feat: complete trading system with FastAPI backend, web frontend, and auto-analysis
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Stock Buddy Bot
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backend/main.py
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250
backend/main.py
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"""
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Stock Buddy 交易系统 - 主入口
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FastAPI + SQLite + APScheduler
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"""
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from fastapi import FastAPI, HTTPException, BackgroundTasks
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.staticfiles import StaticFiles
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from contextlib import asynccontextmanager
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from apscheduler.schedulers.asyncio import AsyncIOScheduler
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from apscheduler.triggers.cron import CronTrigger
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from datetime import datetime, timedelta
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import uvicorn
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from database import init_db, SessionLocal
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from models import PositionCreate, PositionResponse, StockAnalysisRequest, AnalysisResult
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from services.stock_service import StockService
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from services.sentiment_service import SentimentService
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from services.strategy_service import StrategyService
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from services.llm_service import LLMService
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# 初始化数据库
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init_db()
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# 定时任务调度器
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scheduler = AsyncIOScheduler()
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async def daily_analysis_task():
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"""每日定时任务：分析所有持仓股票"""
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print(f"[{datetime.now()}] 开始每日自动分析...")
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db = SessionLocal()
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try:
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stock_service = StockService(db)
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sentiment_service = SentimentService(db)
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strategy_service = StrategyService(db)
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llm_service = LLMService()
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# 获取所有持仓
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positions = stock_service.get_all_positions()
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for pos in positions:
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try:
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# 1. 更新股票数据
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stock_data = stock_service.update_stock_data(pos.ticker)
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# 2. 生成舆情分析
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sentiment = await llm_service.analyze_sentiment(pos.name, pos.ticker)
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sentiment_service.save_sentiment(pos.ticker, sentiment)
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# 3. 计算策略信号
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signal = strategy_service.calculate_signal(
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pos.ticker,
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stock_data,
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sentiment['score']
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)
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# 4. 保存分析结果
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stock_service.save_analysis_result(pos.ticker, {
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'signal': signal,
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'sentiment': sentiment,
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'updated_at': datetime.now().isoformat()
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})
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print(f" ✅ {pos.name}: {signal['action']} (评分:{signal['score']:.2f})")
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except Exception as e:
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print(f" ❌ {pos.name}: {e}")
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print(f"[{datetime.now()}] 每日分析完成")
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finally:
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db.close()
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""应用生命周期管理"""
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# 启动时
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print("🚀 Stock Buddy 交易系统启动")
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# 启动定时任务（每天9:00运行）
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scheduler.add_job(
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daily_analysis_task,
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CronTrigger(hour=9, minute=0),
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id='daily_analysis',
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replace_existing=True
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)
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scheduler.start()
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print("⏰ 定时任务已启动（每天9:00）")
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yield
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# 关闭时
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scheduler.shutdown()
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print("🛑 系统关闭")
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app = FastAPI(
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title="Stock Buddy API",
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description="港股AI交易分析系统",
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version="1.0.0",
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lifespan=lifespan
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)
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# CORS配置
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# ═════════════════════════════════════════════════════════════════════
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# API路由
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# ═════════════════════════════════════════════════════════════════════
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@app.get("/")
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async def root():
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return {"message": "Stock Buddy API", "version": "1.0.0"}
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# ═════════════════════════════════════════════════════════════════════
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# 持仓管理
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# ═════════════════════════════════════════════════════════════════════
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@app.get("/api/positions", response_model=list[PositionResponse])
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async def get_positions():
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"""获取所有持仓"""
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db = SessionLocal()
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try:
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service = StockService(db)
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return service.get_all_positions()
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finally:
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db.close()
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@app.post("/api/positions", response_model=PositionResponse)
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async def create_position(position: PositionCreate):
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"""添加持仓"""
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db = SessionLocal()
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try:
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service = StockService(db)
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return service.create_position(position)
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finally:
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db.close()
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@app.delete("/api/positions/{position_id}")
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async def delete_position(position_id: int):
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"""删除持仓"""
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db = SessionLocal()
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try:
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service = StockService(db)
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service.delete_position(position_id)
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return {"message": "删除成功"}
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finally:
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db.close()
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@app.put("/api/positions/{position_id}", response_model=PositionResponse)
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async def update_position(position_id: int, position: PositionCreate):
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"""更新持仓"""
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db = SessionLocal()
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try:
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service = StockService(db)
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return service.update_position(position_id, position)
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finally:
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db.close()
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# ═════════════════════════════════════════════════════════════════════
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# 分析功能
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# ═════════════════════════════════════════════════════════════════════
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@app.post("/api/analyze", response_model=AnalysisResult)
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async def analyze_stock(request: StockAnalysisRequest):
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"""手动分析股票（支持新增股票）"""
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db = SessionLocal()
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try:
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stock_service = StockService(db)
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sentiment_service = SentimentService(db)
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strategy_service = StrategyService(db)
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llm_service = LLMService()
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# 1. 获取/更新股票数据
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ticker = request.ticker if request.ticker else stock_service.search_ticker(request.stock_name)
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stock_data = stock_service.update_stock_data(ticker)
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# 2. 生成舆情分析（异步）
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sentiment = await llm_service.analyze_sentiment(request.stock_name, ticker)
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sentiment_service.save_sentiment(ticker, sentiment)
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# 3. 计算策略信号
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signal = strategy_service.calculate_signal(ticker, stock_data, sentiment['score'])
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# 4. 技术分析详情
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tech_analysis = strategy_service.get_technical_analysis(ticker, stock_data)
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return AnalysisResult(
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stock_name=request.stock_name,
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ticker=ticker,
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signal=signal,
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sentiment=sentiment,
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technical=tech_analysis,
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timestamp=datetime.now().isoformat()
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)
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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finally:
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db.close()
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@app.get("/api/analysis/{ticker}")
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async def get_latest_analysis(ticker: str):
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"""获取最新分析结果"""
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db = SessionLocal()
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try:
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service = StockService(db)
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result = service.get_latest_analysis(ticker)
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if not result:
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raise HTTPException(status_code=404, detail="暂无分析数据")
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return result
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finally:
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db.close()
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# ═════════════════════════════════════════════════════════════════════
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# 实时行情
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# ═════════════════════════════════════════════════════════════════════
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@app.get("/api/quote/{ticker}")
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async def get_quote(ticker: str):
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"""获取实时行情"""
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db = SessionLocal()
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try:
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service = StockService(db)
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return service.get_realtime_quote(ticker)
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finally:
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db.close()
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# ═════════════════════════════════════════════════════════════════════
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# 手动触发任务
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# ═════════════════════════════════════════════════════════════════════
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@app.post("/api/tasks/daily-analysis")
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async def trigger_daily_analysis(background_tasks: BackgroundTasks):
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"""手动触发每日分析"""
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background_tasks.add_task(daily_analysis_task)
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return {"message": "每日分析任务已触发", "timestamp": datetime.now().isoformat()}
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# ═════════════════════════════════════════════════════════════════════
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# 前端静态文件
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# ═════════════════════════════════════════════════════════════════════
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app.mount("/app", StaticFiles(directory="../frontend", html=True), name="frontend")
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if __name__ == "__main__":
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uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True)
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