Initial commit

.claude/settings.local.json

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+{
+  "permissions": {
+    "allow": [
+      "Bash(npm test:*)",
+      "Bash(xargs ls:*)",
+      "Bash(awk:*)",
+      "Bash(npm start)",
+      "Bash(python3:*)"
+    ],
+    "deny": [],
+    "ask": []
+  }
+}

.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

.gitignore

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+node_modules
+package-lock.json
+yarn.lock
+build
+node_modules
+# 依赖
+node_modules/
+/.pnp
+.pnp.js
+
+# 测试
+/coverage
+
+# 生产构建
+/build
+/dist
+
+# 环境变量
+.env
+.env.local
+.env.development.local
+.env.test.local
+.env.production.local
+
+# 日志
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+
+# 编辑器
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# macOS
+.DS_Store
+
+# Windows
+Thumbs.db

.npmrc

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+legacy-peer-deps=true
+auto-install-peers=true
+strict-peer-dependencies=false

CLAUDE.md

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+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Project Overview
+
+This is a hybrid React dashboard application with a Flask/Python backend. The project is built on the Argon Dashboard Chakra PRO template and includes financial/trading analysis features.
+
+### Frontend (React + Chakra UI)
+- **Framework**: React 18.3.1 with Chakra UI 2.8.2
+- **Styling**: Tailwind CSS + custom Chakra theme
+- **Build Tool**: React Scripts with custom Gulp tasks
+- **Charts**: ApexCharts, ECharts, and custom visualization components
+
+### Backend (Flask/Python)
+- **Framework**: Flask with SQLAlchemy ORM
+- **Database**: ClickHouse for analytics + MySQL/PostgreSQL
+- **Features**: Real-time data processing, trading analysis, user authentication
+- **Task Queue**: Celery for background processing
+
+## Development Commands
+
+### Frontend Development
+```bash
+npm start                    # Start development server (port 3000, proxies to localhost:5001)
+npm run build               # Production build with license headers
+npm test                    # Run React test suite
+npm run lint:check          # Check ESLint rules
+npm run lint:fix            # Auto-fix ESLint issues
+npm run install:clean       # Clean install (removes node_modules and package-lock)
+```
+
+### Backend Development
+```bash
+python app_2.py            # Start Flask server (main backend)
+python simulation_background_processor.py  # Background data processor
+```
+
+### Python Dependencies
+Install from requirements.txt:
+```bash
+pip install -r requirements.txt
+```
+
+## Architecture
+
+### Frontend Structure
+- `src/layouts/` - Main layout components (Admin, Auth, Home)
+- `src/views/` - Page components organized by feature (Dashboard, Company, Community, etc.)
+- `src/components/` - Reusable UI components (Charts, Cards, Buttons, etc.)
+- `src/theme/` - Chakra UI theme customization
+- `src/routes.js` - Application routing configuration
+- `src/contexts/` - React context providers
+- `src/services/` - API service layer
+
+### Backend Structure
+- `app_2.py` - Main Flask application with routes and business logic
+- `simulation_background_processor.py` - Background data processing service
+- `wechat_pay.py` / `wechat_pay_config.py` - Payment integration
+- `tdays.csv` - Trading days data
+
+### Key Integrations
+- ClickHouse for high-performance analytics queries
+- Celery + Redis for background task processing
+- Flask-SocketIO for real-time data updates
+- Tencent Cloud services (SMS, etc.)
+- WeChat Pay integration
+
+## Configuration
+
+### Proxy Setup
+The React dev server proxies API calls to `http://localhost:5001` (see package.json).
+
+### Environment Files
+- `.env` - Environment variables for both frontend and backend
+
+### Build Process
+The build process includes custom Gulp tasks that add Creative Tim license headers to JS, CSS, and HTML files.
+
+### Styling Architecture
+- Tailwind CSS for utility classes
+- Custom Chakra UI theme with extended color palette
+- Component-specific SCSS files in `src/assets/scss/`
+
+## Testing
+- React Testing Library setup for frontend components
+- Test command: `npm test`
+
+## Deployment
+- Build: `npm run build`
+- Deploy: `npm run deploy` (builds the project)

ISSUE_TEMPLATE.md

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+<!--
+ IMPORTANT: Please use the following link to create a new issue:
+
+  https://www.creative-tim.com/new-issue/argon-dashboard-chakra-pro
+
+**If your issue was not created using the app above, it will be closed immediately.**
+-->
+
+<!--
+Love Creative Tim? Do you need Angular, React, Vuejs or HTML? You can visit:
+👉  https://www.creative-tim.com/bundles
+👉  https://www.creative-tim.com
+-->

app/__init__.py

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+from flask import Flask
+from flask_sqlalchemy import SQLAlchemy
+
+from flask_cors import CORS
+from datetime import datetime
+import pytz
+import os
+
+# 创建Flask应用
+app = Flask(__name__)
+
+# 配置
+config_name = os.environ.get('FLASK_ENV', 'development')
+from config import config
+app.config.from_object(config[config_name])
+
+# 初始化扩展
+db = SQLAlchemy(app)
+CORS(app, resources={r"/api/*": {"origins": "*"}})
+
+# 时区设置
+def beijing_now():
+    """获取北京时间"""
+    tz = pytz.timezone('Asia/Shanghai')
+    return datetime.now(tz)
+
+# 导入模型
+from app.models import *
+
+# 创建数据库表
+with app.app_context():
+    db.create_all()
+
+# 注册路由
+from app.routes import events, stocks, limitanalyse, calendar, industries
+
+app.register_blueprint(events.bp)
+app.register_blueprint(stocks.bp)
+app.register_blueprint(limitanalyse.bp)
+app.register_blueprint(calendar.bp)
+app.register_blueprint(industries.bp)
+
+if __name__ == '__main__':
+    print("=== Value Frontier React 架构启动 ===")
+    app.run(host='0.0.0.0', port=5001, debug=True) 

app/extensions.py

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+# app/extensions.py
+from flask_sqlalchemy import SQLAlchemy
+from flask_login import LoginManager
+from flask_compress import Compress
+from flask_cors import CORS
+from clickhouse_driver import Client as Cclient
+from sqlalchemy import create_engine
+
+# Database instances
+db = SQLAlchemy()
+
+# Other extensions
+login_manager = LoginManager()
+compress = Compress()
+cors = CORS()
+
+# Database engines (如果仍然需要直接使用 engine)
+engine = create_engine("mysql+pymysql://root:Zzl33818!@111.198.58.126:33060/stock", echo=False)
+engine_med = create_engine("mysql+pymysql://root:Zzl33818!@111.198.58.126:33060/med", echo=False)
+engine_2 = create_engine("mysql+pymysql://root:Zzl33818!@111.198.58.126:33060/valuefrontier", echo=False)
+
+# ClickHouse client factory
+def get_clickhouse_client():
+    return Cclient(
+        host='111.198.58.126',
+        port=18778,
+        user='default',
+        password='Zzl5588161!',
+        database='stock'
+    )

app/models.py

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+from app import db
+from datetime import datetime
+import pytz
+import json
+
+def beijing_now():
+    """获取北京时间"""
+    tz = pytz.timezone('Asia/Shanghai')
+    return datetime.now(tz)
+
+class Post(db.Model):
+    """帖子模型"""
+    id = db.Column(db.Integer, primary_key=True)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'), nullable=False)
+    user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)
+
+    # 内容
+    title = db.Column(db.String(200))  # 标题(可选)
+    content = db.Column(db.Text, nullable=False)  # 内容
+    content_type = db.Column(db.String(20), default='text')  # 内容类型:text/rich_text/link
+
+    # 时间
+    created_at = db.Column(db.DateTime, default=beijing_now)
+    updated_at = db.Column(db.DateTime, default=beijing_now, onupdate=beijing_now)
+
+    # 统计
+    likes_count = db.Column(db.Integer, default=0)
+    comments_count = db.Column(db.Integer, default=0)
+    view_count = db.Column(db.Integer, default=0)
+
+    # 状态
+    status = db.Column(db.String(20), default='active')  # active/hidden/deleted
+    is_top = db.Column(db.Boolean, default=False)  # 是否置顶
+
+    # 关系
+    user = db.relationship('User', backref='posts')
+    likes = db.relationship('PostLike', backref='post', lazy='dynamic')
+    comments = db.relationship('Comment', backref='post', lazy='dynamic')
+
+class User(db.Model):
+    """用户模型"""
+    id = db.Column(db.Integer, primary_key=True)
+
+    # 基础账号信息(注册时必填)
+    username = db.Column(db.String(80), unique=True, nullable=False)  # 用户名
+    email = db.Column(db.String(120), unique=True, nullable=False)  # 邮箱
+    password_hash = db.Column(db.String(128), nullable=False)  # 密码哈希
+    email_confirmed = db.Column(db.Boolean, default=False)  # 邮箱是否验证
+
+    # 账号状态
+    created_at = db.Column(db.DateTime, default=beijing_now)  # 注册时间
+    last_seen = db.Column(db.DateTime, default=beijing_now)  # 最后活跃时间
+    status = db.Column(db.String(20), default='active')  # 账号状态 active/banned/deleted
+
+    # 个人资料(可选,后续在个人中心完善)
+    nickname = db.Column(db.String(30))  # 社区昵称
+    avatar_url = db.Column(db.String(200))  # 头像URL
+    banner_url = db.Column(db.String(200))  # 个人主页背景图
+    bio = db.Column(db.String(200))  # 个人简介
+    gender = db.Column(db.String(10))  # 性别
+    birth_date = db.Column(db.Date)  # 生日
+    location = db.Column(db.String(100))  # 所在地
+
+    # 联系方式(可选)
+    phone = db.Column(db.String(20))  # 手机号
+    wechat_id = db.Column(db.String(80))  # 微信号
+
+    # 实名认证信息(可选)
+    real_name = db.Column(db.String(30))  # 真实姓名
+    id_number = db.Column(db.String(18))  # 身份证号(加密存储)
+    is_verified = db.Column(db.Boolean, default=False)  # 是否实名认证
+    verify_time = db.Column(db.DateTime)  # 实名认证时间
+
+    # 投资相关信息(可选)
+    trading_experience = db.Column(db.Integer)  # 炒股年限
+    investment_style = db.Column(db.String(50))  # 投资风格
+    risk_preference = db.Column(db.String(20))  # 风险偏好
+    investment_amount = db.Column(db.String(20))  # 投资规模
+    preferred_markets = db.Column(db.String(200), default='[]')  # 偏好市场 JSON
+
+    # 社区信息(系统自动更新)
+    user_level = db.Column(db.Integer, default=1)  # 用户等级
+    reputation_score = db.Column(db.Integer, default=0)  # 信用积分
+    contribution_point = db.Column(db.Integer, default=0)  # 贡献点数
+    post_count = db.Column(db.Integer, default=0)  # 发帖数
+    comment_count = db.Column(db.Integer, default=0)  # 评论数
+    follower_count = db.Column(db.Integer, default=0)  # 粉丝数
+    following_count = db.Column(db.Integer, default=0)  # 关注数
+
+    # 创作者信息(可选)
+    is_creator = db.Column(db.Boolean, default=False)  # 是否创作者
+    creator_type = db.Column(db.String(20))  # 创作者类型
+    creator_tags = db.Column(db.String(200), default='[]')  # 创作者标签 JSON
+
+    # 系统设置
+    email_notifications = db.Column(db.Boolean, default=True)  # 邮件通知
+    sms_notifications = db.Column(db.Boolean, default=False)  # 短信通知
+    wechat_notifications = db.Column(db.Boolean, default=False)  # 微信通知
+    notification_preferences = db.Column(db.String(500), default='{}')  # 通知偏好 JSON
+    privacy_level = db.Column(db.String(20), default='public')  # 隐私级别
+    theme_preference = db.Column(db.String(20), default='light')  # 主题偏好
+    blocked_keywords = db.Column(db.String(500), default='[]')  # 屏蔽关键词 JSON
+    # 手机号验证
+    phone_confirmed = db.Column(db.Boolean, default=False)  # 手机是否验证
+    phone_confirm_time = db.Column(db.DateTime)  # 手机验证时间
+
+    def __init__(self, username, email=None, password=None, phone=None):
+        self.username = username
+        if email:
+            self.email = email
+        if password:
+            self.set_password(password)
+        if phone:
+            self.phone = phone
+
+    def set_password(self, password):
+        from werkzeug.security import generate_password_hash
+        self.password_hash = generate_password_hash(password)
+
+    def check_password(self, password):
+        from werkzeug.security import check_password_hash
+        return check_password_hash(self.password_hash, password)
+
+    def update_last_seen(self):
+        self.last_seen = beijing_now()
+        db.session.commit()
+
+    def get_preferred_markets(self):
+        try:
+            return json.loads(self.preferred_markets)
+        except (json.JSONDecodeError, TypeError):
+            return []
+
+    def get_blocked_keywords(self):
+        try:
+            return json.loads(self.blocked_keywords)
+        except (json.JSONDecodeError, TypeError):
+            return []
+
+    def get_notification_preferences(self):
+        try:
+            return json.loads(self.notification_preferences)
+        except (json.JSONDecodeError, TypeError):
+            return {}
+
+    def get_creator_tags(self):
+        try:
+            return json.loads(self.creator_tags)
+        except (json.JSONDecodeError, TypeError):
+            return []
+
+    def set_preferred_markets(self, markets):
+        self.preferred_markets = json.dumps(markets)
+
+    def set_blocked_keywords(self, keywords):
+        self.blocked_keywords = json.dumps(keywords)
+
+    def set_notification_preferences(self, preferences):
+        self.notification_preferences = json.dumps(preferences)
+
+    def set_creator_tags(self, tags):
+        self.creator_tags = json.dumps(tags)
+
+    def to_dict(self):
+        return {
+            'id': self.id,
+            'username': self.username,
+            'email': self.email,
+            'nickname': self.nickname,
+            'avatar_url': self.avatar_url,
+            'bio': self.bio,
+            'created_at': self.created_at.isoformat() if self.created_at else None,
+            'last_seen': self.last_seen.isoformat() if self.last_seen else None,
+            'status': self.status,
+            'user_level': self.user_level,
+            'reputation_score': self.reputation_score,
+            'post_count': self.post_count,
+            'follower_count': self.follower_count,
+            'following_count': self.following_count
+        }
+
+    def __repr__(self):
+        return f'<User {self.username}>'
+
+class Comment(db.Model):
+    """评论"""
+    id = db.Column(db.Integer, primary_key=True)
+    post_id = db.Column(db.Integer, db.ForeignKey('post.id'), nullable=False)
+    user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)
+    content = db.Column(db.Text, nullable=False)
+    parent_id = db.Column(db.Integer, db.ForeignKey('comment.id'))  # 父评论ID,用于回复
+    created_at = db.Column(db.DateTime, default=beijing_now)
+    status = db.Column(db.String(20), default='active')
+
+    user = db.relationship('User', backref='comments')
+    replies = db.relationship('Comment', backref=db.backref('parent', remote_side=[id]))
+
+
+class CommentLike(db.Model):
+    """评论点赞记录（基于session_id以兼容匿名点赞）"""
+    __tablename__ = 'comment_like'
+
+    id = db.Column(db.Integer, primary_key=True)
+    comment_id = db.Column(db.Integer, db.ForeignKey('comment.id'), nullable=False)
+    session_id = db.Column(db.String(100), nullable=False)
+    created_at = db.Column(db.DateTime, default=beijing_now)
+
+    __table_args__ = (db.UniqueConstraint('comment_id', 'session_id'),)
+
+class EventFollow(db.Model):
+    """事件关注"""
+    id = db.Column(db.Integer, primary_key=True)
+    user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'), nullable=False)
+    created_at = db.Column(db.DateTime, default=beijing_now)
+
+    user = db.relationship('User', backref='event_follows')
+
+    __table_args__ = (db.UniqueConstraint('user_id', 'event_id'),)
+
+class PostLike(db.Model):
+    """帖子点赞"""
+    id = db.Column(db.Integer, primary_key=True)
+    user_id = db.Column(db.Integer, db.ForeignKey('user.id'), nullable=False)
+    post_id = db.Column(db.Integer, db.ForeignKey('post.id'), nullable=False)
+    created_at = db.Column(db.DateTime, default=beijing_now)
+
+    user = db.relationship('User', backref='post_likes')
+
+    __table_args__ = (db.UniqueConstraint('user_id', 'post_id'),)
+
+class Event(db.Model):
+    """事件模型"""
+    id = db.Column(db.Integer, primary_key=True)
+    title = db.Column(db.String(200), nullable=False)
+    description = db.Column(db.Text)
+
+    # 事件类型与状态
+    event_type = db.Column(db.String(50))
+    status = db.Column(db.String(20), default='active')
+
+    # 时间相关
+    start_time = db.Column(db.DateTime, default=beijing_now)
+    end_time = db.Column(db.DateTime)
+    created_at = db.Column(db.DateTime, default=beijing_now)
+    updated_at = db.Column(db.DateTime, default=beijing_now)
+
+    # 热度与统计
+    hot_score = db.Column(db.Float, default=0)
+    view_count = db.Column(db.Integer, default=0)
+    trending_score = db.Column(db.Float, default=0)
+    post_count = db.Column(db.Integer, default=0)
+    follower_count = db.Column(db.Integer, default=0)
+
+    # 关联信息
+    related_industries = db.Column(db.JSON)
+    keywords = db.Column(db.JSON)
+    files = db.Column(db.JSON)
+    importance = db.Column(db.String(20))
+    related_avg_chg = db.Column(db.Float, default=0)
+    related_max_chg = db.Column(db.Float, default=0)
+    related_week_chg = db.Column(db.Float, default=0)
+
+    # 新增字段
+    invest_score = db.Column(db.Integer)  # 超预期得分
+    expectation_surprise_score = db.Column(db.Integer)
+    # 创建者信息
+    creator_id = db.Column(db.Integer, db.ForeignKey('user.id'))
+    creator = db.relationship('User', backref='created_events')
+
+    # 关系
+    posts = db.relationship('Post', backref='event', lazy='dynamic')
+    followers = db.relationship('EventFollow', backref='event', lazy='dynamic')
+    related_stocks = db.relationship('RelatedStock', backref='event', lazy='dynamic')
+    historical_events = db.relationship('HistoricalEvent', backref='event', lazy='dynamic')
+    related_data = db.relationship('RelatedData', backref='event', lazy='dynamic')
+    related_concepts = db.relationship('RelatedConcepts', backref='event', lazy='dynamic')
+
+    @property
+    def keywords_list(self):
+        if isinstance(self.keywords, list):
+            return self.keywords
+        elif isinstance(self.keywords, str):
+            try:
+                return json.loads(self.keywords)
+            except (json.JSONDecodeError, TypeError):
+                return []
+        return []
+
+    def set_keywords(self, keywords):
+        if isinstance(keywords, list):
+            self.keywords = keywords
+        elif isinstance(keywords, str):
+            try:
+                self.keywords = json.loads(keywords)
+            except json.JSONDecodeError:
+                self.keywords = [keywords]
+        else:
+            self.keywords = []
+
+class RelatedStock(db.Model):
+    """相关标的模型"""
+    id = db.Column(db.Integer, primary_key=True)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'))
+    stock_code = db.Column(db.String(20))  # 股票代码
+    stock_name = db.Column(db.String(100))  # 股票名称
+    sector = db.Column(db.String(100))  # 关联类型
+    relation_desc = db.Column(db.String(1024))  # 关联原因描述
+    created_at = db.Column(db.DateTime, default=beijing_now)
+    updated_at = db.Column(db.DateTime, default=beijing_now, onupdate=beijing_now)
+    correlation = db.Column(db.Float())
+    momentum = db.Column(db.String(1024)) #动量
+
+class RelatedData(db.Model):
+    """关联数据模型"""
+    id = db.Column(db.Integer, primary_key=True)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'))
+    title = db.Column(db.String(200))  # 数据标题
+    data_type = db.Column(db.String(50))  # 数据类型
+    data_content = db.Column(db.JSON)  # 数据内容(JSON格式)
+    description = db.Column(db.Text)  # 数据描述
+    created_at = db.Column(db.DateTime, default=beijing_now)
+
+class RelatedConcepts(db.Model):
+    """关联数据模型"""
+    id = db.Column(db.Integer, primary_key=True)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'))
+    concept_code = db.Column(db.String(20))  # 数据标题
+    concept = db.Column(db.String(100))  # 数据类型
+    reason = db.Column(db.Text)  # 数据描述
+    image_paths = db.Column(db.JSON)  # 数据内容(JSON格式)
+    created_at = db.Column(db.DateTime, default=beijing_now)
+
+    @property
+    def image_paths_list(self):
+        if isinstance(self.image_paths, list):
+            return self.image_paths
+        elif isinstance(self.image_paths, str):
+            try:
+                return json.loads(self.image_paths)
+            except (json.JSONDecodeError, TypeError):
+                return []
+        return []
+
+    def set_image_paths(self, image_paths):
+        if isinstance(image_paths, list):
+            self.image_paths = image_paths
+        elif isinstance(image_paths, str):
+            try:
+                self.image_paths = json.loads(image_paths)
+            except json.JSONDecodeError:
+                self.image_paths = [image_paths]
+        else:
+            self.image_paths = []
+
+    def get_first_image_path(self):
+        paths = self.image_paths_list
+        return paths[0] if paths else None
+
+class EventHotHistory(db.Model):
+    """事件热度历史记录"""
+    id = db.Column(db.Integer, primary_key=True)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'))
+    score = db.Column(db.Float)  # 总分
+    interaction_score = db.Column(db.Float)  # 互动分数
+    follow_score = db.Column(db.Float)  # 关注度分数
+    view_score = db.Column(db.Float)  # 浏览量分数
+    recent_activity_score = db.Column(db.Float)  # 最近活跃度分数
+    time_decay = db.Column(db.Float)  # 时间衰减因子
+    created_at = db.Column(db.DateTime, default=beijing_now)
+
+    event = db.relationship('Event', backref='hot_history')
+
+class EventTransmissionNode(db.Model):
+    """事件传导节点模型"""
+    __tablename__ = 'event_transmission_nodes'
+
+    id = db.Column(db.Integer, primary_key=True)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'), nullable=False)
+    node_type = db.Column(db.Enum('company', 'industry', 'policy', 'technology',
+                                  'market', 'event', 'other'), nullable=False)
+    node_name = db.Column(db.String(200), nullable=False)
+    node_description = db.Column(db.Text)
+    importance_score = db.Column(db.Integer, default=50)
+    stock_code = db.Column(db.String(20))
+    is_main_event = db.Column(db.Boolean, default=False)
+
+    created_at = db.Column(db.DateTime, default=beijing_now)
+    updated_at = db.Column(db.DateTime, default=beijing_now, onupdate=beijing_now)
+
+    # Relationships
+    event = db.relationship('Event', backref='transmission_nodes')
+    outgoing_edges = db.relationship('EventTransmissionEdge',
+                                     foreign_keys='EventTransmissionEdge.from_node_id',
+                                     backref='from_node', cascade='all, delete-orphan')
+    incoming_edges = db.relationship('EventTransmissionEdge',
+                                     foreign_keys='EventTransmissionEdge.to_node_id',
+                                     backref='to_node', cascade='all, delete-orphan')
+
+    __table_args__ = (
+        db.Index('idx_event_node_type', 'event_id', 'node_type'),
+        db.Index('idx_node_name', 'node_name'),
+    )
+
+class EventTransmissionEdge(db.Model):
+    """事件传导边模型"""
+    __tablename__ = 'event_transmission_edges'
+
+    id = db.Column(db.Integer, primary_key=True)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'), nullable=False)
+    from_node_id = db.Column(db.Integer, db.ForeignKey('event_transmission_nodes.id'), nullable=False)
+    to_node_id = db.Column(db.Integer, db.ForeignKey('event_transmission_nodes.id'), nullable=False)
+
+    transmission_type = db.Column(db.Enum('supply_chain', 'competition', 'policy',
+                                          'technology', 'capital_flow', 'expectation',
+                                          'cyclic_effect', 'other'), nullable=False)
+    transmission_mechanism = db.Column(db.Text)
+    direction = db.Column(db.Enum('positive', 'negative', 'neutral', 'mixed'), default='neutral')
+    strength = db.Column(db.Integer, default=50)
+    impact = db.Column(db.Text)
+    is_circular = db.Column(db.Boolean, default=False)
+
+    created_at = db.Column(db.DateTime, default=beijing_now)
+    updated_at = db.Column(db.DateTime, default=beijing_now, onupdate=beijing_now)
+
+    # Relationship
+    event = db.relationship('Event', backref='transmission_edges')
+
+    __table_args__ = (
+        db.Index('idx_event_edge_type', 'event_id', 'transmission_type'),
+        db.Index('idx_from_to_nodes', 'from_node_id', 'to_node_id'),
+    )
+
+class EventSankeyFlow(db.Model):
+    """事件桑基流模型"""
+    __tablename__ = 'event_sankey_flows'
+
+    id = db.Column(db.Integer, primary_key=True)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'), nullable=False)
+
+    # 流的基本信息
+    source_node = db.Column(db.String(200), nullable=False)
+    source_type = db.Column(db.Enum('event', 'policy', 'technology', 'industry',
+                                    'company', 'product'), nullable=False)
+    source_level = db.Column(db.Integer, nullable=False, default=0)
+
+    target_node = db.Column(db.String(200), nullable=False)
+    target_type = db.Column(db.Enum('policy', 'technology', 'industry',
+                                    'company', 'product'), nullable=False)
+    target_level = db.Column(db.Integer, nullable=False, default=1)
+
+    # 流量信息
+    flow_value = db.Column(db.Numeric(10, 2), nullable=False)
+    flow_ratio = db.Column(db.Numeric(5, 4), nullable=False)
+
+    # 传导机制
+    transmission_path = db.Column(db.String(500))
+    impact_description = db.Column(db.Text)
+    evidence_strength = db.Column(db.Integer, default=50)
+
+    # 时间戳
+    created_at = db.Column(db.DateTime, default=beijing_now)
+    updated_at = db.Column(db.DateTime, default=beijing_now, onupdate=beijing_now)
+
+    # 关系
+    event = db.relationship('Event', backref='sankey_flows')
+
+    __table_args__ = (
+        db.Index('idx_event_flow', 'event_id'),
+        db.Index('idx_source_target', 'source_node', 'target_node'),
+    )
+
+class HistoricalEvent(db.Model):
+    """历史事件模型"""
+    id = db.Column(db.Integer, primary_key=True)
+    event_id = db.Column(db.Integer, db.ForeignKey('event.id'))
+    title = db.Column(db.String(200))
+    content = db.Column(db.Text)
+    event_date = db.Column(db.DateTime)
+    relevance = db.Column(db.Integer)  # 相关性
+    importance = db.Column(db.Integer)  # 重要程度
+    related_stock = db.Column(db.JSON)  # 保留JSON字段
+    created_at = db.Column(db.DateTime, default=beijing_now)
+
+    # 新增关系
+    stocks = db.relationship('HistoricalEventStock', backref='historical_event', lazy='dynamic',
+                            cascade='all, delete-orphan')
+
+class HistoricalEventStock(db.Model):
+    """历史事件相关股票模型"""
+    __tablename__ = 'historical_event_stocks'
+
+    id = db.Column(db.Integer, primary_key=True)
+    historical_event_id = db.Column(db.Integer, db.ForeignKey('historical_event.id'), nullable=False)
+    stock_code = db.Column(db.String(20), nullable=False)
+    stock_name = db.Column(db.String(50))
+    relation_desc = db.Column(db.Text)
+    correlation = db.Column(db.Float, default=0.5)
+    sector = db.Column(db.String(100))
+    created_at = db.Column(db.DateTime, default=beijing_now)
+
+    __table_args__ = (
+        db.Index('idx_historical_event_stock', 'historical_event_id', 'stock_code'),
+    ) 

app/routes/__init__.py

@@ -0,0 +1 @@
+# 路由包初始化文件 

app/routes/calendar.py

@@ -0,0 +1,121 @@
+from flask import Blueprint, request, jsonify
+from datetime import datetime, timedelta
+import json
+
+bp = Blueprint('calendar', __name__, url_prefix='/api/v1/calendar')
+
+@bp.route('/event-counts', methods=['GET'])
+def get_event_counts():
+    """获取事件数量统计"""
+    try:
+        year = request.args.get('year', '2027')
+        month = request.args.get('month', '10')
+        
+        # 模拟事件数量数据
+        event_counts = []
+        for day in range(1, 32):
+            count = (day % 7) + 1  # 模拟每天1-7个事件
+            event_counts.append({
+                'date': f'{year}-{month.zfill(2)}-{day:02d}',
+                'count': count
+            })
+
+        return jsonify({
+            'success': True,
+            'data': event_counts
+        })
+
+    except Exception as e:
+        print(f"Error getting event counts: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/events', methods=['GET'])
+def get_calendar_events():
+    """获取日历事件"""
+    try:
+        year = request.args.get('year', '2027')
+        month = request.args.get('month', '10')
+        event_type = request.args.get('type', 'all')
+        
+        # 模拟日历事件数据
+        events = []
+        for day in range(1, 32):
+            for i in range((day % 7) + 1):
+                event = {
+                    'id': f'{year}{month.zfill(2)}{day:02d}{i}',
+                    'title': f'事件{day}-{i+1}',
+                    'date': f'{year}-{month.zfill(2)}-{day:02d}',
+                    'type': ['政策', '技术', '产业', '公司'][i % 4],
+                    'importance': ['高', '中', '低'][i % 3],
+                    'status': 'active'
+                }
+                events.append(event)
+
+        # 根据类型过滤
+        if event_type != 'all':
+            events = [e for e in events if e['type'] == event_type]
+
+        return jsonify({
+            'success': True,
+            'data': events
+        })
+
+    except Exception as e:
+        print(f"Error getting calendar events: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/events/<int:event_id>', methods=['GET'])
+def get_calendar_event_detail(event_id):
+    """获取日历事件详情"""
+    try:
+        # 模拟事件详情
+        event_detail = {
+            'id': event_id,
+            'title': f'事件{event_id}详情',
+            'description': f'这是事件{event_id}的详细描述',
+            'date': '2027-10-15',
+            'type': '政策',
+            'importance': '高',
+            'status': 'active',
+            'related_stocks': [
+                {'code': '000001', 'name': '股票A'},
+                {'code': '000002', 'name': '股票B'}
+            ],
+            'keywords': ['政策', '改革', '创新'],
+            'files': [
+                {'name': '报告.pdf', 'url': '/files/report.pdf'},
+                {'name': '数据.xlsx', 'url': '/files/data.xlsx'}
+            ]
+        }
+
+        return jsonify({
+            'success': True,
+            'data': event_detail
+        })
+
+    except Exception as e:
+        print(f"Error getting calendar event detail: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+def get_event_class(count):
+    """根据事件数量获取CSS类"""
+    if count == 0:
+        return 'no-events'
+    elif count <= 3:
+        return 'few-events'
+    elif count <= 6:
+        return 'medium-events'
+    else:
+        return 'many-events'
+
+def parse_json_field(field_value):
+    """解析JSON字段"""
+    if isinstance(field_value, str):
+        try:
+            return json.loads(field_value)
+        except (json.JSONDecodeError, TypeError):
+            return []
+    elif isinstance(field_value, (list, dict)):
+        return field_value
+    else:
+        return [] 

app/routes/events.py

@@ -0,0 +1,385 @@
+from flask import Blueprint, request, jsonify
+from app import db
+from app.models import Event, RelatedStock, RelatedConcepts, HistoricalEvent, EventTransmissionNode, EventTransmissionEdge, EventSankeyFlow
+from datetime import datetime
+import json
+
+bp = Blueprint('events', __name__, url_prefix='/api/events')
+
+
+
+@bp.route('/<int:event_id>', methods=['GET'])
+def get_event_detail(event_id):
+    """获取事件详情"""
+    try:
+        event = Event.query.get(event_id)
+        if not event:
+            return jsonify({'success': False, 'error': '事件不存在'}), 404
+
+        # 获取相关股票
+        related_stocks = RelatedStock.query.filter_by(event_id=event_id).all()
+        stocks_data = []
+        for stock in related_stocks:
+            stocks_data.append({
+                'id': stock.id,
+                'stock_code': stock.stock_code,
+                'stock_name': stock.stock_name,
+                'sector': stock.sector,
+                'relation_desc': stock.relation_desc,
+                'correlation': stock.correlation,
+                'momentum': stock.momentum,
+                'created_at': stock.created_at.isoformat() if stock.created_at else None
+            })
+
+        # 获取相关概念
+        related_concepts = RelatedConcepts.query.filter_by(event_id=event_id).all()
+        concepts_data = []
+        for concept in related_concepts:
+            concepts_data.append({
+                'id': concept.id,
+                'concept_code': concept.concept_code,
+                'concept': concept.concept,
+                'reason': concept.reason,
+                'image_paths': concept.image_paths_list,
+                'created_at': concept.created_at.isoformat() if concept.created_at else None
+            })
+
+        event_data = {
+            'id': event.id,
+            'title': event.title,
+            'description': event.description,
+            'event_type': event.event_type,
+            'status': event.status,
+            'start_time': event.start_time.isoformat() if event.start_time else None,
+            'end_time': event.end_time.isoformat() if event.end_time else None,
+            'created_at': event.created_at.isoformat() if event.created_at else None,
+            'updated_at': event.updated_at.isoformat() if event.updated_at else None,
+            'hot_score': event.hot_score,
+            'view_count': event.view_count,
+            'trending_score': event.trending_score,
+            'post_count': event.post_count,
+            'follower_count': event.follower_count,
+            'related_industries': event.related_industries,
+            'keywords': event.keywords_list,
+            'files': event.files,
+            'importance': event.importance,
+            'related_avg_chg': event.related_avg_chg,
+            'related_max_chg': event.related_max_chg,
+            'related_week_chg': event.related_week_chg,
+            'invest_score': event.invest_score,
+            'expectation_surprise_score': event.expectation_surprise_score,
+            'related_stocks': stocks_data,
+            'related_concepts': concepts_data
+        }
+
+        return jsonify({
+            'success': True,
+            'data': event_data
+        })
+
+    except Exception as e:
+        print(f"Error getting event detail: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/stocks', methods=['GET'])
+def get_related_stocks(event_id):
+    """获取事件相关股票"""
+    try:
+        stocks = RelatedStock.query.filter_by(event_id=event_id).all()
+        stocks_data = []
+        for stock in stocks:
+            stocks_data.append({
+                'id': stock.id,
+                'stock_code': stock.stock_code,
+                'stock_name': stock.stock_name,
+                'sector': stock.sector,
+                'relation_desc': stock.relation_desc,
+                'correlation': stock.correlation,
+                'momentum': stock.momentum,
+                'created_at': stock.created_at.isoformat() if stock.created_at else None
+            })
+
+        return jsonify({
+            'success': True,
+            'data': stocks_data
+        })
+
+    except Exception as e:
+        print(f"Error getting related stocks: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/stocks', methods=['POST'])
+def add_related_stock(event_id):
+    """添加相关股票"""
+    try:
+        data = request.get_json()
+        if not data:
+            return jsonify({'success': False, 'error': '请提供数据'}), 400
+
+        # 检查事件是否存在
+        event = Event.query.get(event_id)
+        if not event:
+            return jsonify({'success': False, 'error': '事件不存在'}), 404
+
+        # 创建新的相关股票记录
+        new_stock = RelatedStock(
+            event_id=event_id,
+            stock_code=data['stock_code'],
+            stock_name=data.get('stock_name', ''),
+            sector=data.get('sector', ''),
+            relation_desc=data['relation_desc'],
+            correlation=data.get('correlation', 0.5),
+            momentum=data.get('momentum', '')
+        )
+
+        db.session.add(new_stock)
+        db.session.commit()
+
+        return jsonify({
+            'success': True,
+            'message': '相关股票添加成功',
+            'data': {
+                'id': new_stock.id,
+                'stock_code': new_stock.stock_code,
+                'stock_name': new_stock.stock_name,
+                'sector': new_stock.sector,
+                'relation_desc': new_stock.relation_desc,
+                'correlation': new_stock.correlation,
+                'momentum': new_stock.momentum
+            }
+        })
+
+    except Exception as e:
+        db.session.rollback()
+        print(f"Error adding related stock: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/stocks/<int:stock_id>', methods=['DELETE'])
+def delete_related_stock(stock_id):
+    """删除相关股票"""
+    try:
+        stock = RelatedStock.query.get(stock_id)
+        if not stock:
+            return jsonify({'success': False, 'error': '相关股票不存在'}), 404
+
+        db.session.delete(stock)
+        db.session.commit()
+
+        return jsonify({
+            'success': True,
+            'message': '相关股票删除成功'
+        })
+
+    except Exception as e:
+        db.session.rollback()
+        print(f"Error deleting related stock: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/concepts', methods=['GET'])
+def get_related_concepts(event_id):
+    """获取事件相关概念"""
+    try:
+        concepts = RelatedConcepts.query.filter_by(event_id=event_id).all()
+        concepts_data = []
+        for concept in concepts:
+            concepts_data.append({
+                'id': concept.id,
+                'concept_code': concept.concept_code,
+                'concept': concept.concept,
+                'reason': concept.reason,
+                'image_paths': concept.image_paths_list,
+                'created_at': concept.created_at.isoformat() if concept.created_at else None
+            })
+
+        return jsonify({
+            'success': True,
+            'data': concepts_data
+        })
+
+    except Exception as e:
+        print(f"Error getting related concepts: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/historical', methods=['GET'])
+def get_historical_events(event_id):
+    """获取历史事件"""
+    try:
+        historical_events = HistoricalEvent.query.filter_by(event_id=event_id).all()
+        events_data = []
+        for event in historical_events:
+            events_data.append({
+                'id': event.id,
+                'title': event.title,
+                'content': event.content,
+                'event_date': event.event_date.isoformat() if event.event_date else None,
+                'relevance': event.relevance,
+                'importance': event.importance,
+                'related_stock': event.related_stock,
+                'created_at': event.created_at.isoformat() if event.created_at else None
+            })
+
+        return jsonify({
+            'success': True,
+            'data': events_data
+        })
+
+    except Exception as e:
+        print(f"Error getting historical events: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/expectation-score', methods=['GET'])
+def get_expectation_score(event_id):
+    """获取超预期得分"""
+    try:
+        event = Event.query.get(event_id)
+        if not event:
+            return jsonify({'success': False, 'error': '事件不存在'}), 404
+
+        return jsonify({
+            'success': True,
+            'data': {
+                'invest_score': event.invest_score,
+                'expectation_surprise_score': event.expectation_surprise_score
+            }
+        })
+
+    except Exception as e:
+        print(f"Error getting expectation score: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/follow', methods=['POST'])
+def toggle_event_follow(event_id):
+    """关注/取消关注事件"""
+    try:
+        # 这里需要用户认证，暂时返回成功
+        return jsonify({
+            'success': True,
+            'message': '关注状态更新成功'
+        })
+
+    except Exception as e:
+        print(f"Error toggling event follow: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/transmission', methods=['GET'])
+def get_transmission_chain(event_id):
+    """获取事件传导链"""
+    try:
+        # 获取传导节点
+        nodes = EventTransmissionNode.query.filter_by(event_id=event_id).all()
+        nodes_data = []
+        for node in nodes:
+            nodes_data.append({
+                'id': node.id,
+                'node_type': node.node_type,
+                'node_name': node.node_name,
+                'node_description': node.node_description,
+                'importance_score': node.importance_score,
+                'stock_code': node.stock_code,
+                'is_main_event': node.is_main_event
+            })
+
+        # 获取传导边
+        edges = EventTransmissionEdge.query.filter_by(event_id=event_id).all()
+        edges_data = []
+        for edge in edges:
+            edges_data.append({
+                'id': edge.id,
+                'from_node_id': edge.from_node_id,
+                'to_node_id': edge.to_node_id,
+                'transmission_type': edge.transmission_type,
+                'transmission_mechanism': edge.transmission_mechanism,
+                'direction': edge.direction,
+                'strength': edge.strength,
+                'impact': edge.impact,
+                'is_circular': edge.is_circular
+            })
+
+        return jsonify({
+            'success': True,
+            'data': {
+                'nodes': nodes_data,
+                'edges': edges_data
+            }
+        })
+
+    except Exception as e:
+        print(f"Error getting transmission chain: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/sankey-data')
+def get_event_sankey_data(event_id):
+    """获取事件桑基图数据"""
+    try:
+        flows = EventSankeyFlow.query.filter_by(event_id=event_id).all()
+        flows_data = []
+        for flow in flows:
+            flows_data.append({
+                'id': flow.id,
+                'source_node': flow.source_node,
+                'source_type': flow.source_type,
+                'source_level': flow.source_level,
+                'target_node': flow.target_node,
+                'target_type': flow.target_type,
+                'target_level': flow.target_level,
+                'flow_value': float(flow.flow_value),
+                'flow_ratio': float(flow.flow_ratio),
+                'transmission_path': flow.transmission_path,
+                'impact_description': flow.impact_description,
+                'evidence_strength': flow.evidence_strength
+            })
+
+        return jsonify({
+            'success': True,
+            'data': flows_data
+        })
+
+    except Exception as e:
+        print(f"Error getting sankey data: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/chain-analysis')
+def get_event_chain_analysis(event_id):
+    """获取事件链分析"""
+    try:
+        # 这里可以添加更复杂的链分析逻辑
+        return jsonify({
+            'success': True,
+            'data': {
+                'event_id': event_id,
+                'analysis': '链分析数据'
+            }
+        })
+
+    except Exception as e:
+        print(f"Error getting chain analysis: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<int:event_id>/chain-node/<int:node_id>', methods=['GET'])
+def get_chain_node_detail(event_id, node_id):
+    """获取链节点详情"""
+    try:
+        node = EventTransmissionNode.query.filter_by(
+            event_id=event_id, 
+            id=node_id
+        ).first()
+        
+        if not node:
+            return jsonify({'success': False, 'error': '节点不存在'}), 404
+
+        return jsonify({
+            'success': True,
+            'data': {
+                'id': node.id,
+                'node_type': node.node_type,
+                'node_name': node.node_name,
+                'node_description': node.node_description,
+                'importance_score': node.importance_score,
+                'stock_code': node.stock_code,
+                'is_main_event': node.is_main_event
+            }
+        })
+
+    except Exception as e:
+        print(f"Error getting chain node detail: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500 

app/routes/industries.py

@@ -0,0 +1,511 @@
+from flask import Blueprint, request, jsonify
+import json
+
+bp = Blueprint('industries', __name__, url_prefix='/api')
+
+@bp.route('/classifications', methods=['GET'])
+def get_classifications():
+    """获取行业分类"""
+    try:
+        # 模拟行业分类数据
+        classifications = [
+            {
+                'id': 1,
+                'name': '申万一级行业',
+                'description': '申万一级行业分类标准',
+                'levels': [
+                    {'id': 1, 'name': '农林牧渔'},
+                    {'id': 2, 'name': '采掘'},
+                    {'id': 3, 'name': '化工'},
+                    {'id': 4, 'name': '钢铁'},
+                    {'id': 5, 'name': '有色金属'},
+                    {'id': 6, 'name': '建筑材料'},
+                    {'id': 7, 'name': '建筑装饰'},
+                    {'id': 8, 'name': '电气设备'},
+                    {'id': 9, 'name': '国防军工'},
+                    {'id': 10, 'name': '汽车'},
+                    {'id': 11, 'name': '家用电器'},
+                    {'id': 12, 'name': '纺织服装'},
+                    {'id': 13, 'name': '轻工制造'},
+                    {'id': 14, 'name': '医药生物'},
+                    {'id': 15, 'name': '公用事业'},
+                    {'id': 16, 'name': '交通运输'},
+                    {'id': 17, 'name': '房地产'},
+                    {'id': 18, 'name': '商业贸易'},
+                    {'id': 19, 'name': '休闲服务'},
+                    {'id': 20, 'name': '银行'},
+                    {'id': 21, 'name': '非银金融'},
+                    {'id': 22, 'name': '综合'},
+                    {'id': 23, 'name': '计算机'},
+                    {'id': 24, 'name': '传媒'},
+                    {'id': 25, 'name': '通信'},
+                    {'id': 26, 'name': '电子'},
+                    {'id': 27, 'name': '机械设备'},
+                    {'id': 28, 'name': '食品饮料'}
+                ]
+            }
+        ]
+
+        return jsonify({
+            'success': True,
+            'data': classifications
+        })
+
+    except Exception as e:
+        print(f"Error getting classifications: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/levels', methods=['GET'])
+def get_industry_levels():
+    """获取行业层级"""
+    try:
+        classification_id = request.args.get('classification_id', '1')
+        
+        # 模拟行业层级数据
+        levels = [
+            {
+                'id': 1,
+                'name': '农林牧渔',
+                'code': '801010',
+                'description': '农业、林业、畜牧业、渔业',
+                'stock_count': 45,
+                'avg_change': 1.2,
+                'total_market_cap': 500000000000,
+                'sub_industries': [
+                    {'id': 101, 'name': '种植业', 'stock_count': 20},
+                    {'id': 102, 'name': '林业', 'stock_count': 8},
+                    {'id': 103, 'name': '畜牧业', 'stock_count': 12},
+                    {'id': 104, 'name': '渔业', 'stock_count': 5}
+                ]
+            },
+            {
+                'id': 2,
+                'name': '采掘',
+                'code': '801020',
+                'description': '煤炭、石油、天然气、有色金属矿采选',
+                'stock_count': 38,
+                'avg_change': 0.8,
+                'total_market_cap': 800000000000,
+                'sub_industries': [
+                    {'id': 201, 'name': '煤炭开采', 'stock_count': 15},
+                    {'id': 202, 'name': '石油开采', 'stock_count': 8},
+                    {'id': 203, 'name': '有色金属矿采选', 'stock_count': 15}
+                ]
+            },
+            {
+                'id': 3,
+                'name': '化工',
+                'code': '801030',
+                'description': '化学原料、化学制品、化学纤维',
+                'stock_count': 156,
+                'avg_change': 1.5,
+                'total_market_cap': 1200000000000,
+                'sub_industries': [
+                    {'id': 301, 'name': '化学原料', 'stock_count': 45},
+                    {'id': 302, 'name': '化学制品', 'stock_count': 78},
+                    {'id': 303, 'name': '化学纤维', 'stock_count': 33}
+                ]
+            },
+            {
+                'id': 4,
+                'name': '钢铁',
+                'code': '801040',
+                'description': '钢铁冶炼、钢铁制品',
+                'stock_count': 32,
+                'avg_change': 0.6,
+                'total_market_cap': 600000000000,
+                'sub_industries': [
+                    {'id': 401, 'name': '钢铁冶炼', 'stock_count': 18},
+                    {'id': 402, 'name': '钢铁制品', 'stock_count': 14}
+                ]
+            },
+            {
+                'id': 5,
+                'name': '有色金属',
+                'code': '801050',
+                'description': '有色金属冶炼、有色金属制品',
+                'stock_count': 67,
+                'avg_change': 1.8,
+                'total_market_cap': 900000000000,
+                'sub_industries': [
+                    {'id': 501, 'name': '有色金属冶炼', 'stock_count': 35},
+                    {'id': 502, 'name': '有色金属制品', 'stock_count': 32}
+                ]
+            },
+            {
+                'id': 6,
+                'name': '建筑材料',
+                'code': '801060',
+                'description': '水泥、玻璃、陶瓷、其他建材',
+                'stock_count': 89,
+                'avg_change': 1.1,
+                'total_market_cap': 700000000000,
+                'sub_industries': [
+                    {'id': 601, 'name': '水泥', 'stock_count': 25},
+                    {'id': 602, 'name': '玻璃', 'stock_count': 18},
+                    {'id': 603, 'name': '陶瓷', 'stock_count': 12},
+                    {'id': 604, 'name': '其他建材', 'stock_count': 34}
+                ]
+            },
+            {
+                'id': 7,
+                'name': '建筑装饰',
+                'code': '801070',
+                'description': '房屋建设、装修装饰、园林工程',
+                'stock_count': 45,
+                'avg_change': 0.9,
+                'total_market_cap': 400000000000,
+                'sub_industries': [
+                    {'id': 701, 'name': '房屋建设', 'stock_count': 15},
+                    {'id': 702, 'name': '装修装饰', 'stock_count': 20},
+                    {'id': 703, 'name': '园林工程', 'stock_count': 10}
+                ]
+            },
+            {
+                'id': 8,
+                'name': '电气设备',
+                'code': '801080',
+                'description': '电机、电气自动化设备、电源设备',
+                'stock_count': 134,
+                'avg_change': 2.1,
+                'total_market_cap': 1500000000000,
+                'sub_industries': [
+                    {'id': 801, 'name': '电机', 'stock_count': 25},
+                    {'id': 802, 'name': '电气自动化设备', 'stock_count': 45},
+                    {'id': 803, 'name': '电源设备', 'stock_count': 64}
+                ]
+            },
+            {
+                'id': 9,
+                'name': '国防军工',
+                'code': '801090',
+                'description': '航天装备、航空装备、地面兵装',
+                'stock_count': 28,
+                'avg_change': 1.6,
+                'total_market_cap': 300000000000,
+                'sub_industries': [
+                    {'id': 901, 'name': '航天装备', 'stock_count': 8},
+                    {'id': 902, 'name': '航空装备', 'stock_count': 12},
+                    {'id': 903, 'name': '地面兵装', 'stock_count': 8}
+                ]
+            },
+            {
+                'id': 10,
+                'name': '汽车',
+                'code': '801100',
+                'description': '汽车整车、汽车零部件',
+                'stock_count': 78,
+                'avg_change': 1.3,
+                'total_market_cap': 1100000000000,
+                'sub_industries': [
+                    {'id': 1001, 'name': '汽车整车', 'stock_count': 25},
+                    {'id': 1002, 'name': '汽车零部件', 'stock_count': 53}
+                ]
+            },
+            {
+                'id': 11,
+                'name': '家用电器',
+                'code': '801110',
+                'description': '白色家电、小家电、家电零部件',
+                'stock_count': 56,
+                'avg_change': 1.0,
+                'total_market_cap': 800000000000,
+                'sub_industries': [
+                    {'id': 1101, 'name': '白色家电', 'stock_count': 20},
+                    {'id': 1102, 'name': '小家电', 'stock_count': 18},
+                    {'id': 1103, 'name': '家电零部件', 'stock_count': 18}
+                ]
+            },
+            {
+                'id': 12,
+                'name': '纺织服装',
+                'code': '801120',
+                'description': '纺织制造、服装家纺',
+                'stock_count': 67,
+                'avg_change': 0.7,
+                'total_market_cap': 500000000000,
+                'sub_industries': [
+                    {'id': 1201, 'name': '纺织制造', 'stock_count': 35},
+                    {'id': 1202, 'name': '服装家纺', 'stock_count': 32}
+                ]
+            },
+            {
+                'id': 13,
+                'name': '轻工制造',
+                'code': '801130',
+                'description': '造纸、包装印刷、家用轻工',
+                'stock_count': 89,
+                'avg_change': 0.9,
+                'total_market_cap': 600000000000,
+                'sub_industries': [
+                    {'id': 1301, 'name': '造纸', 'stock_count': 25},
+                    {'id': 1302, 'name': '包装印刷', 'stock_count': 30},
+                    {'id': 1303, 'name': '家用轻工', 'stock_count': 34}
+                ]
+            },
+            {
+                'id': 14,
+                'name': '医药生物',
+                'code': '801140',
+                'description': '化学制药、中药、生物制品、医疗器械',
+                'stock_count': 234,
+                'avg_change': 1.9,
+                'total_market_cap': 2500000000000,
+                'sub_industries': [
+                    {'id': 1401, 'name': '化学制药', 'stock_count': 78},
+                    {'id': 1402, 'name': '中药', 'stock_count': 45},
+                    {'id': 1403, 'name': '生物制品', 'stock_count': 56},
+                    {'id': 1404, 'name': '医疗器械', 'stock_count': 55}
+                ]
+            },
+            {
+                'id': 15,
+                'name': '公用事业',
+                'code': '801150',
+                'description': '电力、燃气、水务',
+                'stock_count': 78,
+                'avg_change': 0.5,
+                'total_market_cap': 900000000000,
+                'sub_industries': [
+                    {'id': 1501, 'name': '电力', 'stock_count': 45},
+                    {'id': 1502, 'name': '燃气', 'stock_count': 18},
+                    {'id': 1503, 'name': '水务', 'stock_count': 15}
+                ]
+            },
+            {
+                'id': 16,
+                'name': '交通运输',
+                'code': '801160',
+                'description': '港口、公路、铁路、航空',
+                'stock_count': 67,
+                'avg_change': 0.8,
+                'total_market_cap': 800000000000,
+                'sub_industries': [
+                    {'id': 1601, 'name': '港口', 'stock_count': 15},
+                    {'id': 1602, 'name': '公路', 'stock_count': 20},
+                    {'id': 1603, 'name': '铁路', 'stock_count': 12},
+                    {'id': 1604, 'name': '航空', 'stock_count': 20}
+                ]
+            },
+            {
+                'id': 17,
+                'name': '房地产',
+                'code': '801170',
+                'description': '房地产开发、房地产服务',
+                'stock_count': 89,
+                'avg_change': 0.6,
+                'total_market_cap': 1200000000000,
+                'sub_industries': [
+                    {'id': 1701, 'name': '房地产开发', 'stock_count': 65},
+                    {'id': 1702, 'name': '房地产服务', 'stock_count': 24}
+                ]
+            },
+            {
+                'id': 18,
+                'name': '商业贸易',
+                'code': '801180',
+                'description': '贸易、零售',
+                'stock_count': 78,
+                'avg_change': 0.7,
+                'total_market_cap': 600000000000,
+                'sub_industries': [
+                    {'id': 1801, 'name': '贸易', 'stock_count': 35},
+                    {'id': 1802, 'name': '零售', 'stock_count': 43}
+                ]
+            },
+            {
+                'id': 19,
+                'name': '休闲服务',
+                'code': '801190',
+                'description': '景点、酒店、旅游综合',
+                'stock_count': 34,
+                'avg_change': 1.2,
+                'total_market_cap': 300000000000,
+                'sub_industries': [
+                    {'id': 1901, 'name': '景点', 'stock_count': 12},
+                    {'id': 1902, 'name': '酒店', 'stock_count': 15},
+                    {'id': 1903, 'name': '旅游综合', 'stock_count': 7}
+                ]
+            },
+            {
+                'id': 20,
+                'name': '银行',
+                'code': '801200',
+                'description': '银行',
+                'stock_count': 28,
+                'avg_change': 0.4,
+                'total_market_cap': 8000000000000,
+                'sub_industries': [
+                    {'id': 2001, 'name': '银行', 'stock_count': 28}
+                ]
+            },
+            {
+                'id': 21,
+                'name': '非银金融',
+                'code': '801210',
+                'description': '保险、证券、多元金融',
+                'stock_count': 45,
+                'avg_change': 0.8,
+                'total_market_cap': 2000000000000,
+                'sub_industries': [
+                    {'id': 2101, 'name': '保险', 'stock_count': 8},
+                    {'id': 2102, 'name': '证券', 'stock_count': 25},
+                    {'id': 2103, 'name': '多元金融', 'stock_count': 12}
+                ]
+            },
+            {
+                'id': 22,
+                'name': '综合',
+                'code': '801220',
+                'description': '综合',
+                'stock_count': 23,
+                'avg_change': 0.6,
+                'total_market_cap': 200000000000,
+                'sub_industries': [
+                    {'id': 2201, 'name': '综合', 'stock_count': 23}
+                ]
+            },
+            {
+                'id': 23,
+                'name': '计算机',
+                'code': '801230',
+                'description': '计算机设备、计算机应用',
+                'stock_count': 156,
+                'avg_change': 2.3,
+                'total_market_cap': 1800000000000,
+                'sub_industries': [
+                    {'id': 2301, 'name': '计算机设备', 'stock_count': 45},
+                    {'id': 2302, 'name': '计算机应用', 'stock_count': 111}
+                ]
+            },
+            {
+                'id': 24,
+                'name': '传媒',
+                'code': '801240',
+                'description': '文化传媒、营销传播',
+                'stock_count': 78,
+                'avg_change': 1.4,
+                'total_market_cap': 700000000000,
+                'sub_industries': [
+                    {'id': 2401, 'name': '文化传媒', 'stock_count': 45},
+                    {'id': 2402, 'name': '营销传播', 'stock_count': 33}
+                ]
+            },
+            {
+                'id': 25,
+                'name': '通信',
+                'code': '801250',
+                'description': '通信设备、通信运营',
+                'stock_count': 45,
+                'avg_change': 1.7,
+                'total_market_cap': 600000000000,
+                'sub_industries': [
+                    {'id': 2501, 'name': '通信设备', 'stock_count': 30},
+                    {'id': 2502, 'name': '通信运营', 'stock_count': 15}
+                ]
+            },
+            {
+                'id': 26,
+                'name': '电子',
+                'code': '801260',
+                'description': '半导体、电子制造、光学光电子',
+                'stock_count': 178,
+                'avg_change': 2.0,
+                'total_market_cap': 2000000000000,
+                'sub_industries': [
+                    {'id': 2601, 'name': '半导体', 'stock_count': 45},
+                    {'id': 2602, 'name': '电子制造', 'stock_count': 78},
+                    {'id': 2603, 'name': '光学光电子', 'stock_count': 55}
+                ]
+            },
+            {
+                'id': 27,
+                'name': '机械设备',
+                'code': '801270',
+                'description': '通用机械、专用设备、仪器仪表',
+                'stock_count': 234,
+                'avg_change': 1.1,
+                'total_market_cap': 1500000000000,
+                'sub_industries': [
+                    {'id': 2701, 'name': '通用机械', 'stock_count': 89},
+                    {'id': 2702, 'name': '专用设备', 'stock_count': 98},
+                    {'id': 2703, 'name': '仪器仪表', 'stock_count': 47}
+                ]
+            },
+            {
+                'id': 28,
+                'name': '食品饮料',
+                'code': '801280',
+                'description': '食品加工、饮料制造',
+                'stock_count': 67,
+                'avg_change': 1.3,
+                'total_market_cap': 1000000000000,
+                'sub_industries': [
+                    {'id': 2801, 'name': '食品加工', 'stock_count': 35},
+                    {'id': 2802, 'name': '饮料制造', 'stock_count': 32}
+                ]
+            }
+        ]
+
+        return jsonify({
+            'success': True,
+            'data': levels
+        })
+
+    except Exception as e:
+        print(f"Error getting industry levels: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/info', methods=['GET'])
+def get_industry_info():
+    """获取行业信息"""
+    try:
+        industry_id = request.args.get('industry_id')
+        
+        if not industry_id:
+            return jsonify({'success': False, 'error': '请提供行业ID'}), 400
+
+        # 模拟行业信息
+        industry_info = {
+            'id': industry_id,
+            'name': f'行业{industry_id}',
+            'code': f'801{industry_id.zfill(3)}',
+            'description': f'这是行业{industry_id}的详细描述',
+            'stock_count': 50,
+            'avg_change': 1.5,
+            'total_market_cap': 800000000000,
+            'pe_ratio': 15.6,
+            'pb_ratio': 2.3,
+            'roe': 8.5,
+            'top_stocks': [
+                {'code': '000001', 'name': '龙头股A', 'weight': 0.15},
+                {'code': '000002', 'name': '龙头股B', 'weight': 0.12},
+                {'code': '000003', 'name': '龙头股C', 'weight': 0.10}
+            ],
+            'sub_industries': [
+                {'id': 1, 'name': '子行业A', 'stock_count': 20},
+                {'id': 2, 'name': '子行业B', 'stock_count': 18},
+                {'id': 3, 'name': '子行业C', 'stock_count': 12}
+            ],
+            'performance': {
+                'daily': 1.5,
+                'weekly': 3.2,
+                'monthly': 8.5,
+                'quarterly': 12.3,
+                'yearly': 25.6
+            },
+            'trend': {
+                'direction': 'up',
+                'strength': 'medium',
+                'duration': '3 months'
+            }
+        }
+
+        return jsonify({
+            'success': True,
+            'data': industry_info
+        })
+
+    except Exception as e:
+        print(f"Error getting industry info: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500 

app/routes/limitanalyse.py

@@ -0,0 +1,469 @@
+from flask import Blueprint, request, jsonify
+import pandas as pd
+import json
+from datetime import datetime
+
+bp = Blueprint('limitanalyse', __name__, url_prefix='/api/limit-analyse')
+
+@bp.route('/available-dates', methods=['GET'])
+def get_available_dates():
+    """获取可用日期列表"""
+    try:
+        # 模拟可用日期
+        dates = [
+            '2025-07-16',
+            '2025-07-15',
+            '2025-07-14',
+            '2025-07-11',
+            '2025-07-10'
+        ]
+        
+        return jsonify({
+            'success': True,
+            'data': dates
+        })
+    except Exception as e:
+        print(f"Error getting available dates: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+def load_stock_data(datestr):
+    """加载股票数据"""
+    try:
+        # 模拟股票数据
+        data = []
+        for i in range(100):
+            data.append({
+                'code': f'00000{i:03d}',
+                'name': f'股票{i}',
+                'price': 10.0 + i * 0.1,
+                'change': (i % 10 - 5) * 0.5,
+                'sector': f'板块{i % 5}',
+                'limit_type': '涨停' if i % 10 == 0 else '正常',
+                'volume': 1000000 + i * 50000,
+                'amount': 10000000 + i * 500000
+            })
+        
+        return pd.DataFrame(data)
+    except Exception as e:
+        print(f"Error loading stock data: {e}")
+        return pd.DataFrame()
+
+@bp.route('/data', methods=['GET'])
+def get_analysis_data():
+    """获取分析数据"""
+    try:
+        date = request.args.get('date', '2025-07-16')
+        
+        # 加载数据
+        df = load_stock_data(date)
+        if df.empty:
+            return jsonify({'success': False, 'error': '数据加载失败'}), 500
+
+        # 统计信息
+        total_stocks = len(df)
+        limit_up_stocks = len(df[df['limit_type'] == '涨停'])
+        limit_down_stocks = len(df[df['limit_type'] == '跌停'])
+        
+        # 板块统计
+        sector_stats = df.groupby('sector').agg({
+            'code': 'count',
+            'change': 'mean',
+            'volume': 'sum'
+        }).reset_index()
+        
+        sector_data = []
+        for _, row in sector_stats.iterrows():
+            sector_data.append({
+                'sector': row['sector'],
+                'stock_count': int(row['code']),
+                'avg_change': round(row['change'], 2),
+                'total_volume': int(row['volume'])
+            })
+
+        return jsonify({
+            'success': True,
+            'data': {
+                'date': date,
+                'total_stocks': total_stocks,
+                'limit_up_stocks': limit_up_stocks,
+                'limit_down_stocks': limit_down_stocks,
+                'sector_stats': sector_data
+            }
+        })
+
+    except Exception as e:
+        print(f"Error getting analysis data: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/sector-data', methods=['GET'])
+def get_sector_data():
+    """获取板块数据"""
+    try:
+        date = request.args.get('date', '2025-07-16')
+        
+        # 加载数据
+        df = load_stock_data(date)
+        if df.empty:
+            return jsonify({'success': False, 'error': '数据加载失败'}), 500
+
+        # 板块统计
+        sector_stats = df.groupby('sector').agg({
+            'code': 'count',
+            'change': 'mean',
+            'volume': 'sum',
+            'amount': 'sum'
+        }).reset_index()
+        
+        sector_data = []
+        for _, row in sector_stats.iterrows():
+            sector_data.append({
+                'sector': row['sector'],
+                'stock_count': int(row['code']),
+                'avg_change': round(row['change'], 2),
+                'total_volume': int(row['volume']),
+                'total_amount': int(row['amount'])
+            })
+
+        return jsonify({
+            'success': True,
+            'data': sector_data
+        })
+
+    except Exception as e:
+        print(f"Error getting sector data: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/word-cloud', methods=['GET'])
+def get_word_cloud_data():
+    """获取词云数据"""
+    try:
+        date = request.args.get('date', '2025-07-16')
+        
+        # 模拟词云数据
+        word_data = [
+            {'word': '科技', 'value': 100},
+            {'word': '新能源', 'value': 85},
+            {'word': '医药', 'value': 70},
+            {'word': '消费', 'value': 65},
+            {'word': '金融', 'value': 50},
+            {'word': '地产', 'value': 45},
+            {'word': '制造', 'value': 40},
+            {'word': '农业', 'value': 35},
+            {'word': '传媒', 'value': 30},
+            {'word': '环保', 'value': 25}
+        ]
+
+        return jsonify({
+            'success': True,
+            'data': word_data
+        })
+
+    except Exception as e:
+        print(f"Error getting word cloud data: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/chart-data', methods=['GET'])
+def get_chart_data():
+    """获取图表数据"""
+    try:
+        date = request.args.get('date', '2025-07-16')
+        
+        # 模拟图表数据
+        chart_data = {
+            'limit_up_distribution': [
+                {'sector': '科技', 'count': 15},
+                {'sector': '新能源', 'count': 12},
+                {'sector': '医药', 'count': 10},
+                {'sector': '消费', 'count': 8},
+                {'sector': '金融', 'count': 6}
+            ],
+            'sector_performance': [
+                {'sector': '科技', 'change': 2.5},
+                {'sector': '新能源', 'change': 1.8},
+                {'sector': '医药', 'change': 1.2},
+                {'sector': '消费', 'change': 0.8},
+                {'sector': '金融', 'change': 0.5}
+            ]
+        }
+
+        return jsonify({
+            'success': True,
+            'data': chart_data
+        })
+
+    except Exception as e:
+        print(f"Error getting chart data: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/stock-details', methods=['GET'])
+def get_stock_details():
+    """获取股票详情"""
+    try:
+        code = request.args.get('code')
+        date = request.args.get('date', '2025-07-16')
+        
+        if not code:
+            return jsonify({'success': False, 'error': '请提供股票代码'}), 400
+
+        # 模拟股票详情
+        stock_detail = {
+            'code': code,
+            'name': f'股票{code}',
+            'price': 15.50,
+            'change': 2.5,
+            'sector': '科技',
+            'volume': 1500000,
+            'amount': 23250000,
+            'limit_type': '涨停',
+            'turnover_rate': 3.2,
+            'market_cap': 15500000000
+        }
+
+        return jsonify({
+            'success': True,
+            'data': stock_detail
+        })
+
+    except Exception as e:
+        print(f"Error getting stock details: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/sector-analysis', methods=['GET'])
+def get_sector_analysis():
+    """获取板块分析"""
+    try:
+        sector = request.args.get('sector')
+        date = request.args.get('date', '2025-07-16')
+        
+        if not sector:
+            return jsonify({'success': False, 'error': '请提供板块名称'}), 400
+
+        # 模拟板块分析数据
+        sector_analysis = {
+            'sector': sector,
+            'stock_count': 25,
+            'avg_change': 1.8,
+            'limit_up_count': 8,
+            'limit_down_count': 2,
+            'total_volume': 50000000,
+            'total_amount': 750000000,
+            'top_stocks': [
+                {'code': '000001', 'name': '股票A', 'change': 10.0},
+                {'code': '000002', 'name': '股票B', 'change': 9.5},
+                {'code': '000003', 'name': '股票C', 'change': 8.8}
+            ]
+        }
+
+        return jsonify({
+            'success': True,
+            'data': sector_analysis
+        })
+
+    except Exception as e:
+        print(f"Error getting sector analysis: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/trend-analysis', methods=['GET'])
+def get_trend_analysis():
+    """获取趋势分析"""
+    try:
+        date = request.args.get('date', '2025-07-16')
+        
+        # 模拟趋势分析数据
+        trend_data = {
+            'limit_up_trend': [
+                {'date': '2025-07-10', 'count': 45},
+                {'date': '2025-07-11', 'count': 52},
+                {'date': '2025-07-14', 'count': 48},
+                {'date': '2025-07-15', 'count': 55},
+                {'date': '2025-07-16', 'count': 51}
+            ],
+            'sector_trend': [
+                {'sector': '科技', 'trend': 'up'},
+                {'sector': '新能源', 'trend': 'up'},
+                {'sector': '医药', 'trend': 'stable'},
+                {'sector': '消费', 'trend': 'down'},
+                {'sector': '金融', 'trend': 'stable'}
+            ]
+        }
+
+        return jsonify({
+            'success': True,
+            'data': trend_data
+        })
+
+    except Exception as e:
+        print(f"Error getting trend analysis: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/heat-map', methods=['GET'])
+def get_heat_map_data():
+    """获取热力图数据"""
+    try:
+        date = request.args.get('date', '2025-07-16')
+        
+        # 模拟热力图数据
+        heat_map_data = []
+        sectors = ['科技', '新能源', '医药', '消费', '金融', '地产', '制造', '农业']
+        
+        for i, sector in enumerate(sectors):
+            for j in range(8):
+                heat_map_data.append({
+                    'sector': sector,
+                    'metric': f'指标{j+1}',
+                    'value': (i + j) % 10 + 1
+                })
+
+        return jsonify({
+            'success': True,
+            'data': heat_map_data
+        })
+
+    except Exception as e:
+        print(f"Error getting heat map data: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/correlation-analysis', methods=['GET'])
+def get_correlation_analysis():
+    """获取相关性分析"""
+    try:
+        date = request.args.get('date', '2025-07-16')
+        
+        # 模拟相关性分析数据
+        correlation_data = {
+            'sector_correlations': [
+                {'sector1': '科技', 'sector2': '新能源', 'correlation': 0.85},
+                {'sector1': '医药', 'sector2': '消费', 'correlation': 0.72},
+                {'sector1': '金融', 'sector2': '地产', 'correlation': 0.68},
+                {'sector1': '科技', 'sector2': '医药', 'correlation': 0.45},
+                {'sector1': '新能源', 'sector2': '制造', 'correlation': 0.78}
+            ],
+            'stock_correlations': [
+                {'stock1': '000001', 'stock2': '000002', 'correlation': 0.92},
+                {'stock1': '000003', 'stock2': '000004', 'correlation': 0.88},
+                {'stock1': '000005', 'stock2': '000006', 'correlation': 0.76}
+            ]
+        }
+
+        return jsonify({
+            'success': True,
+            'data': correlation_data
+        })
+
+    except Exception as e:
+        print(f"Error getting correlation analysis: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/export-data', methods=['POST'])
+def export_data():
+    """导出数据"""
+    try:
+        data = request.get_json()
+        date = data.get('date', '2025-07-16')
+        export_type = data.get('type', 'excel')
+        
+        # 模拟导出
+        filename = f'limit_analyse_{date}.{export_type}'
+        
+        return jsonify({
+            'success': True,
+            'message': '数据导出成功',
+            'data': {
+                'filename': filename,
+                'download_url': f'/downloads/{filename}'
+            }
+        })
+
+    except Exception as e:
+        print(f"Error exporting data: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500 
+
+@bp.route('/high-position-stocks', methods=['GET'])
+def get_high_position_stocks():
+    """获取高位股统计数据"""
+    try:
+        date = request.args.get('date', datetime.now().strftime('%Y%m%d'))
+        
+        # 模拟高位股数据 - 实际使用时需要连接真实的数据库
+        # 根据用户提供的表结构，查询连续涨停天数较多的股票
+        high_position_stocks = [
+            {
+                'stock_code': '000001',
+                'stock_name': '平安银行',
+                'price': 15.68,
+                'increase_rate': 10.02,
+                'limit_up_days': 5,
+                'continuous_limit_up': 3,
+                'industry': '银行',
+                'turnover_rate': 3.45,
+                'market_cap': 32000000000
+            },
+            {
+                'stock_code': '000002',
+                'stock_name': '万科A',
+                'price': 18.92,
+                'increase_rate': 9.98,
+                'limit_up_days': 4,
+                'continuous_limit_up': 2,
+                'industry': '房地产',
+                'turnover_rate': 5.67,
+                'market_cap': 21000000000
+            },
+            {
+                'stock_code': '600036',
+                'stock_name': '招商银行',
+                'price': 42.15,
+                'increase_rate': 8.45,
+                'limit_up_days': 6,
+                'continuous_limit_up': 4,
+                'industry': '银行',
+                'turnover_rate': 2.89,
+                'market_cap': 105000000000
+            },
+            {
+                'stock_code': '000858',
+                'stock_name': '五粮液',
+                'price': 168.50,
+                'increase_rate': 7.23,
+                'limit_up_days': 3,
+                'continuous_limit_up': 2,
+                'industry': '白酒',
+                'turnover_rate': 1.56,
+                'market_cap': 650000000000
+            },
+            {
+                'stock_code': '002415',
+                'stock_name': '海康威视',
+                'price': 35.68,
+                'increase_rate': 6.89,
+                'limit_up_days': 4,
+                'continuous_limit_up': 3,
+                'industry': '安防',
+                'turnover_rate': 4.12,
+                'market_cap': 33000000000
+            }
+        ]
+        
+        # 统计信息
+        total_count = len(high_position_stocks)
+        avg_continuous_days = sum(stock['continuous_limit_up'] for stock in high_position_stocks) / total_count if total_count > 0 else 0
+        
+        # 按连续涨停天数排序
+        high_position_stocks.sort(key=lambda x: x['continuous_limit_up'], reverse=True)
+
+        return jsonify({
+            'success': True,
+            'data': {
+                'stocks': high_position_stocks,
+                'statistics': {
+                    'total_count': total_count,
+                    'avg_continuous_days': round(avg_continuous_days, 2),
+                    'max_continuous_days': max([stock['continuous_limit_up'] for stock in high_position_stocks], default=0),
+                    'industry_distribution': {}
+                }
+            }
+        })
+
+    except Exception as e:
+        print(f"Error getting high position stocks: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500 

app/routes/stocks.py

@@ -0,0 +1,241 @@
+from flask import Blueprint, request, jsonify
+from app import db
+from clickhouse_driver import Client
+import pandas as pd
+from datetime import datetime, timedelta
+import pytz
+
+bp = Blueprint('stocks', __name__, url_prefix='/api/stock')
+
+def get_clickhouse_client():
+    """获取ClickHouse客户端"""
+    return Client('localhost', port=9000, user='default', password='', database='default')
+
+@bp.route('/quotes', methods=['GET', 'POST'])
+def get_stock_quotes():
+    """获取股票实时报价"""
+    try:
+        if request.method == 'GET':
+            # GET 请求从 URL 参数获取数据
+            codes = request.args.get('codes', '').split(',')
+            event_time_str = request.args.get('event_time')
+        else:
+            # POST 请求从 JSON 获取数据
+            codes = request.json.get('codes', [])
+            event_time_str = request.json.get('event_time')
+
+        if not codes:
+            return jsonify({'success': False, 'error': '请提供股票代码'}), 400
+
+        # 过滤空字符串
+        codes = [code.strip() for code in codes if code.strip()]
+
+        if not codes:
+            return jsonify({'success': False, 'error': '请提供有效的股票代码'}), 400
+
+        # 解析事件时间
+        event_time = None
+        if event_time_str:
+            try:
+                event_time = datetime.fromisoformat(event_time_str.replace('Z', '+00:00'))
+            except ValueError:
+                return jsonify({'success': False, 'error': '事件时间格式错误'}), 400
+
+        # 获取当前时间
+        now = datetime.now(pytz.timezone('Asia/Shanghai'))
+        
+        # 如果提供了事件时间，使用事件时间；否则使用当前时间
+        target_time = event_time if event_time else now
+
+        # 获取交易日和交易时间
+        def get_trading_day_and_times(event_datetime):
+            """获取交易日和交易时间列表"""
+            # 这里简化处理，实际应该查询交易日历
+            trading_day = event_datetime.strftime('%Y-%m-%d')
+            
+            # 生成交易时间列表 (9:30-11:30, 13:00-15:00)
+            morning_times = [f"{trading_day} {hour:02d}:{minute:02d}" 
+                           for hour in range(9, 12) 
+                           for minute in range(0, 60, 1)
+                           if not (hour == 9 and minute < 30) and not (hour == 11 and minute > 30)]
+            
+            afternoon_times = [f"{trading_day} {hour:02d}:{minute:02d}" 
+                             for hour in range(13, 16) 
+                             for minute in range(0, 60, 1)]
+            
+            return trading_day, morning_times + afternoon_times
+
+        trading_day, trading_times = get_trading_day_and_times(target_time)
+
+        # 模拟股票数据
+        results = {}
+        for code in codes:
+            # 这里应该从ClickHouse或其他数据源获取真实数据
+            # 现在使用模拟数据
+            import random
+            base_price = 10.0 + random.random() * 20.0
+            change = (random.random() - 0.5) * 2.0
+            
+            results[code] = {
+                'price': round(base_price, 2),
+                'change': round(change, 2),
+                'name': f'股票{code}'
+            }
+
+        return jsonify({
+            'success': True,
+            'data': results
+        })
+
+    except Exception as e:
+        print(f"Error getting stock quotes: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+@bp.route('/<stock_code>/kline')
+def get_stock_kline(stock_code):
+    """获取股票K线数据"""
+    try:
+        chart_type = request.args.get('type', 'daily')
+        event_time_str = request.args.get('event_time')
+        
+        if not event_time_str:
+            return jsonify({'success': False, 'error': '请提供事件时间'}), 400
+
+        try:
+            event_datetime = datetime.fromisoformat(event_time_str.replace('Z', '+00:00'))
+        except ValueError:
+            return jsonify({'success': False, 'error': '事件时间格式错误'}), 400
+
+        # 获取股票名称（这里简化处理）
+        stock_name = f'股票{stock_code}'
+
+        if chart_type == 'daily':
+            return get_daily_kline(stock_code, event_datetime, stock_name)
+        elif chart_type == 'minute':
+            return get_minute_kline(stock_code, event_datetime, stock_name)
+        elif chart_type == 'timeline':
+            return get_timeline_data(stock_code, event_datetime, stock_name)
+        else:
+            return jsonify({'error': f'Unsupported chart type: {chart_type}'}), 400
+
+    except Exception as e:
+        print(f"Error getting stock kline: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+def get_daily_kline(stock_code, event_datetime, stock_name):
+    """获取日K线数据"""
+    try:
+        # 模拟日K线数据
+        data = []
+        base_price = 10.0
+        for i in range(30):
+            date = (event_datetime - timedelta(days=30-i)).strftime('%Y-%m-%d')
+            open_price = base_price + (i * 0.1) + (i % 3 - 1) * 0.5
+            close_price = open_price + (i % 5 - 2) * 0.3
+            high_price = max(open_price, close_price) + 0.2
+            low_price = min(open_price, close_price) - 0.2
+            volume = 1000000 + i * 50000
+            
+            data.append({
+                'date': date,
+                'open': round(open_price, 2),
+                'close': round(close_price, 2),
+                'high': round(high_price, 2),
+                'low': round(low_price, 2),
+                'volume': volume
+            })
+
+        return jsonify({
+            'code': stock_code,
+            'name': stock_name,
+            'trade_date': event_datetime.strftime('%Y-%m-%d'),
+            'data': data
+        })
+
+    except Exception as e:
+        print(f"Error getting daily kline: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+def get_minute_kline(stock_code, event_datetime, stock_name):
+    """获取分钟K线数据"""
+    try:
+        # 模拟分钟K线数据
+        data = []
+        base_price = 10.0
+        trading_times = []
+        
+        # 生成交易时间
+        for hour in range(9, 16):
+            if hour == 12:
+                continue
+            for minute in range(0, 60):
+                if (hour == 9 and minute < 30) or (hour == 11 and minute > 30):
+                    continue
+                trading_times.append(f"{hour:02d}:{minute:02d}")
+
+        for i, time in enumerate(trading_times):
+            open_price = base_price + (i * 0.01) + (i % 10 - 5) * 0.02
+            close_price = open_price + (i % 7 - 3) * 0.01
+            high_price = max(open_price, close_price) + 0.01
+            low_price = min(open_price, close_price) - 0.01
+            volume = 50000 + i * 1000
+            
+            data.append({
+                'time': time,
+                'open': round(open_price, 2),
+                'close': round(close_price, 2),
+                'high': round(high_price, 2),
+                'low': round(low_price, 2),
+                'volume': volume
+            })
+
+        return jsonify({
+            'code': stock_code,
+            'name': stock_name,
+            'trade_date': event_datetime.strftime('%Y-%m-%d'),
+            'data': data
+        })
+
+    except Exception as e:
+        print(f"Error getting minute kline: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+def get_timeline_data(stock_code, event_datetime, stock_name):
+    """获取分时图数据"""
+    try:
+        # 模拟分时图数据
+        data = []
+        base_price = 10.0
+        trading_times = []
+        
+        # 生成交易时间
+        for hour in range(9, 16):
+            if hour == 12:
+                continue
+            for minute in range(0, 60):
+                if (hour == 9 and minute < 30) or (hour == 11 and minute > 30):
+                    continue
+                trading_times.append(f"{hour:02d}:{minute:02d}")
+
+        for i, time in enumerate(trading_times):
+            price = base_price + (i * 0.01) + (i % 10 - 5) * 0.02
+            avg_price = price + (i % 5 - 2) * 0.01
+            volume = 50000 + i * 1000
+            
+            data.append({
+                'time': time,
+                'price': round(price, 2),
+                'avg_price': round(avg_price, 2),
+                'volume': volume
+            })
+
+        return jsonify({
+            'code': stock_code,
+            'name': stock_name,
+            'trade_date': event_datetime.strftime('%Y-%m-%d'),
+            'data': data
+        })
+
+    except Exception as e:
+        print(f"Error getting timeline data: {e}")
+        return jsonify({'success': False, 'error': str(e)}), 500 

certs/apiclient_cert.pem

@@ -0,0 +1,25 @@
+-----BEGIN CERTIFICATE-----
+MIIEKDCCAxCgAwIBAgIUNltE7/qXxbotf9wJrhpJClsDclIwDQYJKoZIhvcNAQEL
+BQAwXjELMAkGA1UEBhMCQ04xEzARBgNVBAoTClRlbnBheS5jb20xHTAbBgNVBAsT
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+DCTljJfkuqzku7flgLzliY3msr/np5HmioDmnInpmZDlhazlj7gxCzAJBgNVBAYT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+-----END CERTIFICATE-----

certs/apiclient_key.pem

@@ -0,0 +1,28 @@
+-----BEGIN PRIVATE KEY-----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+-----END PRIVATE KEY-----

final_trading_simulation_fixes.md

@@ -0,0 +1,146 @@
+# 模拟盘最终修复总结
+
+## 🎯 修复的问题
+
+### 1. ✅ 编译错误修复
+**问题**：`Card` 组件重复导入
+**解决**：
+- 移除了自定义 Card 组件的重复导入
+- 统一使用 Chakra UI 的 Card 组件
+- 保留必要的图表组件导入
+
+### 2. ✅ 版面布局重新设计
+**改进**：
+- **主要功能放在上面**：交易面板、持仓、历史、融资融券
+- **统计数据放在下面**：账户概览、资产走势等分析图表
+- **现代化标签页**：使用 emoji 图标和圆角设计
+
+### 3. ✅ 真实数据替换Mock数据
+**改进**：
+- **资产走势图**：使用真实的 `getAssetHistory` 数据
+- **空数据处理**：当没有历史数据时显示友好提示
+- **动态显示**：只在有数据时显示图表
+
+### 4. ✅ 价格显示修复
+**问题**：搜索股票时价格显示为 0.00
+**解决**：
+- **后端修复**：`search_stocks` 接口现在返回 `current_price`
+- **前端修复**：正确使用 `stock.current_price` 而不是硬编码0
+- **价格获取优化**：扩大查询范围，多重备选方案
+
+## 🚀 新的页面结构
+
+### 上半部分：主要功能
+```
+┌─────────────────────────────────────────┐
+│ 💹 交易面板 | 📊 我的持仓 | 📋 交易历史 | 💰 融资融券 │
+├─────────────────────────────────────────┤
+│                                         │
+│           主要交易功能区域                │
+│                                         │
+└─────────────────────────────────────────┘
+```
+
+### 下半部分：统计分析
+```
+┌─────────────────────────────────────────┐
+│            📊 账户统计分析                │
+│  ┌─────────────┐  ┌─────────────────┐   │
+│  │   资产卡片   │  │   资产配置图     │   │
+│  └─────────────┘  └─────────────────┘   │
+└─────────────────────────────────────────┘
+┌─────────────────────────────────────────┐
+│            📈 资产走势分析                │
+│         （有数据时显示图表）              │
+│       （无数据时显示友好提示）            │
+└─────────────────────────────────────────┘
+```
+
+## 🔧 关键代码修改
+
+### 1. 价格数据修复
+**后端** (`app_2.py`):
+```python
+# search_stocks 接口现在返回价格
+stocks.append({
+    'stock_code': row.stock_code,
+    'stock_name': row.stock_name,
+    'current_price': current_price or 0,  # 添加真实价格
+    # ... 其他字段
+})
+```
+
+**前端** (`TradingPanel.js`):
+```javascript
+// 使用真实价格而不是0
+price: stock.current_price || 0, // 使用后端返回的真实价格
+```
+
+### 2. 真实数据处理
+**主页面** (`index.js`):
+```javascript
+// 获取真实资产历史
+const [assetHistory, setAssetHistory] = useState([]);
+const { getAssetHistory } = useTradingAccount();
+
+useEffect(() => {
+  if (account) {
+    getAssetHistory(30).then(data => {
+      setAssetHistory(data || []);
+    });
+  }
+}, [account, getAssetHistory]);
+
+// 只在有数据时显示图表
+{hasAssetData && (
+  <LineChart chartData={assetTrendData} chartOptions={assetTrendOptions} />
+)}
+
+// 无数据时显示友好提示
+{!hasAssetData && account && (
+  <VStack spacing={4} py={8}>
+    <Text fontSize="lg" color="gray.500">📊 暂无历史数据</Text>
+    <Text fontSize="sm" color="gray.400">
+      开始交易后，这里将显示您的资产走势图表和详细统计分析
+    </Text>
+  </VStack>
+)}
+```
+
+### 3. 现代化标签页设计
+```javascript
+<TabList bg={useColorModeValue('white', 'gray.800')} p={2} borderRadius="xl" shadow="sm">
+  <Tab fontWeight="bold">💹 交易面板</Tab>
+  <Tab fontWeight="bold">📊 我的持仓</Tab>
+  <Tab fontWeight="bold">📋 交易历史</Tab>
+  <Tab fontWeight="bold">💰 融资融券</Tab>
+</TabList>
+```
+
+## 🎯 预期效果
+
+### 搜索股票
+- ✅ 显示真实价格（如：寒武纪 ¥1394.94）
+- ✅ 价格不再显示 0.00
+- ✅ 搜索结果包含完整的股票信息
+
+### 页面布局
+- ✅ 主要功能优先显示（交易、持仓等）
+- ✅ 统计分析放在下方（不干扰主要操作）
+- ✅ 现代化的标签页设计
+
+### 数据显示
+- ✅ 使用真实的后端数据
+- ✅ 优雅处理空数据情况
+- ✅ 动态显示图表和提示
+
+## 🚀 现在可以：
+
+1. **重新编译**：`npm run build` 应该成功
+2. **重启服务**：让后端价格获取修改生效
+3. **测试功能**：
+   - 搜索股票应该显示真实价格
+   - 页面布局更加合理
+   - 空数据时有友好提示
+
+所有问题都已修复，现在模拟盘应该可以正常显示价格数据了！🎉

gulpfile.js

@@ -0,0 +1,76 @@
+const gulp = require("gulp");
+const gap = require("gulp-append-prepend");
+
+gulp.task("licenses", async function () {
+  // this is to add Creative Tim licenses in the production mode for the minified js
+  gulp
+    .src("build/static/js/*chunk.js", { base: "./" })
+    .pipe(
+      gap.prependText(`/*!
+
+      =========================================================
+      * Argon Dashboard Chakra PRO - v1.0.0
+      =========================================================
+
+      * Product Page: https://www.creative-tim.com/product/argon-dashboard-chakra-pro
+      * Copyright 2022 Creative Tim (https://www.creative-tim.com/)
+
+      * Designed and Coded by Simmmple & Creative Tim
+
+      =========================================================
+
+      * The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+      
+      */`)
+    )
+    .pipe(gulp.dest("./", { overwrite: true }));
+
+  // this is to add Creative Tim licenses in the production mode for the minified html
+  gulp
+    .src("build/index.html", { base: "./" })
+    .pipe(
+      gap.prependText(`<!--
+      /*!
+      
+      =========================================================
+      * Argon Dashboard Chakra PRO - v1.0.0
+      =========================================================
+
+      * Product Page: https://www.creative-tim.com/product/argon-dashboard-chakra-pro
+      * Copyright 2022 Creative Tim (https://www.creative-tim.com/)
+
+      * Designed and Coded by Simmmple & Creative Tim
+
+      =========================================================
+
+      * The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+      
+      */
+      -->`)
+    )
+    .pipe(gulp.dest("./", { overwrite: true }));
+
+  // this is to add Creative Tim licenses in the production mode for the minified css
+  gulp
+    .src("build/static/css/*chunk.css", { base: "./" })
+    .pipe(
+      gap.prependText(`/*!
+
+      =========================================================
+      * Argon Dashboard Chakra PRO - v1.0.0
+      =========================================================
+
+      * Product Page: https://www.creative-tim.com/product/argon-dashboard-chakra-pro
+      * Copyright 2022 Creative Tim (https://www.creative-tim.com/)
+
+      * Designed and Coded by Simmmple & Creative Tim
+
+      =========================================================
+
+      * The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+      
+      */`)
+    )
+    .pipe(gulp.dest("./", { overwrite: true }));
+  return;
+});

jsconfig.json

@@ -0,0 +1,8 @@
+{
+  "compilerOptions": {
+    "baseUrl": "src",
+    "paths": {
+      "*": ["src/*"]
+    }
+  }
+}

package.json

@@ -0,0 +1,105 @@
+{
+  "name": "argon-dashboard-chakra-pro",
+  "version": "2.0.0",
+  "private": true,
+  "homepage": "https://demos.creative-tim.com/argon-dashboard-chakra-pro/#/",
+  "dependencies": {
+    "@ant-design/icons": "^6.0.0",
+    "@asseinfo/react-kanban": "^2.2.0",
+    "@chakra-ui/icons": "^2.1.1",
+    "@chakra-ui/react": "^2.8.2",
+    "@chakra-ui/theme-tools": "^1.3.6",
+    "@emotion/cache": "^11.4.0",
+    "@emotion/react": "^11.4.0",
+    "@emotion/styled": "^11.3.0",
+    "@fontsource/open-sans": "^4.5.0",
+    "@fontsource/raleway": "^4.5.0",
+    "@fontsource/roboto": "^4.5.0",
+    "@fullcalendar/daygrid": "^5.9.0",
+    "@fullcalendar/interaction": "^5.9.0",
+    "@fullcalendar/react": "^5.9.0",
+    "@visx/visx": "^3.12.0",
+    "antd": "^5.26.4",
+    "apexcharts": "^3.27.3",
+    "axios": "^1.10.0",
+    "classnames": "2.3.1",
+    "date-fns": "^2.23.0",
+    "draft-js": "^0.11.7",
+    "echarts": "^5.6.0",
+    "echarts-for-react": "^3.0.2",
+    "echarts-wordcloud": "^2.1.0",
+    "framer-motion": "^4.1.17",
+    "fullcalendar": "^5.9.0",
+    "globalize": "^1.7.0",
+    "leaflet": "^1.9.4",
+    "match-sorter": "6.3.0",
+    "moment": "^2.29.1",
+    "nouislider": "15.0.0",
+    "react": "18.3.1",
+    "react-apexcharts": "^1.3.9",
+    "react-big-calendar": "^0.33.2",
+    "react-bootstrap-sweetalert": "5.2.0",
+    "react-circular-slider-svg": "^0.1.5",
+    "react-custom-scrollbars-2": "^4.4.0",
+    "react-datetime": "^3.0.4",
+    "react-dom": "^18.3.1",
+    "react-dropzone": "^11.4.2",
+    "react-github-btn": "^1.2.1",
+    "react-icons": "^4.2.0",
+    "react-input-pin-code": "^1.1.5",
+    "react-jvectormap": "0.0.16",
+    "react-leaflet": "^3.2.5",
+    "react-markdown": "^10.1.0",
+    "react-quill": "^2.0.0-beta.4",
+    "react-router-dom": "^6.4.0",
+    "react-scripts": "^5.0.1",
+    "react-scroll": "^1.8.4",
+    "react-swipeable-views": "0.13.9",
+    "react-table": "^7.7.0",
+    "react-tagsinput": "3.19.0",
+    "react-to-print": "^2.13.0",
+    "sass": "^1.49.9",
+    "styled-components": "^5.3.11",
+    "stylis": "^4.0.10",
+    "stylis-plugin-rtl": "^2.1.1",
+    "three": "0.109.0"
+  },
+  "resolutions": {
+    "react-error-overlay": "6.0.9",
+    "@types/react": "18.2.0",
+    "@types/react-dom": "18.2.0"
+  },
+  "proxy": "http://localhost:5001",
+  "scripts": {
+    "start": "react-scripts --openssl-legacy-provider start",
+    "build": "react-scripts build && gulp licenses",
+    "test": "react-scripts test --env=jsdom",
+    "eject": "react-scripts eject",
+    "deploy": "npm run build",
+    "lint:check": "eslint . --ext=js,jsx;  exit 0",
+    "lint:fix": "eslint . --ext=js,jsx --fix;  exit 0",
+    "install:clean": "rm -rf node_modules/ && rm -rf package-lock.json && npm install && npm start"
+  },
+  "devDependencies": {
+    "ajv": "^8.17.1",
+    "autoprefixer": "^10.4.21",
+    "eslint-config-prettier": "8.3.0",
+    "eslint-plugin-prettier": "3.4.0",
+    "gulp": "4.0.2",
+    "gulp-append-prepend": "1.0.9",
+    "prettier": "2.2.1",
+    "react-error-overlay": "6.0.9"
+  },
+  "browserslist": {
+    "production": [
+      ">0.2%",
+      "not dead",
+      "not op_mini all"
+    ],
+    "development": [
+      ">0.2%",
+      "not dead",
+      "not op_mini all"
+    ]
+  }
+}

postcss.config.js

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+module.exports = {
+  plugins: [
+    require('tailwindcss'),
+    require('autoprefixer'),
+  ],
+}

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+</svg>

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+</defs>
+</svg>

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