From 01825eab57fb77a8d84dbb0b8ad3d0e698a1bd33 Mon Sep 17 00:00:00 2001 From: zyj118 Date: Mon, 13 Jan 2025 19:48:17 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E6=8F=90=E4=BA=A4?= =?UTF-8?q?=EF=BC=9A=E4=BB=B7=E5=80=BC=E6=8A=95=E8=B5=84=E7=9B=AF=E7=9B=98?= =?UTF-8?q?=E7=B3=BB=E7=BB=9F?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .gitignore | 38 + README.md | 64 + app/__init__.py | 25 + app/api/stock_routes.py | 82 + app/config.py | 29 + app/models/stock.py | 32 + app/services/ai_analysis_service.py | 308 ++++ app/services/stock_service.py | 573 +++++++ app/templates/index.html | 1514 ++++++++++++++++++ app/templates/market.html | 223 +++ config.json.example | 4 + requirements.txt | 54 + run.py | 12 + stock_cache.json | 2283 +++++++++++++++++++++++++++ watchlist.json | 38 + 15 files changed, 5279 insertions(+) create mode 100644 .gitignore create mode 100644 README.md create mode 100644 app/__init__.py create mode 100644 app/api/stock_routes.py create mode 100644 app/config.py create mode 100644 app/models/stock.py create mode 100644 app/services/ai_analysis_service.py create mode 100644 app/services/stock_service.py create mode 100644 app/templates/index.html create mode 100644 app/templates/market.html create mode 100644 config.json.example create mode 100644 requirements.txt create mode 100644 run.py create mode 100644 stock_cache.json create mode 100644 watchlist.json diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..4ec4ccc --- /dev/null +++ b/.gitignore @@ -0,0 +1,38 @@ +# 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 \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..96e9c0e --- /dev/null +++ b/README.md @@ -0,0 +1,64 @@ +# 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 \ No newline at end of file diff --git a/app/__init__.py b/app/__init__.py new file mode 100644 index 0000000..c8e2d15 --- /dev/null +++ b/app/__init__.py @@ -0,0 +1,25 @@ +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) \ No newline at end of file diff --git a/app/api/stock_routes.py b/app/api/stock_routes.py new file mode 100644 index 0000000..b908a32 --- /dev/null +++ b/app/api/stock_routes.py @@ -0,0 +1,82 @@ +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)}"} \ No newline at end of file diff --git a/app/config.py b/app/config.py new file mode 100644 index 0000000..7ea0fc3 --- /dev/null +++ b/app/config.py @@ -0,0 +1,29 @@ +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": {}}') \ No newline at end of file diff --git a/app/models/stock.py b/app/models/stock.py new file mode 100644 index 0000000..4ccf75b --- /dev/null +++ b/app/models/stock.py @@ -0,0 +1,32 @@ +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 \ No newline at end of file diff --git a/app/services/ai_analysis_service.py b/app/services/ai_analysis_service.py new file mode 100644 index 0000000..a44e68e --- /dev/null +++ b/app/services/ai_analysis_service.py @@ -0,0 +1,308 @@ +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 \ No newline at end of file diff --git a/app/services/stock_service.py b/app/services/stock_service.py new file mode 100644 index 0000000..7fa008a --- /dev/null +++ b/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)}"} \ No newline at end of file diff --git a/app/templates/index.html b/app/templates/index.html new file mode 100644 index 0000000..5928e94 --- /dev/null +++ b/app/templates/index.html @@ -0,0 +1,1514 @@ + + + + + + + 价值投资盯盘系统 - 智能股票分析与监控平台 + + + + + + + + + + + + + + + + + + + + +
+
+
+ +
+
+
+ +
+ +
+
+ 添加监控股票 +
+
+
+
+
+ + +
+
+ +
+ + - + +
+
+
+ +
+
+
+
+
+ + +
+
+ 监控列表 +
+ +
+
+
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
代码名称现价涨跌幅 监控目标市值 市盈率 市净率 市销率 股息率 ROE 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 操作
统计(0只)
+
+
+
+
+ + + + + + + + + + + + \ No newline at end of file diff --git a/app/templates/market.html b/app/templates/market.html new file mode 100644 index 0000000..6ae10ea --- /dev/null +++ b/app/templates/market.html @@ -0,0 +1,223 @@ + + + + + + 指数行情 - 价值投资盯盘系统 + + + + + + + +
+
+ +
+
+ + + + + + \ No newline at end of file diff --git a/config.json.example b/config.json.example new file mode 100644 index 0000000..0ff06d7 --- /dev/null +++ b/config.json.example @@ -0,0 +1,4 @@ +{ + "watchlist": {}, + "tushare_token": "your_tushare_token_here" +} \ No newline at end of file diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..4768a4e --- /dev/null +++ b/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 diff --git a/run.py b/run.py new file mode 100644 index 0000000..cdff16b --- /dev/null +++ b/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 + ) \ No newline at end of file diff --git a/stock_cache.json b/stock_cache.json new file mode 100644 index 0000000..6f39f01 --- /dev/null +++ b/stock_cache.json @@ -0,0 +1,2283 @@ +{ + "300059": { + "data": { + "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, + "roe": 0.0811, + "gross_profit_margin": 0.8372, + "net_profit_margin": 2.694, + "debt_to_assets": 0.7643, + "revenue_yoy": 0, + "net_profit_yoy": -0.0269, + "bps": 4.874, + "ocfps": 4.062, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 2500.0, + "max": 2800.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "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, + "roe": 0.1319, + "gross_profit_margin": 0, + "net_profit_margin": 0.1806, + "debt_to_assets": 0.8979, + "revenue_yoy": 0, + "net_profit_yoy": 0.3609, + "bps": 49.859, + "ocfps": 22.933, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 8000.0, + "max": 9500.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "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, + "roe": 0.1037, + "gross_profit_margin": 0.437, + "net_profit_margin": 0.1435, + "debt_to_assets": 0.3435, + "revenue_yoy": 0, + "net_profit_yoy": -0.0292, + "bps": 9.463, + "ocfps": -0.038, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 336.0, + "max": 429.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "002714": { + "data": { + "stock_info": { + "code": "002714", + "name": "牧原股份", + "market_value": 1980.25, + "pe_ratio": 0, + "pb_ratio": 2.97, + "ps_ratio": 1.79, + "dividend_yield": 0.0227, + "price": 36.25, + "change_percent": 0.0014, + "roe": 0.1552, + "gross_profit_margin": 0.1727, + "net_profit_margin": 0.1162, + "debt_to_assets": 0.5838, + "revenue_yoy": 0, + "net_profit_yoy": 6.689, + "bps": 13.034, + "ocfps": 5.339, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 1650.0, + "max": 2200.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "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, + "roe": 0.1076, + "gross_profit_margin": 0.284, + "net_profit_margin": 0.1447, + "debt_to_assets": 0.271, + "revenue_yoy": 0, + "net_profit_yoy": 0.0493, + "bps": 22.711, + "ocfps": 2.283, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 807.0, + "max": 1210.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "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, + "roe": 0.1117, + "gross_profit_margin": 0.7413, + "net_profit_margin": 0.2661, + "debt_to_assets": 0.2188, + "revenue_yoy": 0, + "net_profit_yoy": 0.47, + "bps": 15.392, + "ocfps": 2.238, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 270.0, + "max": 330.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "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, + "roe": 0.1189, + "gross_profit_margin": 0.3255, + "net_profit_margin": 0.0814, + "debt_to_assets": 0.398, + "revenue_yoy": 0, + "net_profit_yoy": 0.1705, + "bps": 12.565, + "ocfps": 1.429, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 500.0, + "max": 650.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "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, + "roe": 0.1059, + "gross_profit_margin": 0.4476, + "net_profit_margin": 0.1371, + "debt_to_assets": 0.3296, + "revenue_yoy": 0, + "net_profit_yoy": -0.084, + "bps": 8.321, + "ocfps": 0.282, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 2000.0, + "max": 2200.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "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, + "roe": 0.0801, + "gross_profit_margin": 0.6177, + "net_profit_margin": 0.2897, + "debt_to_assets": 0.1485, + "revenue_yoy": 0, + "net_profit_yoy": -0.1346, + "bps": 6.396, + "ocfps": 0.251, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 240.0, + "max": 288.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "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, + "roe": 0.623, + "gross_profit_margin": 0.492, + "net_profit_margin": 0.2041, + "debt_to_assets": 0.6684, + "revenue_yoy": 0, + "net_profit_yoy": -0.009, + "bps": 4.413, + "ocfps": 7.153, + "from_cache": false + }, + "targets": { + "target_market_value": { + "min": 225.0, + "max": 260.0 + } + } + }, + "timestamp": "2025-01-13" + }, + "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, + 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