Initial commit: stock analysis backend and prototype UI.

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/main.py

@@ -0,0 +1,624 @@
+"""智策股票终端 — FastAPI 后端入口。
+
+- /api/*  : 数据接口（基于 AkShare，带缓存与降级）
+- /       : 托管前端原型（prototype 目录）
+"""
+import os
+import json
+import datetime as dt
+from contextlib import asynccontextmanager
+
+from fastapi import FastAPI, Query
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.staticfiles import StaticFiles
+from sqlalchemy import select, func, desc
+
+from pydantic import BaseModel
+
+import akshare_service as svc
+import config
+import scheduler
+import backtest as bt
+import ai
+import signals as sig
+import report as rpt
+import portfolio as pf
+import llm
+import alerts as al
+import notifier
+from db import init_db, get_session
+from models import (DailyQuote, IndexDaily, SectorDaily, FundFlowDaily,
+                    SentimentDaily, DragonTiger, Security, JobRun, StockMetric, Trade,
+                    AlertRule, AlertEvent)
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    try:
+        init_db()
+        scheduler.start_scheduler()
+        print("[startup] db + scheduler ready")
+    except Exception as e:
+        print("[startup] WARN:", repr(e)[:160])
+    yield
+
+
+app = FastAPI(title="智策股票终端 API", version="0.2.0", lifespan=lifespan)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# 自选股本地存储
+BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+WATCH_FILE = os.path.join(BASE_DIR, "watchlist.json")
+DEFAULT_WATCH = ["600519", "300750", "002594", "688981", "300059", "601012"]
+
+
+def load_watch():
+    if os.path.exists(WATCH_FILE):
+        try:
+            with open(WATCH_FILE, "r", encoding="utf-8") as f:
+                return json.load(f)
+        except Exception:
+            pass
+    return DEFAULT_WATCH
+
+
+def save_watch(symbols):
+    with open(WATCH_FILE, "w", encoding="utf-8") as f:
+        json.dump(symbols, f, ensure_ascii=False)
+
+
+# ============ API ============
+@app.get("/api/health")
+def health():
+    return {"ok": True, "akshare": svc.AK_OK}
+
+
+@app.get("/api/indices")
+def indices():
+    return svc.get_indices()
+
+
+@app.get("/api/kline")
+def kline(symbol: str = Query("600519"), days: int = Query(120, ge=20, le=500)):
+    return svc.get_kline(symbol, days)
+
+
+@app.get("/api/sentiment")
+def sentiment():
+    return svc.get_sentiment()
+
+
+@app.get("/api/treemap")
+def treemap(mode: str = Query("sector")):
+    return svc.get_treemap(mode)
+
+
+@app.get("/api/fundflow")
+def fundflow():
+    return svc.get_fund_flow()
+
+
+@app.get("/api/hot/stocks")
+def hot_stocks():
+    return svc.get_hot_stocks()
+
+
+@app.get("/api/hot/sectors")
+def hot_sectors():
+    return svc.get_industry_boards()
+
+
+@app.get("/api/dragon")
+def dragon():
+    return svc.get_dragon_tiger()
+
+
+@app.get("/api/watchlist")
+def watchlist():
+    return svc.get_watchlist(load_watch())
+
+
+@app.post("/api/watchlist/{code}")
+def watch_add(code: str):
+    w = load_watch()
+    if code not in w:
+        w.append(code)
+        save_watch(w)
+    return {"ok": True, "list": w}
+
+
+@app.delete("/api/watchlist/{code}")
+def watch_del(code: str):
+    w = [c for c in load_watch() if c != code]
+    save_watch(w)
+    return {"ok": True, "list": w}
+
+
+# ============ 数据中台 ============
+@app.get("/api/admin/status")
+def admin_status():
+    counts, last_dates = {}, {}
+    with get_session() as s:
+        for label, model in [("securities", Security), ("quotes_daily", DailyQuote),
+                             ("index_daily", IndexDaily), ("sector_daily", SectorDaily),
+                             ("fund_flow_daily", FundFlowDaily), ("sentiment_daily", SentimentDaily),
+                             ("dragon_tiger", DragonTiger)]:
+            counts[label] = s.execute(select(func.count()).select_from(model)).scalar() or 0
+            if hasattr(model, "date"):
+                d = s.execute(select(func.max(model.date))).scalar()
+                last_dates[label] = d.isoformat() if d else None
+        jobs = s.execute(select(JobRun).order_by(desc(JobRun.id)).limit(8)).scalars().all()
+        job_list = [{"id": j.id, "job": j.job, "status": j.status,
+                     "started": j.started_at.strftime("%m-%d %H:%M:%S") if j.started_at else "",
+                     "finished": j.finished_at.strftime("%H:%M:%S") if j.finished_at else "",
+                     "message": j.message[:200]} for j in jobs]
+    return {"counts": counts, "last_dates": last_dates, "jobs": job_list,
+            "running": scheduler.is_running(), "universe": config.DEFAULT_UNIVERSE,
+            "schedule": f"周一至周五 {config.INGEST_HOUR:02d}:{config.INGEST_MINUTE:02d}"}
+
+
+@app.post("/api/admin/ingest")
+def admin_ingest():
+    if scheduler.is_running():
+        return {"started": False, "msg": "已有入库任务在执行"}
+    return scheduler.trigger_async()
+
+
+@app.post("/api/admin/ingest_all")
+def admin_ingest_all():
+    return scheduler.trigger_all_async()
+
+
+@app.get("/api/db/kline")
+def db_kline(symbol: str = Query("600519"), days: int = Query(250, ge=20, le=1000)):
+    with get_session() as s:
+        rows = s.execute(
+            select(DailyQuote).where(DailyQuote.code == symbol)
+            .order_by(DailyQuote.date.desc()).limit(days)
+        ).scalars().all()
+    rows = list(reversed(rows))
+    if not rows:
+        return {"source": "db", "empty": True, "symbol": symbol, "dates": [], "ohlc": [], "vols": []}
+    return {"source": "db", "symbol": symbol,
+            "dates": [r.date.strftime("%m/%d") for r in rows],
+            "ohlc": [[r.open, r.close, r.low, r.high] for r in rows],
+            "vols": [r.volume for r in rows]}
+
+
+@app.get("/api/db/sentiment_history")
+def db_sentiment_history(days: int = Query(60, ge=5, le=365)):
+    with get_session() as s:
+        rows = s.execute(select(SentimentDaily).order_by(SentimentDaily.date.desc()).limit(days)).scalars().all()
+    rows = list(reversed(rows))
+    return {"dates": [r.date.isoformat() for r in rows],
+            "up": [r.up for r in rows], "down": [r.down for r in rows],
+            "limit_up": [r.limit_up for r in rows]}
+
+
+@app.get("/api/review/daily")
+def review_daily(date: str = Query(None)):
+    with get_session() as s:
+        if date:
+            d = dt.date.fromisoformat(date)
+        else:
+            d = s.execute(select(func.max(SectorDaily.date))).scalar()
+        if not d:
+            return {"ok": False, "msg": "暂无入库数据，请先在数据中台执行入库"}
+        sectors = s.execute(select(SectorDaily).where(SectorDaily.date == d).order_by(SectorDaily.pct.desc())).scalars().all()
+        flows = s.execute(select(FundFlowDaily).where(FundFlowDaily.date == d).order_by(FundFlowDaily.net.desc())).scalars().all()
+        senti = s.execute(select(SentimentDaily).where(SentimentDaily.date == d)).scalar_one_or_none()
+        lhb = s.execute(select(DragonTiger).where(DragonTiger.date == d).order_by(DragonTiger.net.desc()).limit(10)).scalars().all()
+
+    top_sec = [{"name": x.name, "pct": x.pct} for x in sectors[:8]]
+    bot_sec = [{"name": x.name, "pct": x.pct} for x in sectors[-5:]]
+    inflow = [{"name": x.name, "net": x.net} for x in flows[:8]]
+    outflow = [{"name": x.name, "net": x.net} for x in flows[-5:][::-1]]
+    senti_d = ({"up": senti.up, "down": senti.down, "limit_up": senti.limit_up,
+                "limit_down": senti.limit_down} if senti else None)
+
+    summary = _gen_review_text(d, senti_d, top_sec, inflow)
+    return {"ok": True, "date": d.isoformat(), "sentiment": senti_d,
+            "top_sectors": top_sec, "weak_sectors": bot_sec,
+            "inflow": inflow, "outflow": outflow,
+            "dragon": [{"name": x.name, "code": x.code, "net": x.net, "pct": x.pct} for x in lhb],
+            "summary": summary}
+
+
+def _gen_review_text(d, senti, top_sec, inflow):
+    parts = [f"【{d.isoformat()} 复盘】"]
+    if senti:
+        tone = "情绪偏暖" if senti["up"] > senti["down"] else "情绪偏弱"
+        parts.append(f"全市场上涨 {senti['up']} 家、下跌 {senti['down']} 家，涨停 {senti['limit_up']} 家、跌停 {senti['limit_down']} 家，{tone}。")
+    if top_sec:
+        names = "、".join(x["name"] for x in top_sec[:3])
+        parts.append(f"领涨板块：{names}。")
+    if inflow:
+        names = "、".join(x["name"] for x in inflow[:3])
+        parts.append(f"主力净流入居前：{names}。")
+    parts.append("注：以上为基于入库数据的自动统计，AI 智能点评将在 AI 分析模块接入大模型后生成。")
+    return " ".join(parts)
+
+
+@app.get("/api/backtest")
+def backtest_api(symbol: str = Query("600519"), fast: int = Query(5, ge=2, le=60),
+                 slow: int = Query(20, ge=5, le=250)):
+    if fast >= slow:
+        return {"ok": False, "msg": "快线周期需小于慢线周期"}
+    return bt.run_backtest(symbol, fast, slow)
+
+
+# ============ 全市场选股 ============
+STRATEGIES = {
+    "surge": "最近暴涨（5日涨幅≥20%）",
+    "plunge": "最近暴跌（5日跌幅≥15%）",
+    "dip": "超跌抄底（60日分位≤20%且当日企稳）",
+    "breakout": "突破走强（逼近60日新高）",
+    "ma_bull": "均线多头（MA5>10>20）",
+    "volume": "放量上攻（量比≥2且上涨）",
+    "macd_gold": "MACD金叉",
+    "strong": "强势连涨（≥3日连阳）",
+}
+
+
+@app.get("/api/screen/strategies")
+def screen_strategies():
+    return {"list": [{"id": k, "name": v} for k, v in STRATEGIES.items()]}
+
+
+@app.get("/api/screen")
+def screen(strategy: str = Query("surge"), limit: int = Query(60, ge=10, le=300),
+           min_amount: float = Query(0.0)):
+    M = StockMetric
+    q = select(M)
+    order = M.ret5.desc()
+    if strategy == "surge":
+        q = q.where(M.ret5 >= 20)
+    elif strategy == "plunge":
+        q = q.where(M.ret5 <= -15); order = M.ret5.asc()
+    elif strategy == "dip":
+        q = q.where(M.pos60 <= 0.2, M.pct > 0); order = M.pos60.asc()
+    elif strategy == "breakout":
+        q = q.where(M.pos60 >= 0.95, M.pct > 0); order = M.ret20.desc()
+    elif strategy == "ma_bull":
+        q = q.where(M.ma_bull.is_(True)); order = M.ret20.desc()
+    elif strategy == "volume":
+        q = q.where(M.vol_ratio >= 2, M.pct > 0); order = M.vol_ratio.desc()
+    elif strategy == "macd_gold":
+        q = q.where(M.macd_gold.is_(True)); order = M.ret5.desc()
+    elif strategy == "strong":
+        q = q.where(M.up_streak >= 3); order = M.up_streak.desc()
+    if min_amount > 0:
+        q = q.where(M.amount >= min_amount)
+    q = q.order_by(order).limit(limit)
+    with get_session() as s:
+        rows = s.execute(q).scalars().all()
+        total = s.execute(select(func.count()).select_from(M)).scalar() or 0
+    return {"strategy": strategy, "name": STRATEGIES.get(strategy, strategy), "pool_size": total,
+            "count": len(rows), "list": [{
+                "code": r.code, "name": r.name, "close": r.close, "pct": r.pct,
+                "ret5": r.ret5, "ret20": r.ret20, "vol_ratio": r.vol_ratio,
+                "rsi14": r.rsi14, "pos60": round(r.pos60 * 100, 1), "amount": r.amount,
+                "up_streak": r.up_streak} for r in rows]}
+
+
+@app.get("/api/securities/search")
+def securities_search(q: str = Query("", min_length=0), limit: int = Query(15, le=50)):
+    with get_session() as s:
+        stmt = select(Security)
+        if q:
+            stmt = stmt.where((Security.code.like(f"{q}%")) | (Security.name.like(f"%{q}%")))
+        rows = s.execute(stmt.limit(limit)).scalars().all()
+    return {"list": [{"code": r.code, "name": r.name} for r in rows]}
+
+
+# ============ 个股复盘（K线 + 买卖点 + 回放） ============
+def _ma_list(close, n):
+    out = [None] * len(close)
+    for i in range(len(close)):
+        if i >= n - 1:
+            out[i] = round(sum(close[i - n + 1:i + 1]) / n, 3)
+    return out
+
+
+@app.get("/api/review/stock")
+def review_stock(symbol: str = Query("600519"), days: int = Query(250, ge=40, le=1000),
+                 fast: int = Query(5), slow: int = Query(20)):
+    with get_session() as s:
+        rows = s.execute(
+            select(DailyQuote).where(DailyQuote.code == symbol)
+            .order_by(DailyQuote.date.desc()).limit(days)
+        ).scalars().all()
+        sec = s.get(Security, symbol)
+    rows = list(reversed(rows))
+    if not rows:
+        return {"ok": False, "msg": "该股票库内无日线，请先在数据中台入库该股或执行全市场回填", "symbol": symbol}
+    dates = [r.date.strftime("%y/%m/%d") for r in rows]
+    ohlc = [[r.open, r.close, r.low, r.high] for r in rows]
+    vols = [r.volume for r in rows]
+    close = [r.close for r in rows]
+    maf, mas = _ma_list(close, fast), _ma_list(close, slow)
+
+    signals = []
+    for i in range(1, len(close)):
+        if maf[i] is None or mas[i] is None or maf[i - 1] is None or mas[i - 1] is None:
+            continue
+        if maf[i - 1] <= mas[i - 1] and maf[i] > mas[i]:
+            signals.append({"idx": i, "date": dates[i], "price": close[i], "type": "buy"})
+        elif maf[i - 1] >= mas[i - 1] and maf[i] < mas[i]:
+            signals.append({"idx": i, "date": dates[i], "price": close[i], "type": "sell"})
+
+    # 区间统计
+    hi = max(r.high for r in rows); lo = min(r.low for r in rows)
+    period_ret = round((close[-1] / close[0] - 1) * 100, 2)
+    return {"ok": True, "symbol": symbol, "name": sec.name if sec else symbol,
+            "dates": dates, "ohlc": ohlc, "vols": vols,
+            "ma_fast": maf, "ma_slow": mas, "fast": fast, "slow": slow,
+            "signals": signals,
+            "stats": {"period_return": period_ret, "high": hi, "low": lo,
+                      "start": dates[0], "end": dates[-1], "bars": len(rows)}}
+
+
+# ============ AI 分析 ============
+@app.get("/api/ai/status")
+def ai_status():
+    return {"enabled": llm.enabled(), "model": config.LLM_MODEL if llm.enabled() else None}
+
+
+@app.get("/api/ai/review_daily")
+def ai_review_daily(date: str = Query(None)):
+    return ai.review_daily_comment(date)
+
+
+@app.get("/api/ai/diagnose")
+def ai_diagnose(symbol: str = Query("600519")):
+    return ai.diagnose(symbol)
+
+
+@app.get("/api/ai/today")
+def ai_today():
+    return ai.today_strategy()
+
+
+# ============ 可回溯：信号历史胜率 + 实测准确率 ============
+@app.get("/api/ai/signal_stats")
+def ai_signal_stats(horizon: int = Query(5, ge=1, le=20)):
+    return {"horizon": horizon, "stats": sig.get_stats(horizon)}
+
+
+@app.post("/api/ai/signal_stats/compute")
+def ai_signal_stats_compute(sample: int = Query(500, ge=50, le=4000), horizon: int = Query(5, ge=1, le=20)):
+    return scheduler.trigger_signal_stats_async(sample, horizon)
+
+
+@app.get("/api/ai/accuracy")
+def ai_accuracy():
+    return sig.accuracy()
+
+
+@app.post("/api/ai/accuracy/verify")
+def ai_accuracy_verify():
+    return sig.verify_predictions()
+
+
+# ============ AI 自动复盘日报 ============
+@app.get("/api/report/daily")
+def report_daily(date: str = Query(None)):
+    return rpt.get_by_date(date) if date else rpt.latest()
+
+
+@app.get("/api/report/history")
+def report_history(limit: int = Query(30, ge=1, le=120)):
+    return rpt.history(limit)
+
+
+@app.post("/api/report/generate")
+def report_generate(date: str = Query(None), push: bool = Query(False)):
+    return rpt.generate(date, push=push)
+
+
+# ============ 交易日志 & 组合 ============
+class TradeIn(BaseModel):
+    code: str
+    name: str = ""
+    side: str = "buy"
+    price: float
+    qty: int
+    fee: float = 0.0
+    date: str = ""
+    reason: str = ""
+    emotion: str = ""
+
+
+@app.get("/api/trades")
+def list_trades():
+    with get_session() as s:
+        rows = s.execute(select(Trade).order_by(Trade.date.desc(), Trade.id.desc())).scalars().all()
+        names = {}
+    return {"list": [{"id": t.id, "date": t.date.isoformat(), "code": t.code, "name": t.name,
+                      "side": t.side, "price": t.price, "qty": t.qty, "fee": t.fee,
+                      "reason": t.reason, "emotion": t.emotion} for t in rows]}
+
+
+@app.post("/api/trades")
+def add_trade(t: TradeIn):
+    d = dt.date.fromisoformat(t.date) if t.date else dt.date.today()
+    name = t.name
+    if not name:
+        with get_session() as s:
+            sec = s.get(Security, t.code)
+            name = sec.name if sec else t.code
+    with get_session() as s:
+        row = Trade(date=d, code=t.code, name=name, side=t.side, price=t.price,
+                    qty=t.qty, fee=t.fee, reason=t.reason, emotion=t.emotion)
+        s.add(row); s.commit()
+        return {"ok": True, "id": row.id}
+
+
+@app.delete("/api/trades/{tid}")
+def del_trade(tid: int):
+    with get_session() as s:
+        row = s.get(Trade, tid)
+        if row:
+            s.delete(row); s.commit()
+    return {"ok": True}
+
+
+@app.get("/api/portfolio")
+def get_portfolio():
+    return pf.compute()
+
+
+@app.get("/api/portfolio/equity")
+def portfolio_equity():
+    return pf.equity_curve()
+
+
+# ============ 推送通知 ============
+@app.get("/api/notify/status")
+def notify_status():
+    return {"channels": notifier.channels_status(), "enabled": notifier.any_enabled()}
+
+
+@app.post("/api/notify/test")
+def notify_test():
+    if not notifier.any_enabled():
+        return {"ok": False, "msg": "未配置任何推送渠道，请在 backend/.env 配置后重启"}
+    res = notifier.notify("【智策】推送测试", "这是一条来自智策股票终端的测试通知，收到即表示推送通道正常。")
+    return {"ok": True, "result": res}
+
+
+# ============ 智能预警 ============
+class AlertIn(BaseModel):
+    code: str
+    kind: str = "price_above"
+    threshold: float
+    note: str = ""
+
+
+@app.get("/api/alerts")
+def list_alerts():
+    with get_session() as s:
+        rows = s.execute(select(AlertRule).order_by(AlertRule.id.desc())).scalars().all()
+    return {"list": [{"id": r.id, "code": r.code, "name": r.name, "kind": r.kind,
+                      "threshold": r.threshold, "status": r.status, "note": r.note,
+                      "last_value": r.last_value,
+                      "triggered_at": r.triggered_at.strftime("%m-%d %H:%M") if r.triggered_at else ""}
+                     for r in rows]}
+
+
+@app.post("/api/alerts")
+def add_alert(a: AlertIn):
+    with get_session() as s:
+        sec = s.get(Security, a.code)
+        name = sec.name if sec else a.code
+        row = AlertRule(code=a.code, name=name, kind=a.kind, threshold=a.threshold, note=a.note)
+        s.add(row); s.commit()
+        return {"ok": True, "id": row.id}
+
+
+@app.delete("/api/alerts/{aid}")
+def del_alert(aid: int):
+    with get_session() as s:
+        row = s.get(AlertRule, aid)
+        if row:
+            s.delete(row); s.commit()
+    return {"ok": True}
+
+
+@app.post("/api/alerts/{aid}/reactivate")
+def reactivate_alert(aid: int):
+    with get_session() as s:
+        row = s.get(AlertRule, aid)
+        if row:
+            row.status = "active"; row.triggered_at = None; s.commit()
+    return {"ok": True}
+
+
+@app.post("/api/alerts/check")
+def manual_check():
+    return al.check_alerts()
+
+
+@app.get("/api/alerts/events")
+def alert_events(unread_only: bool = Query(False), limit: int = Query(30, le=100)):
+    with get_session() as s:
+        stmt = select(AlertEvent).order_by(AlertEvent.id.desc())
+        if unread_only:
+            stmt = stmt.where(AlertEvent.read.is_(False))
+        rows = s.execute(stmt.limit(limit)).scalars().all()
+        unread = s.execute(select(func.count()).select_from(AlertEvent).where(AlertEvent.read.is_(False))).scalar() or 0
+    return {"unread": unread, "list": [{"id": e.id, "code": e.code, "name": e.name,
+            "message": e.message, "time": e.created_at.strftime("%m-%d %H:%M:%S") if e.created_at else ""}
+            for e in rows]}
+
+
+@app.post("/api/alerts/events/read")
+def mark_events_read():
+    with get_session() as s:
+        for e in s.execute(select(AlertEvent).where(AlertEvent.read.is_(False))).scalars():
+            e.read = True
+        s.commit()
+    return {"ok": True}
+
+
+# ============ 资讯中心 ============
+@app.get("/api/news")
+def news(limit: int = Query(40, le=100)):
+    return svc.get_news(limit)
+
+
+@app.get("/api/news/stock")
+def news_stock(code: str = Query(...)):
+    return svc.get_stock_news(code)
+
+
+@app.get("/api/news/watch")
+def news_watch():
+    codes = load_watch()[:6]
+    out = []
+    for c in codes:
+        r = svc.get_stock_news(c, limit=4)
+        for x in r["list"]:
+            x["code"] = c
+            out.append(x)
+    out.sort(key=lambda x: x["time"], reverse=True)
+    return {"list": out[:40]}
+
+
+class NewsAI(BaseModel):
+    title: str
+    content: str = ""
+
+
+@app.post("/api/news/ai")
+def news_ai(n: NewsAI):
+    text_in = (n.title + "。" + n.content).strip()
+    senti, kw = svc.judge_sentiment(text_in)
+    if llm.enabled():
+        try:
+            prompt = ("请分析下面这条财经资讯：\n"
+                      "1) 一句话摘要；2) 利好/利空/中性判断及理由；3) 可能受影响的板块或个股方向。120字内。\n\n"
+                      + text_in[:1200])
+            text = llm.ask(prompt, temperature=0.3, max_tokens=400)
+            return {"ok": True, "source": "llm", "sentiment": senti, "text": text}
+        except Exception:
+            pass
+    return {"ok": True, "source": "rule", "sentiment": senti,
+            "text": f"判断：{senti}（关键词：{'、'.join(kw) or '无'}）。摘要：{text_in[:80]}…\n（配置大模型后可获得更深入的关联分析）"}
+
+
+# ============ 静态前端 ============
+FRONTEND_DIR = os.path.join(os.path.dirname(BASE_DIR), "prototype")
+if os.path.isdir(FRONTEND_DIR):
+    app.mount("/", StaticFiles(directory=FRONTEND_DIR, html=True), name="frontend")
+
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=False)