0.2897, @@ -276,20 +276,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "600132": { "data": { "stock_info": { "code": "600132", "name": "重庆啤酒", - "market_value": 277.32, - "pe_ratio": 20.75, - "pb_ratio": 19.67, - "ps_ratio": 1.87, - "dividend_yield": 0.075, - "price": 57.3, - "change_percent": 0.0145, + "market_value": 281.28, + "pe_ratio": 21.04, + "pb_ratio": 19.95, + "ps_ratio": 1.9, + "dividend_yield": 0.074, + "price": 58.12, + "change_percent": 0.0143, "roe": 0.623, "gross_profit_margin": 0.492, "net_profit_margin": 0.2041, @@ -302,25 +302,25 @@ }, "targets": { "target_market_value": { - "min": 225.0, - "max": 260.0 + "min": 220.0, + "max": 290.0 } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "002049": { "data": { "stock_info": { "code": "002049", "name": "紫光国微", - "market_value": 492.36, - "pe_ratio": 19.46, - "pb_ratio": 4.1, - "ps_ratio": 6.51, - "dividend_yield": 0.0116, - "price": 57.95, - "change_percent": -0.0113, + "market_value": 508.67, + "pe_ratio": 20.1, + "pb_ratio": 4.24, + "ps_ratio": 6.72, + "dividend_yield": 0.0113, + "price": 59.87, + "change_percent": 0.0331, "roe": 0.0847, "gross_profit_margin": 0.5681, "net_profit_margin": 0.2383, @@ -338,20 +338,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "600436": { "data": { "stock_info": { "code": "600436", "name": "片仔癀", - "market_value": 1236.8, - "pe_ratio": 44.21, - "pb_ratio": 9.28, - "ps_ratio": 12.3, - "dividend_yield": 0.0169, - "price": 205.0, - "change_percent": 0.0029, + "market_value": 1261.9, + "pe_ratio": 45.11, + "pb_ratio": 9.47, + "ps_ratio": 12.55, + "dividend_yield": 0.0166, + "price": 209.16, + "change_percent": 0.0203, "roe": 0.1961, "gross_profit_margin": 0.4544, "net_profit_margin": 0.3216, @@ -369,20 +369,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "002216": { "data": { "stock_info": { "code": "002216", "name": "三全食品", - "market_value": 97.77, - "pe_ratio": 13.05, - "pb_ratio": 2.28, - "ps_ratio": 1.39, - "dividend_yield": 0.045, - "price": 11.12, - "change_percent": 0.0091, + "market_value": 100.14, + "pe_ratio": 13.36, + "pb_ratio": 2.34, + "ps_ratio": 1.42, + "dividend_yield": 0.0439, + "price": 11.39, + "change_percent": 0.0243, "roe": 0.0914, "gross_profit_margin": 0.2503, "net_profit_margin": 0.0769, @@ -396,24 +396,24 @@ "targets": { "target_market_value": { "min": 72.0, - "max": 96.0 + "max": 97.0 } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "601966": { "data": { "stock_info": { "code": "601966", "name": "玲珑轮胎", - "market_value": 251.87, - "pe_ratio": 18.11, - "pb_ratio": 1.18, - "ps_ratio": 1.25, - "dividend_yield": 0.0371, - "price": 17.21, - "change_percent": -0.0023, + "market_value": 257.87, + "pe_ratio": 18.54, + "pb_ratio": 1.2, + "ps_ratio": 1.28, + "dividend_yield": 0.0363, + "price": 17.62, + "change_percent": 0.0238, "roe": 0.0801, "gross_profit_margin": 0.2435, "net_profit_margin": 0.1073, @@ -431,20 +431,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "603195": { "data": { "stock_info": { "code": "603195", "name": "公牛集团", - "market_value": 861.35, - "pe_ratio": 22.26, - "pb_ratio": 5.8, - "ps_ratio": 5.49, - "dividend_yield": 0.0321, - "price": 66.66, - "change_percent": -0.0141, + "market_value": 875.57, + "pe_ratio": 22.62, + "pb_ratio": 5.9, + "ps_ratio": 5.58, + "dividend_yield": 0.0316, + "price": 67.76, + "change_percent": 0.0165, "roe": 0.2228, "gross_profit_margin": 0.4312, "net_profit_margin": 0.2589, @@ -462,20 +462,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "000001": { "data": { "stock_info": { "code": "000001", "name": "平安银行", - "market_value": 2173.46, - "pe_ratio": 4.68, - "pb_ratio": 0.52, - "ps_ratio": 1.32, - "dividend_yield": 0.0862, - "price": 11.2, - "change_percent": -0.0089, + "market_value": 2208.39, + "pe_ratio": 4.75, + "pb_ratio": 0.53, + "ps_ratio": 1.34, + "dividend_yield": 0.0848, + "price": 11.38, + "change_percent": 0.0161, "roe": 0.0825, "gross_profit_margin": 0, "net_profit_margin": 0.3561, @@ -488,25 +488,25 @@ }, "targets": { "target_market_value": { - "min": 2300.0, - "max": 2800.0 + "min": 1800.0, + "max": 2500.0 } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "600867": { "data": { "stock_info": { "code": "600867", "name": "通化东宝", - "market_value": 145.52, - "pe_ratio": 12.46, - "pb_ratio": 2.33, - "ps_ratio": 4.73, - "dividend_yield": 0.034, - "price": 7.43, - "change_percent": 0.0095, + "market_value": 150.22, + "pe_ratio": 12.86, + "pb_ratio": 2.41, + "ps_ratio": 4.88, + "dividend_yield": 0.033, + "price": 7.67, + "change_percent": 0.0323, "roe": -0.0097, "gross_profit_margin": 0.7447, "net_profit_margin": -0.0459, @@ -524,20 +524,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "603087": { "data": { "stock_info": { "code": "603087", "name": "甘李药业", - "market_value": 250.34, - "pe_ratio": 73.62, - "pb_ratio": 2.3, - "ps_ratio": 9.6, - "dividend_yield": 0.0168, - "price": 41.65, - "change_percent": 0.0161, + "market_value": 258.16, + "pe_ratio": 75.91, + "pb_ratio": 2.37, + "ps_ratio": 9.9, + "dividend_yield": 0.0163, + "price": 42.95, + "change_percent": 0.0312, "roe": 0.0462, "gross_profit_margin": 0.7536, "net_profit_margin": 0.226, @@ -555,20 +555,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "603290": { "data": { "stock_info": { "code": "603290", "name": "斯达半导", - "market_value": 193.85, - "pe_ratio": 21.29, - "pb_ratio": 2.94, - "ps_ratio": 5.29, - "dividend_yield": 0.0141, - "price": 80.95, - "change_percent": 0.0021, + "market_value": 202.52, + "pe_ratio": 22.24, + "pb_ratio": 3.07, + "ps_ratio": 5.53, + "dividend_yield": 0.0135, + "price": 84.57, + "change_percent": 0.0447, "roe": 0.065, "gross_profit_margin": 0.3169, "net_profit_margin": 0.1773, @@ -586,20 +586,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "600332": { "data": { "stock_info": { "code": "600332", "name": "白云山", - "market_value": 433.11, - "pe_ratio": 10.68, - "pb_ratio": 1.22, - "ps_ratio": 0.57, - "dividend_yield": 0.0431, - "price": 26.64, - "change_percent": 0.0019, + "market_value": 442.54, + "pe_ratio": 10.91, + "pb_ratio": 1.24, + "ps_ratio": 0.59, + "dividend_yield": 0.0422, + "price": 27.22, + "change_percent": 0.0218, "roe": 0.0888, "gross_profit_margin": 0.177, "net_profit_margin": 0.0557, @@ -617,20 +617,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "300124": { "data": { "stock_info": { "code": "300124", "name": "汇川技术", - "market_value": 1570.93, - "pe_ratio": 33.13, - "pb_ratio": 5.86, - "ps_ratio": 5.16, - "dividend_yield": 0.0077, - "price": 58.35, - "change_percent": -0.0273, + "market_value": 1663.81, + "pe_ratio": 35.09, + "pb_ratio": 6.21, + "ps_ratio": 5.47, + "dividend_yield": 0.0072, + "price": 61.8, + "change_percent": 0.0591, "roe": 0.1316, "gross_profit_margin": 0.3102, "net_profit_margin": 0.1345, @@ -648,20 +648,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "300146": { "data": { "stock_info": { "code": "300146", "name": "汤臣倍健", - "market_value": 192.2, - "pe_ratio": 11.01, - "pb_ratio": 1.7, - "ps_ratio": 2.04, - "dividend_yield": 0.0789, - "price": 11.3, - "change_percent": 0.0116, + "market_value": 198.49, + "pe_ratio": 11.37, + "pb_ratio": 1.75, + "ps_ratio": 2.11, + "dividend_yield": 0.0764, + "price": 11.67, + "change_percent": 0.0327, "roe": 0.074, "gross_profit_margin": 0.6793, "net_profit_margin": 0.1504, @@ -679,20 +679,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "000999": { "data": { "stock_info": { "code": "000999", "name": "华润三九", - "market_value": 546.6, - "pe_ratio": 19.16, - "pb_ratio": 2.84, - "ps_ratio": 2.21, - "dividend_yield": 0.0506, - "price": 42.56, - "change_percent": -0.0014, + "market_value": 557.39, + "pe_ratio": 19.54, + "pb_ratio": 2.9, + "ps_ratio": 2.25, + "dividend_yield": 0.0496, + "price": 43.4, + "change_percent": 0.0197, "roe": 0.1499, "gross_profit_margin": 0.5268, "net_profit_margin": 0.1644, @@ -710,7 +710,7 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "000516": { "data": { @@ -748,13 +748,13 @@ "stock_info": { "code": "002466", "name": "天齐锂业", - "market_value": 529.95, - "pe_ratio": 7.26, - "pb_ratio": 1.22, - "ps_ratio": 1.31, - "dividend_yield": 0.0418, - "price": 32.29, - "change_percent": 0.0416, + "market_value": 541.44, + "pe_ratio": 7.42, + "pb_ratio": 1.24, + "ps_ratio": 1.34, + "dividend_yield": 0.0409, + "price": 32.99, + "change_percent": 0.0217, "roe": -0.12, "gross_profit_margin": 0.4903, "net_profit_margin": 0.1723, @@ -772,7 +772,7 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "index_data": { "data": { @@ -2130,13 +2130,13 @@ "stock_info": { "code": "300009", "name": "安科生物", - "market_value": 135.81, - "pe_ratio": 16.03, - "pb_ratio": 3.47, - "ps_ratio": 4.74, - "dividend_yield": 0.0308, - "price": 8.12, - "change_percent": 0.01, + "market_value": 139.66, + "pe_ratio": 16.48, + "pb_ratio": 3.56, + "ps_ratio": 4.87, + "dividend_yield": 0.0299, + "price": 8.35, + "change_percent": 0.0283, "roe": 0.1537, "gross_profit_margin": 0.7775, "net_profit_margin": 0.3122, @@ -2149,25 +2149,25 @@ }, "targets": { "target_market_value": { - "min": null, - "max": null + "min": 120.0, + "max": 160.0 } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "300743": { "data": { "stock_info": { "code": "300743", "name": "天地数码", - "market_value": 21.74, - "pe_ratio": 39.08, - "pb_ratio": 3.57, - "ps_ratio": 3.38, - "dividend_yield": 0.0241, - "price": 14.17, - "change_percent": 0.0093, + "market_value": 22.94, + "pe_ratio": 41.23, + "pb_ratio": 3.76, + "ps_ratio": 3.56, + "dividend_yield": 0.0229, + "price": 14.95, + "change_percent": 0.055, "roe": 0.1209, "gross_profit_margin": 0.3493, "net_profit_margin": 0.1335, @@ -2185,20 +2185,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "603511": { "data": { "stock_info": { "code": "603511", "name": "爱慕股份", - "market_value": 46.23, - "pe_ratio": 15.12, - "pb_ratio": 1.05, - "ps_ratio": 1.35, - "dividend_yield": 0.0662, - "price": 11.37, - "change_percent": -0.0026, + "market_value": 50.86, + "pe_ratio": 16.64, + "pb_ratio": 1.16, + "ps_ratio": 1.48, + "dividend_yield": 0.0602, + "price": 12.51, + "change_percent": 0.1003, "roe": 0.0317, "gross_profit_margin": 0.6597, "net_profit_margin": 0.0615, @@ -2216,20 +2216,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "688553": { "data": { "stock_info": { "code": "688553", "name": "汇宇制药-W", - "market_value": 58.37, - "pe_ratio": 41.76, - "pb_ratio": 1.5, - "ps_ratio": 6.3, + "market_value": 60.79, + "pe_ratio": 43.49, + "pb_ratio": 1.57, + "ps_ratio": 6.56, "dividend_yield": 0.0, - "price": 13.78, - "change_percent": 0.0117, + "price": 14.35, + "change_percent": 0.0414, "roe": 0.0594, "gross_profit_margin": 0.8315, "net_profit_margin": 0.2592, @@ -2247,20 +2247,20 @@ } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" }, "600030": { "data": { "stock_info": { "code": "600030", "name": "中信证券", - "market_value": 3928.93, - "pe_ratio": 19.92, - "pb_ratio": 1.53, - "ps_ratio": 6.54, - "dividend_yield": 0.027, - "price": 26.51, - "change_percent": 0.0019, + "market_value": 4105.29, + "pe_ratio": 20.82, + "pb_ratio": 1.6, + "ps_ratio": 6.83, + "dividend_yield": 0.0258, + "price": 27.7, + "change_percent": 0.0449, "roe": 0.0605, "gross_profit_margin": 0, "net_profit_margin": 0.3782, @@ -2273,11 +2273,11 @@ }, "targets": { "target_market_value": { - "min": null, - "max": null + "min": 3200.0, + "max": 3600.0 } } }, - "timestamp": "2025-01-13" + "timestamp": "2025-01-15" } } \ No newline at end of file diff --git a/项目文档.txt b/项目文档.txt new file mode 100644 index 0000000..c534033 --- /dev/null +++ b/项目文档.txt @@ -0,0 +1,193 @@ +# 价值投资盯盘系统项目文档 + +## 项目概述 + +**项目名称**：价值投资盯盘系统 +**开发者**：张艺杰 +**项目类型**：A股智能股票分析与监控平台 +**技术栈**：Python + FastAPI + Bootstrap + ECharts + +## 系统功能 + +### 1. 核心功能 + +1. **股票监控** + - 实时股票行情监控 + - 自定义市值目标区间 + - 多维度指标展示 + - 涨跌幅实时更新 + +2. **指数行情** + - 主要指数实时展示 + - K线图可视化 + - 涨跌幅实时更新 + +3. **公司详情分析** + - 公司基本信息 + - 财务指标分析 + - 股东结构分析 + - AI智能分析 + +### 2. 具体指标监控 + +#### 2.1 基础指标 +- 股票代码和名称 +- 现价和涨跌幅 +- 市值监控 +- 目标区间对比 + +#### 2.2 估值指标 +- 市盈率(PE) +- 市净率(PB) +- 市销率(PS) +- 股息率 + +#### 2.3 财务指标 +- ROE（净资产收益率） +- 毛利率 +- 净利率 +- 资产负债率 +- 净利润增长率 +- 每股净资产 +- 每股经营现金流 + +### 3. AI分析功能 + +1. **投资建议** + - 总体建议 + - 建议操作 + - 关注重点 + +2. **价格分析** + - 合理价格区间 + - 目标市值区间 + +3. **多维度分析** + - 估值分析 + - 财务健康状况 + - 成长潜力 + - 风险评估 + +## 技术实现 + +### 1. 后端架构 + +1. **Web框架** + - FastAPI作为主要Web框架 + - Uvicorn作为ASGI服务器 + +2. **数据源集成** + - Tushare API接口 + +3. **数据处理** + - Pandas进行数据分析 + - NumPy进行数值计算 + +### 2. 前端实现 + +1. **UI框架** + - Bootstrap 5.1.3 + - 响应式设计 + +2. **数据可视化** + - ECharts 5.4.3 + - 动态K线图表 + +3. **交互设计** + - AJAX异步数据更新 + - 实时数据刷新 + - 模态框展示详情 + +### 3. 数据存储 + +1. **配置存储** + - JSON文件存储监控列表 + - 配置文件自动管理 + +2. **缓存机制** + - 行情数据缓存 + - 智能更新策略 + +## 部署要求 + +### 1. 系统要求 +- Python 3.8+ +- 8GB+ RAM +- 现代浏览器支持 + +### 2. 依赖安装 +```bash +pip install -r requirements.txt +``` + +### 3. 配置说明 +- 需配置Tushare API Token +- 配置端口默认为8000 +- 支持热重载 + +## 使用说明 + +### 1. 启动系统 +```bash +python run.py +``` + +### 2. 访问系统 +- 浏览器访问：`http://localhost:8000` + +### 3. 基本操作 +1. 添加监控股票 + - 输入6位股票代码 + - 设置目标市值区间 + +2. 查看股票详情 + - 点击股票名称查看详细信息 + - 查看AI分析报告 + +3. 管理监控列表 + - 删除不需要的股票 + - 强制刷新数据 + +## 安全性考虑 + +1. **数据安全** + - API Token安全存储 + - 敏感信息加密 + +2. **访问控制** + - 请求频率限制 + - 错误处理机制 + +## 后续优化方向 + +1. **功能扩展** + - 增加更多技术指标 + - 添加自定义告警功能 + - 支持多维度筛选 + +2. **性能优化** + - 优化数据缓存机制 + - 提升响应速度 + - 减少资源占用 + +3. **用户体验** + - 增加自定义主题 + - 优化移动端显示 + - 添加更多图表类型 + +## 维护说明 + +1. **日常维护** + - 定期更新依赖 + - 检查API可用性 + - 优化数据缓存 + +2. **问题处理** + - 日志监控 + - 异常处理 + - 性能监控 + +## 版权信息 + +版权所有 © 2024 张艺杰 +保留所有权利 \ No newline at end of file