1154 lines
36 KiB
Python
1154 lines
36 KiB
Python
"""Blackdata股票终端 — FastAPI 后端入口。
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- /api/* : 数据接口（基于 AkShare，带缓存与降级）
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- / : 托管前端原型（prototype 目录）
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"""
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import os
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import json
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import datetime as dt
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from contextlib import asynccontextmanager
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from typing import List, Dict, Any, Optional
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from fastapi import FastAPI, Query
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.staticfiles import StaticFiles
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from sqlalchemy import select, func, desc
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from pydantic import BaseModel
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import akshare_service as svc
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import config
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import scheduler
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import backtest as bt
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import backtest_advanced as bta
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import ai
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import signals as sig
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import report as rpt
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import portfolio as pf
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import llm
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import alerts as al
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import notifier
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import intraday_radar as radar
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import sector_rotation as sector
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import smart_selector as selector
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import attribution_analysis as attrib
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import ai_chat
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import sentiment_monitor as sentiment
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import event_driven as events
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import financial_analysis as fin
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import limit_analysis as limit_up
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from db import init_db, get_session
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from models import (DailyQuote, IndexDaily, SectorDaily, FundFlowDaily,
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SentimentDaily, DragonTiger, Security, JobRun, StockMetric, Trade,
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AlertRule, AlertEvent, SelectorStrategy, SelectorAlert)
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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try:
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init_db()
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scheduler.start_scheduler()
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print("[startup] db + scheduler ready")
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except Exception as e:
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print("[startup] WARN:", repr(e)[:160])
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yield
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app = FastAPI(title="Blackdata股票终端 API", version="0.2.0", lifespan=lifespan)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# 自选股本地存储
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BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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WATCH_FILE = os.path.join(BASE_DIR, "watchlist.json")
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DEFAULT_WATCH = ["600519", "300750", "002594", "688981", "300059", "601012"]
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def load_watch():
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if os.path.exists(WATCH_FILE):
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try:
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with open(WATCH_FILE, "r", encoding="utf-8") as f:
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return json.load(f)
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except Exception:
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pass
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return DEFAULT_WATCH
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def save_watch(symbols):
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with open(WATCH_FILE, "w", encoding="utf-8") as f:
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json.dump(symbols, f, ensure_ascii=False)
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# ============ API ============
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@app.get("/api/health")
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def health():
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return {"ok": True, "akshare": svc.AK_OK}
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@app.get("/api/indices")
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def indices():
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return svc.get_indices()
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@app.get("/api/kline")
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def kline(symbol: str = Query("600519"), days: int = Query(120, ge=20, le=500)):
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return svc.get_kline(symbol, days)
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@app.get("/api/sentiment")
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def sentiment():
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return svc.get_sentiment()
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@app.get("/api/treemap")
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def treemap(mode: str = Query("sector")):
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return svc.get_treemap(mode)
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@app.get("/api/fundflow")
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def fundflow():
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return svc.get_fund_flow()
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@app.get("/api/hot/stocks")
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def hot_stocks():
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return svc.get_hot_stocks()
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@app.get("/api/hot/sectors")
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def hot_sectors():
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return svc.get_industry_boards()
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@app.get("/api/dragon")
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def dragon():
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return svc.get_dragon_tiger()
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@app.get("/api/watchlist")
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def watchlist():
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return svc.get_watchlist(load_watch())
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@app.post("/api/watchlist/{code}")
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def watch_add(code: str):
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w = load_watch()
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if code not in w:
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w.append(code)
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save_watch(w)
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return {"ok": True, "list": w}
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@app.delete("/api/watchlist/{code}")
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def watch_del(code: str):
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w = [c for c in load_watch() if c != code]
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save_watch(w)
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return {"ok": True, "list": w}
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# ============ 数据中台 ============
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@app.get("/api/admin/status")
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def admin_status():
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counts, last_dates = {}, {}
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with get_session() as s:
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for label, model in [("securities", Security), ("quotes_daily", DailyQuote),
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("index_daily", IndexDaily), ("sector_daily", SectorDaily),
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("fund_flow_daily", FundFlowDaily), ("sentiment_daily", SentimentDaily),
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("dragon_tiger", DragonTiger)]:
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counts[label] = s.execute(select(func.count()).select_from(model)).scalar() or 0
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if hasattr(model, "date"):
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d = s.execute(select(func.max(model.date))).scalar()
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last_dates[label] = d.isoformat() if d else None
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jobs = s.execute(select(JobRun).order_by(desc(JobRun.id)).limit(8)).scalars().all()
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job_list = [{"id": j.id, "job": j.job, "status": j.status,
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"started": j.started_at.strftime("%m-%d %H:%M:%S") if j.started_at else "",
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"finished": j.finished_at.strftime("%H:%M:%S") if j.finished_at else "",
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"message": j.message[:200]} for j in jobs]
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return {"counts": counts, "last_dates": last_dates, "jobs": job_list,
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"running": scheduler.is_running(), "universe": config.DEFAULT_UNIVERSE,
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"schedule": f"周一至周五 {config.INGEST_HOUR:02d}:{config.INGEST_MINUTE:02d}"}
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@app.post("/api/admin/ingest")
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def admin_ingest():
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if scheduler.is_running():
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return {"started": False, "msg": "已有入库任务在执行"}
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return scheduler.trigger_async()
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@app.post("/api/admin/ingest_all")
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def admin_ingest_all():
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return scheduler.trigger_all_async()
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@app.get("/api/db/kline")
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def db_kline(symbol: str = Query("600519"), days: int = Query(250, ge=20, le=1000)):
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with get_session() as s:
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rows = s.execute(
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select(DailyQuote).where(DailyQuote.code == symbol)
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.order_by(DailyQuote.date.desc()).limit(days)
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).scalars().all()
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rows = list(reversed(rows))
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if not rows:
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return {"source": "db", "empty": True, "symbol": symbol, "dates": [], "ohlc": [], "vols": []}
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return {"source": "db", "symbol": symbol,
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"dates": [r.date.strftime("%m/%d") for r in rows],
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"ohlc": [[r.open, r.close, r.low, r.high] for r in rows],
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"vols": [r.volume for r in rows]}
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@app.get("/api/db/sentiment_history")
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def db_sentiment_history(days: int = Query(60, ge=5, le=365)):
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with get_session() as s:
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rows = s.execute(select(SentimentDaily).order_by(SentimentDaily.date.desc()).limit(days)).scalars().all()
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rows = list(reversed(rows))
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return {"dates": [r.date.isoformat() for r in rows],
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"up": [r.up for r in rows], "down": [r.down for r in rows],
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"limit_up": [r.limit_up for r in rows]}
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@app.get("/api/review/daily")
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def review_daily(date: str = Query(None)):
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with get_session() as s:
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if date:
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d = dt.date.fromisoformat(date)
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else:
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d = s.execute(select(func.max(SectorDaily.date))).scalar()
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if not d:
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return {"ok": False, "msg": "暂无入库数据，请先在数据中台执行入库"}
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sectors = s.execute(select(SectorDaily).where(SectorDaily.date == d).order_by(SectorDaily.pct.desc())).scalars().all()
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flows = s.execute(select(FundFlowDaily).where(FundFlowDaily.date == d).order_by(FundFlowDaily.net.desc())).scalars().all()
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senti = s.execute(select(SentimentDaily).where(SentimentDaily.date == d)).scalar_one_or_none()
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lhb = s.execute(select(DragonTiger).where(DragonTiger.date == d).order_by(DragonTiger.net.desc()).limit(10)).scalars().all()
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top_sec = [{"name": x.name, "pct": x.pct} for x in sectors[:8]]
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bot_sec = [{"name": x.name, "pct": x.pct} for x in sectors[-5:]]
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inflow = [{"name": x.name, "net": x.net} for x in flows[:8]]
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outflow = [{"name": x.name, "net": x.net} for x in flows[-5:][::-1]]
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senti_d = ({"up": senti.up, "down": senti.down, "limit_up": senti.limit_up,
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"limit_down": senti.limit_down} if senti else None)
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summary = _gen_review_text(d, senti_d, top_sec, inflow)
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return {"ok": True, "date": d.isoformat(), "sentiment": senti_d,
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"top_sectors": top_sec, "weak_sectors": bot_sec,
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"inflow": inflow, "outflow": outflow,
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"dragon": [{"name": x.name, "code": x.code, "net": x.net, "pct": x.pct} for x in lhb],
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"summary": summary}
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def _gen_review_text(d, senti, top_sec, inflow):
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parts = [f"【{d.isoformat()} 复盘】"]
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if senti:
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tone = "情绪偏暖" if senti["up"] > senti["down"] else "情绪偏弱"
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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}。")
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if top_sec:
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names = "、".join(x["name"] for x in top_sec[:3])
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parts.append(f"领涨板块：{names}。")
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if inflow:
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names = "、".join(x["name"] for x in inflow[:3])
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parts.append(f"主力净流入居前：{names}。")
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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。")
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return " ".join(parts)
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@app.get("/api/backtest")
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def backtest_api(symbol: str = Query("600519"), fast: int = Query(5, ge=2, le=60),
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slow: int = Query(20, ge=5, le=250)):
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if fast >= slow:
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return {"ok": False, "msg": "快线周期需小于慢线周期"}
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return bt.run_backtest(symbol, fast, slow)
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# ============ 增强回测 ============
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class BacktestParams(BaseModel):
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symbol: str
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strategy: str = "ma" # ma, multi_factor
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fast: int = 5
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slow: int = 20
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position_size: float = 1.0
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stop_loss: float = 0.0
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take_profit: float = 0.0
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initial_capital: float = 100000.0
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commission: float = 0.0005
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@app.post("/api/backtest/advanced")
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def backtest_advanced(params: BacktestParams):
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"""增强回测"""
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if params.strategy == "ma":
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strategy = bta.MAStrategy(
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fast=params.fast,
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slow=params.slow,
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position_size=params.position_size,
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stop_loss=params.stop_loss,
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take_profit=params.take_profit
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)
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elif params.strategy == "multi_factor":
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strategy = bta.MultiFactorStrategy(position_size=params.position_size)
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else:
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return {"ok": False, "msg": "不支持的策略类型"}
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return bta.run_advanced_backtest(
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symbol=params.symbol,
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strategy=strategy,
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initial_capital=params.initial_capital,
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commission=params.commission
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)
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class OptimizeParams(BaseModel):
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symbol: str
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strategy: str = "ma"
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fast_range: List[int] = [3, 5, 10, 15]
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slow_range: List[int] = [20, 30, 60]
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metric: str = "sharpe_ratio"
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@app.post("/api/backtest/optimize")
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def backtest_optimize(params: OptimizeParams):
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"""参数优化"""
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param_grid = {
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"fast": params.fast_range,
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"slow": params.slow_range
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}
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results = bta.optimize_parameters(
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symbol=params.symbol,
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param_grid=param_grid,
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strategy_class=bta.MAStrategy,
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metric=params.metric
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)
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return {
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"ok": True,
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"symbol": params.symbol,
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"metric": params.metric,
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"results": results[:20] # 返回前20个最优结果
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}
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class CompareParams(BaseModel):
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symbol: str
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strategies: List[Dict[str, Any]]
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@app.post("/api/backtest/compare")
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||
def backtest_compare(params: CompareParams):
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"""策略对比"""
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strategies = []
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||
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for s in params.strategies:
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if s["type"] == "ma":
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strategies.append(bta.MAStrategy(
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fast=s.get("fast", 5),
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slow=s.get("slow", 20),
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stop_loss=s.get("stop_loss", 0),
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take_profit=s.get("take_profit", 0)
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))
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elif s["type"] == "multi_factor":
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strategies.append(bta.MultiFactorStrategy())
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||
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return bta.compare_strategies(params.symbol, strategies)
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||
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||
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# ============ 全市场选股 ============
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STRATEGIES = {
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"surge": "最近暴涨（5日涨幅≥20%）",
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"plunge": "最近暴跌（5日跌幅≥15%）",
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"dip": "超跌抄底（60日分位≤20%且当日企稳）",
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"breakout": "突破走强（逼近60日新高）",
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"ma_bull": "均线多头（MA5>10>20）",
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"volume": "放量上攻（量比≥2且上涨）",
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"macd_gold": "MACD金叉",
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"strong": "强势连涨（≥3日连阳）",
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}
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|
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@app.get("/api/screen/strategies")
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||
def screen_strategies():
|
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return {"list": [{"id": k, "name": v} for k, v in STRATEGIES.items()]}
|
||
|
||
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||
@app.get("/api/screen")
|
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def screen(strategy: str = Query("surge"), limit: int = Query(60, ge=10, le=300),
|
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min_amount: float = Query(0.0)):
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||
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()
|
||
|
||
|
||
@app.get("/api/portfolio/attribution")
|
||
def portfolio_attribution():
|
||
"""持仓归因分析"""
|
||
return attrib.analyze_attribution()
|
||
|
||
|
||
# ============ AI 对话式分析 ============
|
||
class ChatRequest(BaseModel):
|
||
session_id: str
|
||
message: str
|
||
|
||
|
||
@app.post("/api/chat")
|
||
def chat(req: ChatRequest):
|
||
"""AI对话"""
|
||
return ai_chat.chat(req.session_id, req.message)
|
||
|
||
|
||
@app.delete("/api/chat/{session_id}")
|
||
def clear_chat(session_id: str):
|
||
"""清空会话"""
|
||
ai_chat.clear_session(session_id)
|
||
return {"ok": True}
|
||
|
||
|
||
@app.get("/api/chat/{session_id}/history")
|
||
def chat_history(session_id: str):
|
||
"""获取会话历史"""
|
||
return {"ok": True, "messages": ai_chat.get_session_history(session_id)}
|
||
|
||
|
||
# ============ 社区情绪监控 ============
|
||
@app.post("/api/sentiment/collect")
|
||
def sentiment_collect(limit: int = Query(50, ge=10, le=200)):
|
||
"""采集社区帖子"""
|
||
return sentiment.collect_posts(limit)
|
||
|
||
|
||
@app.get("/api/sentiment/index")
|
||
def sentiment_index(date: Optional[str] = None):
|
||
"""获取情绪指数"""
|
||
d = dt.date.fromisoformat(date) if date else None
|
||
return sentiment.calculate_sentiment_index(d)
|
||
|
||
|
||
@app.get("/api/sentiment/hot_stocks")
|
||
def sentiment_hot_stocks(days: int = Query(1, ge=1, le=7), limit: int = Query(20, le=50)):
|
||
"""热议股票排行"""
|
||
return sentiment.get_hot_stocks(days, limit)
|
||
|
||
|
||
@app.get("/api/sentiment/history")
|
||
def sentiment_history(days: int = Query(30, ge=7, le=90)):
|
||
"""情绪指数历史"""
|
||
return sentiment.get_sentiment_history(days)
|
||
|
||
|
||
@app.get("/api/sentiment/correlation")
|
||
def sentiment_correlation(code: str = Query(...), days: int = Query(60, ge=20, le=180)):
|
||
"""情绪与股价相关性"""
|
||
return sentiment.analyze_sentiment_correlation(code, days)
|
||
|
||
|
||
@app.get("/api/sentiment/wordcloud")
|
||
def sentiment_wordcloud(days: int = Query(7, ge=1, le=30), top_n: int = Query(50, le=100)):
|
||
"""关键词云"""
|
||
return sentiment.get_keyword_cloud(days, top_n)
|
||
|
||
|
||
# ============ 事件驱动策略 ============
|
||
@app.post("/api/events/seed")
|
||
def events_seed():
|
||
"""生成示例事件数据"""
|
||
return events.seed_sample_events()
|
||
|
||
|
||
@app.get("/api/events/earnings/pattern")
|
||
def earnings_pattern(days_before: int = Query(5, ge=1, le=10), days_after: int = Query(10, ge=5, le=30)):
|
||
"""财报发布前后统计规律"""
|
||
return events.analyze_earnings_pattern(days_before, days_after)
|
||
|
||
|
||
@app.get("/api/events/insider")
|
||
def insider_trading(code: Optional[str] = None, days: int = Query(180, ge=30, le=365)):
|
||
"""高管增减持跟踪"""
|
||
return events.track_insider_trading(code, days)
|
||
|
||
|
||
@app.get("/api/events/unlock")
|
||
def unlock_impact(days: int = Query(90, ge=30, le=180)):
|
||
"""限售解禁影响分析"""
|
||
return events.analyze_unlock_impact(days)
|
||
|
||
|
||
@app.get("/api/events/policy")
|
||
def policy_events(sector: Optional[str] = None, days: int = Query(180, ge=30, le=365)):
|
||
"""行业政策事件"""
|
||
return events.get_policy_events(sector, days)
|
||
|
||
|
||
class EventSelectorRequest(BaseModel):
|
||
event_types: List[str]
|
||
days: int = 30
|
||
|
||
|
||
@app.post("/api/events/selector")
|
||
def event_selector(req: EventSelectorRequest):
|
||
"""事件驱动选股"""
|
||
return events.event_driven_selector(req.event_types, req.days)
|
||
|
||
|
||
# ============ 财报深度解读 ============
|
||
@app.post("/api/financial/seed")
|
||
def financial_seed():
|
||
"""生成示例财报数据"""
|
||
return fin.seed_sample_reports()
|
||
|
||
|
||
@app.get("/api/financial/trend")
|
||
def financial_trend(code: str = Query(...), periods: int = Query(8, ge=4, le=16)):
|
||
"""财报关键指标趋势"""
|
||
return fin.get_report_trend(code, periods)
|
||
|
||
|
||
@app.get("/api/financial/summary")
|
||
def financial_summary(code: str = Query(...)):
|
||
"""AI财报摘要"""
|
||
return fin.generate_ai_summary(code)
|
||
|
||
|
||
@app.get("/api/financial/compare")
|
||
def financial_compare(code: str = Query(...), sector: Optional[str] = None):
|
||
"""同行对比"""
|
||
return fin.compare_with_peers(code, sector)
|
||
|
||
|
||
@app.get("/api/financial/warnings")
|
||
def financial_warnings(code: str = Query(...)):
|
||
"""财报异常预警"""
|
||
return fin.detect_abnormalities(code)
|
||
|
||
|
||
@app.get("/api/financial/calendar")
|
||
def financial_calendar(days: int = Query(30, ge=7, le=90)):
|
||
"""财报发布日历"""
|
||
return fin.get_report_calendar(days)
|
||
|
||
|
||
@app.get("/api/financial/rankings")
|
||
def financial_rankings(metric: str = Query("roe"), limit: int = Query(20, le=50)):
|
||
"""财报排行榜"""
|
||
return fin.get_top_reports(metric, limit)
|
||
|
||
|
||
# ============ 涨跌停分析 ============
|
||
@app.get("/api/limit/stocks")
|
||
def limit_stocks(date: Optional[str] = None, limit_type: str = Query("up")):
|
||
"""获取涨停/跌停股票"""
|
||
d = dt.date.fromisoformat(date) if date else None
|
||
return limit_up.get_limit_stocks(d, limit_type)
|
||
|
||
|
||
@app.get("/api/limit/consecutive")
|
||
def consecutive_limits(days: int = Query(10, ge=5, le=30)):
|
||
"""连板股追踪"""
|
||
return limit_up.track_consecutive_limits(days)
|
||
|
||
|
||
@app.get("/api/limit/break_rate")
|
||
def limit_break_rate(days: int = Query(60, ge=30, le=180)):
|
||
"""炸板率统计"""
|
||
return limit_up.analyze_limit_break_rate(days)
|
||
|
||
|
||
@app.get("/api/limit/squad")
|
||
def limit_squad(days: int = Query(30, ge=10, le=90), min_limits: int = Query(5, ge=3, le=10)):
|
||
"""涨停敢死队排行"""
|
||
return limit_up.get_limit_squad_rankings(days, min_limits)
|
||
|
||
|
||
# ============ 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("【Blackdata】推送测试", "这是一条来自Blackdata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）"}
|
||
|
||
|
||
# ============ 盘中实时监控雷达 ============
|
||
@app.get("/api/radar/status")
|
||
def radar_status():
|
||
"""雷达状态。"""
|
||
return {"trading_time": radar._is_trading_time()}
|
||
|
||
|
||
@app.post("/api/radar/scan")
|
||
def radar_scan():
|
||
"""手动触发异动扫描。"""
|
||
return radar.scan_all()
|
||
|
||
|
||
@app.get("/api/radar/events")
|
||
def radar_events(hours: int = Query(2, ge=1, le=24), limit: int = Query(50, le=200)):
|
||
"""获取最近的异动事件。"""
|
||
return {"list": radar.get_recent_events(hours, limit)}
|
||
|
||
|
||
@app.post("/api/radar/notify")
|
||
def radar_notify():
|
||
"""推送未通知的异动。"""
|
||
return radar.notify_events()
|
||
|
||
|
||
@app.get("/api/radar/stats")
|
||
def radar_stats(date: str = Query(None)):
|
||
"""异动统计。"""
|
||
d = dt.date.fromisoformat(date) if date else None
|
||
return radar.get_statistics(d)
|
||
|
||
|
||
# ============ 板块轮动分析 ============
|
||
@app.get("/api/sector/trend")
|
||
def sector_trend(days: int = Query(20, ge=5, le=60), top_n: int = Query(15, le=30)):
|
||
"""板块强弱趋势"""
|
||
return sector.get_sector_trend(days, top_n)
|
||
|
||
|
||
@app.get("/api/sector/flow")
|
||
def sector_flow(days: int = Query(5, ge=1, le=20)):
|
||
"""资金流向分析"""
|
||
return sector.analyze_fund_flow(days)
|
||
|
||
|
||
@app.get("/api/sector/lifecycle")
|
||
def sector_lifecycle(name: str = Query(...), days: int = Query(60, ge=20, le=120)):
|
||
"""板块生命周期"""
|
||
return sector.analyze_lifecycle(name, days)
|
||
|
||
|
||
@app.get("/api/sector/leaders")
|
||
def sector_leaders(name: str = Query(...), days: int = Query(20, ge=5, le=60), limit: int = Query(10, le=30)):
|
||
"""龙头股识别"""
|
||
return sector.identify_leaders(name, days, limit)
|
||
|
||
|
||
@app.get("/api/sector/correlation")
|
||
def sector_correlation(days: int = Query(60, ge=20, le=120), top_n: int = Query(20, le=30)):
|
||
"""板块联动性分析"""
|
||
return sector.analyze_correlation(days, top_n)
|
||
|
||
|
||
@app.get("/api/sector/summary")
|
||
def sector_summary():
|
||
"""板块轮动摘要"""
|
||
return sector.get_rotation_summary()
|
||
|
||
|
||
# ============ 智能选股增强 ============
|
||
@app.get("/api/selector/fields")
|
||
def selector_fields():
|
||
"""获取可用字段"""
|
||
return {"ok": True, "fields": selector.get_available_fields()}
|
||
|
||
|
||
@app.get("/api/selector/presets")
|
||
def selector_presets():
|
||
"""获取预设策略"""
|
||
return {"ok": True, "presets": selector.get_preset_strategies()}
|
||
|
||
|
||
class SelectorRequest(BaseModel):
|
||
strategy: Dict[str, Any]
|
||
date: Optional[str] = None
|
||
|
||
|
||
@app.post("/api/selector/run")
|
||
def selector_run(req: SelectorRequest):
|
||
"""执行选股"""
|
||
try:
|
||
strategy = selector.Strategy.from_dict(req.strategy)
|
||
date = dt.date.fromisoformat(req.date) if req.date else None
|
||
return selector.run_selector(strategy, date)
|
||
except Exception as e:
|
||
return {"ok": False, "msg": str(e)}
|
||
|
||
|
||
@app.post("/api/selector/backtest")
|
||
def selector_backtest(req: SelectorRequest, days: int = Query(60, ge=20, le=250)):
|
||
"""选股策略回测"""
|
||
try:
|
||
strategy = selector.Strategy.from_dict(req.strategy)
|
||
return selector.backtest_selector(strategy, days)
|
||
except Exception as e:
|
||
return {"ok": False, "msg": str(e)}
|
||
|
||
|
||
class CompareRequest(BaseModel):
|
||
strategy: Dict[str, Any]
|
||
date1: str
|
||
date2: str
|
||
|
||
|
||
@app.post("/api/selector/compare")
|
||
def selector_compare(req: CompareRequest):
|
||
"""对比选股结果"""
|
||
try:
|
||
strategy = selector.Strategy.from_dict(req.strategy)
|
||
date1 = dt.date.fromisoformat(req.date1)
|
||
date2 = dt.date.fromisoformat(req.date2)
|
||
return selector.compare_results(date1, date2, strategy)
|
||
except Exception as e:
|
||
return {"ok": False, "msg": str(e)}
|
||
|
||
|
||
@app.get("/api/selector/strategies")
|
||
def list_strategies():
|
||
"""获取保存的策略列表"""
|
||
with get_session() as s:
|
||
rows = s.execute(
|
||
select(SelectorStrategy).order_by(SelectorStrategy.updated_at.desc())
|
||
).scalars().all()
|
||
return {
|
||
"ok": True,
|
||
"strategies": [{
|
||
"id": r.id,
|
||
"name": r.name,
|
||
"description": r.description,
|
||
"is_preset": r.is_preset,
|
||
"created_at": r.created_at.strftime("%Y-%m-%d %H:%M:%S"),
|
||
"updated_at": r.updated_at.strftime("%Y-%m-%d %H:%M:%S")
|
||
} for r in rows]
|
||
}
|
||
|
||
|
||
class SaveStrategyRequest(BaseModel):
|
||
name: str
|
||
description: str = ""
|
||
strategy: Dict[str, Any]
|
||
|
||
|
||
@app.post("/api/selector/strategies")
|
||
def save_strategy(req: SaveStrategyRequest):
|
||
"""保存策略"""
|
||
try:
|
||
strategy = selector.Strategy.from_dict(req.strategy)
|
||
with get_session() as s:
|
||
record = SelectorStrategy(
|
||
name=req.name,
|
||
description=req.description,
|
||
strategy_json=strategy.to_json()
|
||
)
|
||
s.add(record)
|
||
s.commit()
|
||
return {"ok": True, "id": record.id}
|
||
except Exception as e:
|
||
return {"ok": False, "msg": str(e)}
|
||
|
||
|
||
@app.get("/api/selector/strategies/{sid}")
|
||
def get_strategy(sid: int):
|
||
"""获取策略详情"""
|
||
with get_session() as s:
|
||
record = s.get(SelectorStrategy, sid)
|
||
if not record:
|
||
return {"ok": False, "msg": "策略不存在"}
|
||
return {
|
||
"ok": True,
|
||
"id": record.id,
|
||
"name": record.name,
|
||
"description": record.description,
|
||
"strategy": json.loads(record.strategy_json)
|
||
}
|
||
|
||
|
||
@app.delete("/api/selector/strategies/{sid}")
|
||
def delete_strategy(sid: int):
|
||
"""删除策略"""
|
||
with get_session() as s:
|
||
record = s.get(SelectorStrategy, sid)
|
||
if record:
|
||
s.delete(record)
|
||
s.commit()
|
||
return {"ok": True}
|
||
|
||
|
||
@app.get("/api/selector/alerts")
|
||
def list_selector_alerts():
|
||
"""获取选股预警列表"""
|
||
with get_session() as s:
|
||
rows = s.execute(
|
||
select(SelectorAlert).order_by(SelectorAlert.id.desc())
|
||
).scalars().all()
|
||
return {
|
||
"ok": True,
|
||
"alerts": [{
|
||
"id": r.id,
|
||
"strategy_id": r.strategy_id,
|
||
"strategy_name": r.strategy_name,
|
||
"status": r.status,
|
||
"last_checked": r.last_checked.strftime("%m-%d %H:%M") if r.last_checked else "",
|
||
"last_count": r.last_count
|
||
} for r in rows]
|
||
}
|
||
|
||
|
||
class CreateAlertRequest(BaseModel):
|
||
strategy_id: int
|
||
strategy_name: str
|
||
|
||
|
||
@app.post("/api/selector/alerts")
|
||
def create_selector_alert(req: CreateAlertRequest):
|
||
"""创建选股预警"""
|
||
with get_session() as s:
|
||
record = SelectorAlert(
|
||
strategy_id=req.strategy_id,
|
||
strategy_name=req.strategy_name
|
||
)
|
||
s.add(record)
|
||
s.commit()
|
||
return {"ok": True, "id": record.id}
|
||
|
||
|
||
@app.delete("/api/selector/alerts/{aid}")
|
||
def delete_selector_alert(aid: int):
|
||
"""删除选股预警"""
|
||
with get_session() as s:
|
||
record = s.get(SelectorAlert, aid)
|
||
if record:
|
||
s.delete(record)
|
||
s.commit()
|
||
return {"ok": True}
|
||
|
||
|
||
# ============ 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)
|