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30
backend/app/api/__init__.py
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30
backend/app/api/__init__.py
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"""HTTP 路由（OpenAPI 契约的载体）——按域拆分：
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stocks.py /api/stocks*（列表/筛选项/公司/财务/分红/参考数据）+ /api/data/sync
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etfs.py /api/etfs + /api/etf/sync*
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market.py /api/market/*（总览/打板/概念板块/指数 K 线与详情）
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backtest.py /api/backtest + /api/backtest/event
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screener.py /api/screener/*（选股/历史/同步/个股预览）
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user.py /api/preferences + /api/watchlist* + /api/trades*
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_deps.py 共享件：JSON 直返缓存、复权换算、行转 Bar、共享常量与 SQL
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统一约定：prefix=/api 与 require_user 鉴权在本层挂一次，子路由不带前缀；
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路由注册顺序 = include 顺序（各域路径前缀互不重叠，顺序不影响匹配）。
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"""
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from fastapi import APIRouter, Depends
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from ..auth import require_user
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from .backtest import router as backtest_router
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from .etfs import router as etfs_router
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from .market import router as market_router
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from .screener import router as screener_router
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from .stocks import router as stocks_router
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from .user import router as user_router
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router = APIRouter(prefix="/api", dependencies=[Depends(require_user)])
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router.include_router(stocks_router)
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router.include_router(etfs_router)
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router.include_router(market_router)
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router.include_router(backtest_router)
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router.include_router(screener_router)
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router.include_router(user_router)
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145
backend/app/api/_deps.py
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145
backend/app/api/_deps.py
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"""路由包共享件：JSON 直返缓存、复权换算、行转 Bar、共享常量与 SQL。
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各域路由模块（stocks/etfs/market/backtest/screener/user）从这里取公共工具，
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域内私有工具留在各自文件里。
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"""
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from __future__ import annotations
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import bisect
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import pandas as pd
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from fastapi import Response
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from sqlalchemy import text
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from .. import cache
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from ..domain import Bar
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# 复权模式白名单
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ADJUST_MODES = ("bfq", "qfq", "hfq")
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# MA 全量集合（前端已改为本地计算 MA，后端始终返回此集合以保证缓存一致）
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FULL_MA_SET = (5, 10, 20, 30, 60, 120, 250)
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# 指数 K 线支持的周期（日线基底聚合）
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INDEX_TIMEFRAMES = ("1d", "1w", "1M", "1y")
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def raw_json(resp) -> str:
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"""pydantic-core（Rust）序列化：与 response_model 直返时的字节完全一致（紧凑分隔符、
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非 ASCII 直出、浮点小数形式），且比 stdlib json.dumps 快。大响应（preview ~250KB）
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命中缓存时直接 Response 原样返回，跳过校验/再序列化。"""
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return resp.model_dump_json()
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async def cached_json_response(key: str) -> Response | None:
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"""两级缓存读（进程内 → Redis）：命中返回可直接吐给客户端的 Response。
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存的均为序列化好的 JSON 字符串（Redis 侧 json.loads 后仍是 str），Redis 命中顺手晋级本地。"""
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raw = cache.local_get(key)
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if raw is None:
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raw = await cache.cache_get(key)
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if not isinstance(raw, str):
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return None
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cache.local_set(key, raw, ttl=120)
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return Response(content=raw, media_type="application/json")
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def series_to_jsonable(s: pd.Series) -> list[float | None]:
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"""NaN -> None（lightweight-charts 的 whitespace data，跳过指标预热期）。"""
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out: list[float | None] = []
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for v in s.tolist():
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if v is None or (isinstance(v, float) and v != v):
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out.append(None)
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else:
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out.append(float(v))
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return out
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def rows_to_bars(rows) -> list[Bar]:
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return [
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Bar(
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ts=r.ts, open=r.open, high=r.high, low=r.low, close=r.close, volume=r.volume,
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amount=getattr(r, "amount", None), turnover=getattr(r, "turnover", None),
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)
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for r in rows
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]
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# 信息卡一条 SQL 拿全：stock_basic 基本信息 + 「优先与行情同日、缺则最新日」的 daily_snapshot
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# （LATERAL 单条替换原两条查询，语义不变：target 为 NULL 时全按最新日兜底）。
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# ETF 走 etf_basic 分支（代码前缀与股票不重叠，两分支至多一个命中）：
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# 名称/上市日来自表内，市值（元）换算成万元与快照口径一致，无 PE/PB。
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INFO_SQL = text(
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"""
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SELECT ts_code, symbol, name, industry, area, market, list_date,
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turnover_rate, pe_ttm, pb, total_mv, circ_mv
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FROM (
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SELECT sb.ts_code, sb.symbol, sb.name, sb.industry, sb.area, sb.market, sb.list_date,
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ds.turnover_rate, ds.pe_ttm, ds.pb, ds.total_mv, ds.circ_mv
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FROM stock_basic sb
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LEFT JOIN LATERAL (
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SELECT turnover_rate, pe_ttm, pb, total_mv, circ_mv
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FROM daily_snapshot
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WHERE ts_code = sb.ts_code
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ORDER BY (trade_date = cast(:target AS timestamp)) DESC, trade_date DESC
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LIMIT 1
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) ds ON true
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WHERE sb.ts_code = :code
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UNION ALL
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SELECT eb.ts_code, eb.symbol, eb.name, NULL, NULL,
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CASE eb.exchange WHEN 'SH' THEN '沪市' ELSE '深市' END, eb.list_date,
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eb.turnover_rate, NULL, NULL,
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eb.total_mv / 10000.0, eb.circ_mv / 10000.0
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FROM etf_basic eb
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WHERE eb.ts_code = :code
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) t
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LIMIT 1
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"""
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)
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# 复权因子是阶梯函数（除权日之间不变）：只取「变化点」行，把每符号 ~7000 行日级因子压到
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# 几十行（600118 仅 32 行），传输量再降两个数量级；lag 窗口在覆盖索引上走 Index Only Scan。
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# upto 传全局最新交易日（非分页）或 end 日期（分页）；窗口首行 prev 为 NULL 恒被保留（窗口基线因子）。
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FACTOR_STEP_SQL = text(
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"""
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SELECT trade_date, adj_factor FROM (
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SELECT trade_date, adj_factor,
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lag(adj_factor) OVER (ORDER BY trade_date) AS prev
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FROM adj_factor
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WHERE ts_code = :code AND trade_date <= :upto
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) t
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WHERE adj_factor IS DISTINCT FROM prev
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ORDER BY trade_date
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"""
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)
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def adjust_bars(bars: list[Bar], factors, from_mode: str, to_mode: str) -> list[Bar]:
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"""按复权因子把 K 线从 from_mode 换算到 to_mode（bfq/qfq/hfq）。
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相对不复权的乘数：bfq=1，qfq=f(t)/f(latest)，hfq=f(t)。
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因子缺失的日期向前沿用最近因子（因子是阶梯函数，除权日之间不变）。
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"""
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fd = sorted((f[0].date(), float(f[1])) for f in factors)
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fdates = [d for d, _ in fd]
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f_latest = fd[-1][1]
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def _f_at(d) -> float:
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i = bisect.bisect_right(fdates, d) - 1
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return fd[i][1] if i >= 0 else fd[0][1]
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def _mult(mode: str, f: float) -> float:
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if mode == "bfq":
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return 1.0
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return f / f_latest if mode == "qfq" else f
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out: list[Bar] = []
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for b in bars:
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f = _f_at(b.ts.date())
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m = _mult(to_mode, f) / _mult(from_mode, f)
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out.append(Bar(
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ts=b.ts,
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open=round(b.open * m, 3), high=round(b.high * m, 3),
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low=round(b.low * m, 3), close=round(b.close * m, 3),
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volume=b.volume,
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# 成交额/换手率是名义量，不随复权缩放
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amount=b.amount, turnover=b.turnover,
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))
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return out
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152
backend/app/api/backtest.py
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152
backend/app/api/backtest.py
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"""回测域路由：策略回测（旧 API，K线+指标+买卖点+净值）+ 自然语言事件回测。"""
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from __future__ import annotations
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import json
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import pandas as pd
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from fastapi import APIRouter, Depends, HTTPException
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from sqlalchemy.ext.asyncio import AsyncSession
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from ..backtest.engine import BacktestConfig, run_backtest
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from ..backtest.events import EventEngineError, run_event_backtest
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from ..backtest.strategies import build_strategy
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from ..data import fetcher, repository
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from ..data.aggregation import bars_per_year, resample_bars
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from ..data.symbols import is_etf_symbol
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from ..db import get_session
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from ..models import BacktestRun
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from ..schemas import (
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BacktestRequest,
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BacktestResponse,
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CandleOut,
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EquityPoint,
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EventBacktestRequest,
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EventBacktestResponse,
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IndicatorOut,
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MetricsOut,
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SignalOut,
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)
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from ..screener.llm import parse_event_spec, ScreenerError
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from ._deps import rows_to_bars, series_to_jsonable
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router = APIRouter()
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@router.post("/backtest", response_model=BacktestResponse)
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async def backtest(
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req: BacktestRequest,
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session: AsyncSession = Depends(get_session),
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) -> BacktestResponse:
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# 真实数据：本地无缓存则先拉取
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if not await fetcher.is_cached(session, req.symbol):
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try:
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await fetcher.sync_symbol(session, req.symbol, source="auto")
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except Exception as e: # noqa: BLE001
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raise HTTPException(status_code=502, detail=f"数据拉取失败: {e}")
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# 日线为基底，聚合到请求周期
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rows = await repository.get_candles(
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session, req.symbol, "1d", start=req.start, end=req.end, limit=100000
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)
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if not rows:
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raise HTTPException(status_code=404, detail=f"无数据: symbol={req.symbol}")
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bars = resample_bars(rows_to_bars(rows), req.timeframe)
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if len(bars) < 2:
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raise HTTPException(status_code=400, detail=f"周期 {req.timeframe} 下数据不足，无法回测")
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try:
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strategy = build_strategy(req.strategy, req.params)
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except Exception as e: # noqa: BLE001
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raise HTTPException(status_code=400, detail=f"策略构建失败: {e}")
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cfg = BacktestConfig(
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initial_cash=req.initial_cash,
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fast_mode=req.fast_mode,
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bars_per_year=bars_per_year(req.timeframe),
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is_fund=is_etf_symbol(req.symbol), # ETF 免印花税/过户费
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)
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result = run_backtest(bars, strategy, cfg)
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df: pd.DataFrame = result["df"]
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m = result["metrics"]
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# 记录到回测运行注册表（可复现/可审计的基础）
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session.add(
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BacktestRun(
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symbol=req.symbol,
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strategy=req.strategy,
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timeframe=req.timeframe,
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params_json=json.dumps(req.params, ensure_ascii=False),
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initial_cash=req.initial_cash,
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total_return=m["total_return"],
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max_drawdown=m["max_drawdown"],
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sharpe=m["sharpe"],
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num_trades=m["num_trades"],
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)
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)
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await session.commit()
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candles = [
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CandleOut(ts=r["ts"], open=r["open"], high=r["high"], low=r["low"],
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close=r["close"], volume=r["volume"],
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amount=r["amount"] if "amount" in df.columns else None,
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turnover=r["turnover"] if "turnover" in df.columns else None)
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for _, r in df.iterrows()
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]
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signals = [
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SignalOut(ts=f.ts, side=f.side.value, price=f.price, qty=f.qty)
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for f in result["fills"]
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]
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indicators = IndicatorOut(
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strategy=req.strategy,
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data={col: series_to_jsonable(df[col]) for col in result["indicator_cols"]},
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)
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equity = [EquityPoint(ts=t.to_pydatetime(), value=float(v))
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for t, v in result["equity"].items()]
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return BacktestResponse(
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symbol=req.symbol,
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timeframe=req.timeframe,
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strategy=req.strategy,
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candles=candles,
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indicators=indicators,
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signals=signals,
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equity=equity,
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metrics=MetricsOut(**m),
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final_cash=result["final_cash"],
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final_position=result["final_position"],
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initial_cash=req.initial_cash,
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)
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@router.post("/backtest/event", response_model=EventBacktestResponse)
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async def backtest_event(
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req: EventBacktestRequest,
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session: AsyncSession = Depends(get_session),
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) -> EventBacktestResponse:
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"""自然语言事件回测：入场条件命中 -> 次日买入 -> 持有 N 日，单股或全市场汇总统计。
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直传 spec 则跳过 LLM（前端调参重跑）。"""
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try:
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spec = req.spec or await parse_event_spec(req.text)
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result = await run_event_backtest(
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session, spec,
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ts_code=req.ts_code,
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start=req.start.date() if req.start else None,
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end=req.end.date() if req.end else None,
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)
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except ScreenerError as e:
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raise HTTPException(status_code=502, detail=str(e))
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except EventEngineError as e:
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raise HTTPException(status_code=400, detail=str(e))
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except Exception as e: # noqa: BLE001
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raise HTTPException(status_code=500, detail=f"事件回测失败: {e}")
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return EventBacktestResponse(
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text=req.text,
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spec=result["spec"],
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universe=result["universe"],
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start=result["start"],
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end=result["end"],
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stats=result["stats"],
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trades=result["trades"],
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total=result["total"],
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)
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133
backend/app/api/etfs.py
Normal file
133
backend/app/api/etfs.py
Normal file
@@ -0,0 +1,133 @@
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"""ETF 域路由：全市场列表（东财快照 + candles 行情）+ 同步任务。"""
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from __future__ import annotations
|
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|
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from fastapi import APIRouter, Depends, HTTPException, Response
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from sqlalchemy import text
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy.sql.elements import TextClause
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from .. import cache
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from ..auth import require_user
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from ..config import settings
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from ..data import etf_sync as etf_sync_mod
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from ..db import get_session
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from ..schemas import EtfListItemOut, EtfListResponse, EtfSyncRequest, EtfSyncStatus
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from ._deps import cached_json_response, raw_json
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router = APIRouter()
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# ---------- ETF 列表（全市场浏览；行情走 candles 底座，规模/换手走东财快照） ----------
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# 与 /stocks 不同：成交额来自 candles 最新 bar（LATERAL），必须在分页前 join 才能参与
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# 排序 —— ETF 全市场仅 ~1100 行，3 个索引探测/行 也就几 ms，可以承受。
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# 排序列白名单（键→表达式）；order_by 由白名单拼接进模板，不接收用户原文。
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_ETFS_SORTS = {
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"symbol": "eb.symbol",
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"close": "c.close",
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"pct_chg": "pct_chg",
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"amount": "c.amount",
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"total_mv": "eb.total_mv",
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"circ_mv": "eb.circ_mv",
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"turnover_rate": "eb.turnover_rate",
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}
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_ETFS_SQL_TMPL = """
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SELECT eb.ts_code, eb.symbol, eb.name, eb.exchange, eb.list_date,
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(w.id IS NOT NULL) AS watched,
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eb.turnover_rate,
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round((eb.total_mv / 100000000.0)::numeric, 2) AS total_mv,
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round((eb.circ_mv / 100000000.0)::numeric, 2) AS circ_mv,
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c.close AS close, prev.close AS prev_close, c.ts AS last_ts,
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CASE WHEN c.close IS NOT NULL AND prev.close IS NOT NULL AND prev.close <> 0
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THEN round(((c.close / prev.close - 1) * 100)::numeric, 2) END AS pct_chg,
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round((c.amount / 100000000.0)::numeric, 2) AS amount
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FROM etf_basic eb
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LEFT JOIN watchlist_items w ON w.ts_code = eb.ts_code AND w.user_id = :uid
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LEFT JOIN LATERAL (
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SELECT close, ts, amount FROM candles
|
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WHERE symbol = eb.symbol AND timeframe = '1d'
|
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ORDER BY ts DESC LIMIT 1
|
||||
) c ON true
|
||||
LEFT JOIN LATERAL (
|
||||
SELECT close FROM candles
|
||||
WHERE symbol = eb.symbol AND timeframe = '1d' AND ts < c.ts
|
||||
ORDER BY ts DESC LIMIT 1
|
||||
) prev ON c.ts IS NOT NULL
|
||||
WHERE (:search = '' OR eb.symbol LIKE :psearch OR eb.name LIKE :psearch)
|
||||
AND (:exchange = '' OR eb.exchange = :exchange)
|
||||
AND (:watched_only = false OR w.id IS NOT NULL)
|
||||
ORDER BY {order_by}
|
||||
LIMIT :limit OFFSET :offset
|
||||
"""
|
||||
|
||||
_ETFS_COUNT_SQL = text("""
|
||||
SELECT count(*) FROM etf_basic eb
|
||||
LEFT JOIN watchlist_items w ON w.ts_code = eb.ts_code AND w.user_id = :uid
|
||||
WHERE (:search = '' OR eb.symbol LIKE :psearch OR eb.name LIKE :psearch)
|
||||
AND (:exchange = '' OR eb.exchange = :exchange)
|
||||
AND (:watched_only = false OR w.id IS NOT NULL)
|
||||
""")
|
||||
|
||||
|
||||
def _etfs_sql(sort: str, order: str) -> TextClause:
|
||||
col = _ETFS_SORTS.get(sort, _ETFS_SORTS["symbol"])
|
||||
direction = "DESC" if order == "desc" else "ASC"
|
||||
nulls = " NULLS LAST" if col != "eb.symbol" else "" # 无行情/无快照的排最后
|
||||
return text(_ETFS_SQL_TMPL.format(order_by=f"{col} {direction}{nulls}"))
|
||||
|
||||
|
||||
@router.get("/etfs", response_model=EtfListResponse)
|
||||
async def list_etfs(
|
||||
search: str = "",
|
||||
exchange: str = "",
|
||||
watched_only: bool = False,
|
||||
sort: str = "symbol",
|
||||
order: str = "asc",
|
||||
limit: int = 100,
|
||||
offset: int = 0,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> Response:
|
||||
"""全市场场内 ETF 列表：etf_basic 名称/规模（东财快照）+ candles 最新收盘/涨跌幅/成交额。
|
||||
exchange ∈ {SH, SZ}（空 = 全部）；sort ∈ {symbol,close,pct_chg,amount,total_mv,circ_mv,
|
||||
turnover_rate}（白名单，其他值回落 symbol），order ∈ asc/desc；快照/行情列排序时
|
||||
缺失值恒排末尾。缓存：按「用户自选版本 + etf 版本 + 查询参数」缓存整页，
|
||||
ETF 同步完成（bump ver:etf / ver:candles）或自选增删即失效。
|
||||
"""
|
||||
search = search.strip()
|
||||
sort = sort if sort in _ETFS_SORTS else "symbol"
|
||||
order = "desc" if order.lower() == "desc" else "asc"
|
||||
limit = max(1, min(limit, 500))
|
||||
offset = max(0, offset)
|
||||
key = (
|
||||
f"etfsj:u{user.id}"
|
||||
f":v{await cache.get_version(f'watchlist:{user.id}')}"
|
||||
f":v{await cache.get_version('etf')}"
|
||||
f":{cache.digest(search, exchange, watched_only, sort, order, limit, offset)}"
|
||||
)
|
||||
cached = await cached_json_response(key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
params = {
|
||||
"search": search, "psearch": f"%{search}%",
|
||||
"exchange": exchange.upper(), "watched_only": watched_only,
|
||||
"uid": user.id, "limit": limit, "offset": offset,
|
||||
}
|
||||
total = (await session.execute(_ETFS_COUNT_SQL, params)).scalar_one()
|
||||
rows = (await session.execute(_etfs_sql(sort, order), params)).mappings().all()
|
||||
resp = EtfListResponse(total=total, items=[EtfListItemOut(**r) for r in rows])
|
||||
raw = raw_json(resp)
|
||||
cache.local_set(key, raw, ttl=min(120, settings.stocks_cache_ttl))
|
||||
cache.set_bg(key, raw, ttl=settings.stocks_cache_ttl)
|
||||
return Response(content=raw, media_type="application/json")
|
||||
|
||||
|
||||
@router.post("/etf/sync", response_model=EtfSyncStatus)
|
||||
async def etf_sync_start(req: EtfSyncRequest) -> EtfSyncStatus:
|
||||
"""启动全市场 ETF 同步（后台任务：东财快照 -> etf_basic，逐只日线 -> candles）。"""
|
||||
return EtfSyncStatus(**await etf_sync_mod.start_sync(full=req.full))
|
||||
|
||||
|
||||
@router.get("/etf/sync/status", response_model=EtfSyncStatus)
|
||||
async def etf_sync_status(session: AsyncSession = Depends(get_session)) -> EtfSyncStatus:
|
||||
"""ETF 同步任务状态与数据实况（ETF 数 / 最新交易日）。"""
|
||||
return EtfSyncStatus(**await etf_sync_mod.get_status(session))
|
||||
252
backend/app/api/market.py
Normal file
252
backend/app/api/market.py
Normal file
@@ -0,0 +1,252 @@
|
||||
"""行情专题路由：大盘总览 / 打板 / 概念板块 / 指数（上证 K 线、国际指数、指数详情与权重）。"""
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import datetime
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Response
|
||||
from pydantic import TypeAdapter
|
||||
from sqlalchemy import select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from .. import cache
|
||||
from ..data import index_global as index_mod
|
||||
from ..data import limit_board as limit_board_mod
|
||||
from ..data import ths_board as ths_board_mod
|
||||
from ..data.index_series import SH_INDEX, get_index_daily
|
||||
from ..data.aggregation import resample_bars
|
||||
from ..data.limit_board import LimitBoardError
|
||||
from ..data.market_overview import MarketOverviewError, fetch_overview
|
||||
from ..data.ths_board import ThsBoardError
|
||||
from ..db import async_session, get_session
|
||||
from ..models import StockBasic, TradeCalendar
|
||||
from ..schemas import (
|
||||
CandleOut,
|
||||
GlobalIndexListResponse,
|
||||
IndexBasicOut,
|
||||
IndexDetailResponse,
|
||||
IndexQuoteBriefOut,
|
||||
IndexValuationPointOut,
|
||||
IndexWeightItemOut,
|
||||
IndexWeightsResponse,
|
||||
LimitBoardResponse,
|
||||
MarketOverviewResponse,
|
||||
ThsBoardListResponse,
|
||||
ThsBoardMembersResponse,
|
||||
)
|
||||
from ._deps import INDEX_TIMEFRAMES, cached_json_response
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
async def _is_trading_day_today() -> bool | None:
|
||||
"""今日是否 A 股交易日（trade_date 为 String(8) unique 索引，等值查亚毫秒级）；
|
||||
DB 不可用时返回 None，调用方回退 weekday 启发式（只影响盘中 TTL 精度）。"""
|
||||
today8 = datetime.now().strftime("%Y%m%d")
|
||||
try:
|
||||
async with async_session() as s:
|
||||
return bool(await s.scalar(
|
||||
select(TradeCalendar.id).where(TradeCalendar.trade_date == today8).limit(1)
|
||||
))
|
||||
except Exception: # noqa: BLE001
|
||||
return None
|
||||
|
||||
|
||||
@router.get("/market/overview", response_model=MarketOverviewResponse)
|
||||
async def get_market_overview(session: AsyncSession = Depends(get_session)) -> MarketOverviewResponse:
|
||||
"""主页大盘总览：A 股 + 港美指数实时价（腾讯）叠加收盘历史走势（tushare），
|
||||
沪深两市市值/成交统计 + 成交额历史。部分来源失败不影响其余。
|
||||
"""
|
||||
is_trading_day: bool | None = None
|
||||
try:
|
||||
is_trading_day = bool(await session.scalar(
|
||||
select(TradeCalendar.id).where(
|
||||
TradeCalendar.trade_date == datetime.now().strftime("%Y%m%d")).limit(1)
|
||||
))
|
||||
except Exception: # noqa: BLE001 —— 判定失败只影响「今日盘中 bar」是否追加
|
||||
pass
|
||||
try:
|
||||
data = await fetch_overview(is_trading_day=is_trading_day)
|
||||
except MarketOverviewError as e:
|
||||
raise HTTPException(status_code=503, detail=str(e)) from e
|
||||
return MarketOverviewResponse(**data)
|
||||
|
||||
|
||||
@router.get("/market/limit-board", response_model=LimitBoardResponse)
|
||||
async def get_limit_board(session: AsyncSession = Depends(get_session)) -> LimitBoardResponse:
|
||||
"""首页打板专题（同花顺口径）：涨停/炸板/跌停三池 + 连板天梯 + 涨停最强板块，
|
||||
当日快照（盘中 5 分钟 / 盘后 4 小时，整包 SWR 缓存）。部分池失败不影响其余。"""
|
||||
is_trading_day: bool | None = None
|
||||
try:
|
||||
is_trading_day = bool(await session.scalar(
|
||||
select(TradeCalendar.id).where(
|
||||
TradeCalendar.trade_date == datetime.now().strftime("%Y%m%d")).limit(1)
|
||||
))
|
||||
except Exception: # noqa: BLE001 —— 判定失败回退 weekday 启发式（影响盘中 TTL 精度而已）
|
||||
pass
|
||||
try:
|
||||
data = await limit_board_mod.fetch_limit_board(is_trading_day)
|
||||
except LimitBoardError as e:
|
||||
raise HTTPException(status_code=503, detail=str(e)) from e
|
||||
return LimitBoardResponse(**data)
|
||||
|
||||
|
||||
@router.get("/market/boards", response_model=ThsBoardListResponse)
|
||||
async def list_ths_boards() -> ThsBoardListResponse:
|
||||
"""概念/行业板块列表（同花顺口径，全部类型一次给全，前端本地过滤）：
|
||||
ths_index 列表直缓存 24h + ths_daily 当日快照 SWR（盘中 5 分钟 / 盘后 4 小时）。"""
|
||||
try:
|
||||
data = await ths_board_mod.fetch_boards(await _is_trading_day_today())
|
||||
except ThsBoardError as e:
|
||||
raise HTTPException(status_code=503, detail=str(e)) from e
|
||||
return ThsBoardListResponse(**data)
|
||||
|
||||
|
||||
@router.get("/market/boards/{code}/members", response_model=ThsBoardMembersResponse)
|
||||
async def list_ths_board_members(code: str, session: AsyncSession = Depends(get_session)) -> ThsBoardMembersResponse:
|
||||
"""板块成分股（ths_member 懒加载缓存 24h）+ 最新现价/涨跌幅（candles LATERAL 现算）。"""
|
||||
bc = code.strip().upper()
|
||||
try:
|
||||
boards = await ths_board_mod.get_board_list()
|
||||
except ThsBoardError as e:
|
||||
raise HTTPException(status_code=503, detail=str(e)) from e
|
||||
board = next((b for b in boards if b["ts_code"] == bc), None)
|
||||
if board is None:
|
||||
raise HTTPException(status_code=404, detail=f"未知板块: {bc}")
|
||||
try:
|
||||
members = await ths_board_mod.get_members(session, bc)
|
||||
except Exception:
|
||||
raise HTTPException(status_code=503, detail="板块成分拉取失败，请稍后重试")
|
||||
return ThsBoardMembersResponse(code=bc, name=board.get("name"), members=members)
|
||||
|
||||
|
||||
@router.get("/market/index-candles", response_model=list[CandleOut])
|
||||
async def get_index_candles(timeframe: str = "1d") -> Response:
|
||||
"""上证指数全量 K 线：日线为基底（tushare index_daily，进程内+Redis 缓存），
|
||||
聚合到 1d/1w/1M/1y。收盘口径（数据随 EOD 更新，与总览 spark 一致）。"""
|
||||
if timeframe not in INDEX_TIMEFRAMES:
|
||||
raise HTTPException(status_code=400, detail=f"timeframe 仅支持 {'/'.join(INDEX_TIMEFRAMES)}")
|
||||
key = f"idxkj:{cache.digest('idxc', SH_INDEX, timeframe)}"
|
||||
cached = await cached_json_response(key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
try:
|
||||
bars = resample_bars(await get_index_daily(), timeframe)
|
||||
except Exception as e: # noqa: BLE001
|
||||
raise HTTPException(status_code=502, detail=f"指数数据获取失败: {e}")
|
||||
outs = [
|
||||
CandleOut(ts=b.ts, open=b.open, high=b.high, low=b.low, close=b.close,
|
||||
volume=b.volume, amount=b.amount, turnover=None)
|
||||
for b in bars
|
||||
]
|
||||
# pydantic-core 序列化（与 raw_json 同款），历史不可变、TTL 兜到当日更新
|
||||
raw = TypeAdapter(list[CandleOut]).dump_json(outs).decode()
|
||||
cache.local_set(key, raw, ttl=300)
|
||||
await cache.cache_set(key, raw, ttl=7200)
|
||||
return Response(content=raw, media_type="application/json")
|
||||
|
||||
|
||||
@router.get("/market/global-indexes", response_model=GlobalIndexListResponse)
|
||||
async def get_global_indexes() -> GlobalIndexListResponse:
|
||||
"""国际指数卡片列表（index_global 21 个指数最新收盘 + 45 日 spark，SWR 缓存）。"""
|
||||
try:
|
||||
data = await index_mod.fetch_global_list()
|
||||
except index_mod.GlobalIndexError as e:
|
||||
raise HTTPException(status_code=503, detail=str(e)) from e
|
||||
payload = dict(data)
|
||||
payload["updated_at"] = payload.pop("fetched_at")
|
||||
return GlobalIndexListResponse(**payload)
|
||||
|
||||
|
||||
def _index_or_404(code: str) -> str:
|
||||
"""详情/K线/权重接口只放行白名单内的指数 code。"""
|
||||
if not index_mod.ensure_known(code):
|
||||
raise HTTPException(status_code=404, detail=f"不支持的指数代码: {code}")
|
||||
return code
|
||||
|
||||
|
||||
@router.get("/market/indexes/{code}", response_model=IndexDetailResponse)
|
||||
async def get_index_detail(code: str) -> IndexDetailResponse:
|
||||
"""指数详情聚合：最新行情（收盘口径）+ 基本信息（国内 index_basic / 国际静态表）
|
||||
+ 估值指标（index_dailybasic，仅部分国内指数）。各层自带缓存，直接组装。"""
|
||||
code = _index_or_404(code)
|
||||
if index_mod.is_cn_index(code):
|
||||
name, region = index_mod.CN_INDEXES.get(code, code), "cn"
|
||||
else:
|
||||
g = index_mod.GLOBAL_META[code]
|
||||
name, region = g["name"], g["region"]
|
||||
|
||||
try:
|
||||
quote = await index_mod.fetch_index_quote(code)
|
||||
except index_mod.GlobalIndexError as e:
|
||||
raise HTTPException(status_code=502, detail=f"指数行情获取失败: {e}") from e
|
||||
|
||||
basic_raw = await index_mod.get_index_basic(code)
|
||||
basic = IndexBasicOut(**basic_raw) if basic_raw else None
|
||||
|
||||
valuation_rows = await index_mod.get_index_valuation(code)
|
||||
valuation = IndexValuationPointOut(**valuation_rows[-1]) if valuation_rows else None
|
||||
history = [IndexValuationPointOut(**r) for r in valuation_rows]
|
||||
|
||||
return IndexDetailResponse(
|
||||
code=code, name=name, region=region,
|
||||
quote=IndexQuoteBriefOut(**quote),
|
||||
basic=basic, valuation=valuation, valuation_history=history,
|
||||
)
|
||||
|
||||
|
||||
@router.get("/market/indexes/{code}/candles", response_model=list[CandleOut])
|
||||
async def get_any_index_candles(code: str, timeframe: str = "1d") -> Response:
|
||||
"""白名单指数全量 K 线（国内 index_daily / 国际 index_global），1d/1w/1M/1y 聚合。
|
||||
收盘口径，历史不可变、TTL 兜到当日更新（与首页上证 K 线同款缓存策略）。"""
|
||||
code = _index_or_404(code)
|
||||
if timeframe not in INDEX_TIMEFRAMES:
|
||||
raise HTTPException(status_code=400, detail=f"timeframe 仅支持 {'/'.join(INDEX_TIMEFRAMES)}")
|
||||
key = f"idxck:{cache.digest('idxk2', code, timeframe)}"
|
||||
cached = await cached_json_response(key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
try:
|
||||
bars = resample_bars(await index_mod.get_index_bars(code), timeframe)
|
||||
except Exception as e: # noqa: BLE001
|
||||
raise HTTPException(status_code=502, detail=f"指数数据获取失败: {e}")
|
||||
outs = [
|
||||
CandleOut(ts=b.ts, open=b.open, high=b.high, low=b.low, close=b.close,
|
||||
volume=b.volume, amount=b.amount, turnover=None)
|
||||
for b in bars
|
||||
]
|
||||
raw = TypeAdapter(list[CandleOut]).dump_json(outs).decode()
|
||||
cache.local_set(key, raw, ttl=300)
|
||||
await cache.cache_set(key, raw, ttl=7200)
|
||||
return Response(content=raw, media_type="application/json")
|
||||
|
||||
|
||||
@router.get("/market/indexes/{code}/weights", response_model=IndexWeightsResponse)
|
||||
async def get_index_weights(
|
||||
code: str,
|
||||
limit: int = 50,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
) -> IndexWeightsResponse:
|
||||
"""指数成分股权重（index_weight 最近月度快照，按权重降序取前 limit）。
|
||||
仅国内指数有数据；成分股名称从本地 stock_basic 回填。"""
|
||||
code = _index_or_404(code)
|
||||
limit = max(1, min(limit, 300))
|
||||
data = await index_mod.get_index_weights(code)
|
||||
if data is None:
|
||||
raise HTTPException(status_code=404, detail=f"该指数暂无成分权重数据: {code}")
|
||||
|
||||
items = data["items"][:limit]
|
||||
codes = [it["con_code"] for it in items]
|
||||
names: dict[str, str] = {}
|
||||
if codes:
|
||||
try:
|
||||
rows = await session.execute(
|
||||
select(StockBasic.ts_code, StockBasic.name).where(StockBasic.ts_code.in_(codes))
|
||||
)
|
||||
names = {r[0]: r[1] for r in rows.all()}
|
||||
except Exception: # noqa: BLE001 —— 名称缺失不阻塞权重展示
|
||||
pass
|
||||
return IndexWeightsResponse(
|
||||
trade_date=data["trade_date"], total=data["total"],
|
||||
items=[IndexWeightItemOut(con_code=c, name=names.get(c), weight=w)
|
||||
for c, w in ((it["con_code"], it["weight"]) for it in items)],
|
||||
)
|
||||
422
backend/app/api/screener.py
Normal file
422
backend/app/api/screener.py
Normal file
@@ -0,0 +1,422 @@
|
||||
"""智能选股域路由：自然语言选股（NDJSON 流式）+ 提问历史 + 全市场同步 + 个股预览。"""
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
from datetime import datetime
|
||||
|
||||
import pandas as pd
|
||||
from fastapi import APIRouter, Depends, HTTPException, Response
|
||||
from fastapi.responses import StreamingResponse
|
||||
from sqlalchemy import func, select, text
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from .. import cache
|
||||
from .. import indicators as ind
|
||||
from ..auth import require_user
|
||||
from ..config import settings
|
||||
from ..data import fetcher, repository
|
||||
from ..data.aggregation import resample_bars
|
||||
from ..data.symbols import plain_code
|
||||
from ..db import async_session, get_session
|
||||
from ..models import AdjFactor, Candle, ScreenerQuery
|
||||
from ..schemas import (
|
||||
CandleOut,
|
||||
PreviewInfoOut,
|
||||
PreviewResponse,
|
||||
ScreenerQueryListResponse,
|
||||
ScreenerQueryOut,
|
||||
ScreenerRunRequest,
|
||||
ScreenerRunResponse,
|
||||
ScreenerSyncRequest,
|
||||
ScreenerSyncStatus,
|
||||
)
|
||||
from ..screener import engine, market_sync
|
||||
from ..screener.engine import DataNotReadyError
|
||||
from ..screener.llm import ScreenerError, parse_conditions
|
||||
from ._deps import (
|
||||
ADJUST_MODES,
|
||||
FACTOR_STEP_SQL,
|
||||
FULL_MA_SET,
|
||||
INFO_SQL,
|
||||
adjust_bars,
|
||||
cached_json_response,
|
||||
raw_json,
|
||||
rows_to_bars,
|
||||
series_to_jsonable,
|
||||
)
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
# ---------- 智能选股 ----------
|
||||
@router.post("/screener/run")
|
||||
async def screener_run(
|
||||
req: ScreenerRunRequest,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> StreamingResponse:
|
||||
"""自然语言 -> LLM 解析条件 -> 全市场筛选。也可直传 conditions 跳过 LLM（微调再跑）。
|
||||
|
||||
NDJSON 流式响应（每行一个 JSON 事件，前端逐行渲染进度）：
|
||||
{"type":"stage","key":"llm|date|prefilter|bars|filter_done|done","msg":"…","ms":123}
|
||||
{"type":"parsed","conditions":{…},"ms":456} LLM 解析出的结构化条件
|
||||
{"type":"candidates","count":5400,"msg":"…","ms":…} SQL 预筛后的候选数
|
||||
{"type":"progress","done":500,"total":5400} 逐股指标过滤进度
|
||||
{"type":"result","result":{…ScreenerRunResponse…},"ms":…}
|
||||
{"type":"error","message":"…","code":400} 流中途失败（HTTP 已 200）
|
||||
成功的提问（含解析出的条件与命中数）记录到 screener_queries，供历史一键重跑。
|
||||
"""
|
||||
limit = settings.screener_default_limit
|
||||
|
||||
async def gen():
|
||||
try:
|
||||
if req.conditions:
|
||||
conds = req.conditions
|
||||
else:
|
||||
yield _ndjson({"type": "stage", "key": "llm",
|
||||
"msg": f"AI 解析条件中（{settings.llm_model}）…"})
|
||||
conds = await parse_conditions(req.text)
|
||||
if not conds.indicator and not conds.snapshot:
|
||||
yield _ndjson({"type": "error", "code": 400,
|
||||
"message": "AI 未从描述中解析出任何筛选条件，请换种说法"})
|
||||
return
|
||||
yield _ndjson({"type": "parsed", "conditions": conds.model_dump()})
|
||||
|
||||
result = None
|
||||
async for ev in engine.run_screen_events(session, conds, limit):
|
||||
if ev["type"] == "result":
|
||||
result = ev["result"]
|
||||
yield _ndjson({"type": "stage", "key": "done", "ms": ev.get("ms"),
|
||||
"msg": f"筛选完成：{result['total']} 只命中（数据基准 {result['trade_date']:%Y-%m-%d}）"})
|
||||
else:
|
||||
yield _ndjson(ev)
|
||||
|
||||
if result is None:
|
||||
yield _ndjson({"type": "error", "code": 500, "message": "选股流程未产出结果"})
|
||||
return
|
||||
yield _ndjson({"type": "result", "result": ScreenerRunResponse(**result).model_dump(mode="json")})
|
||||
|
||||
# 相同文本 + 相同条件的上一条不重复记录（一键重跑场景）
|
||||
exists = (
|
||||
await session.execute(
|
||||
select(ScreenerQuery.id).where(
|
||||
ScreenerQuery.user_id == user.id,
|
||||
ScreenerQuery.text == req.text.strip(),
|
||||
ScreenerQuery.conditions_json == json.dumps(conds.model_dump(), ensure_ascii=False),
|
||||
)
|
||||
)
|
||||
).scalar_one_or_none()
|
||||
if exists is None:
|
||||
session.add(ScreenerQuery(
|
||||
user_id=user.id,
|
||||
text=req.text.strip(),
|
||||
conditions_json=json.dumps(conds.model_dump(), ensure_ascii=False),
|
||||
hit_count=result.get("total", 0),
|
||||
))
|
||||
await session.commit()
|
||||
except DataNotReadyError as e:
|
||||
yield _ndjson({"type": "error", "code": 409, "message": str(e)})
|
||||
except ValueError as e: # 未知指标/字段、条件为空
|
||||
yield _ndjson({"type": "error", "code": 400, "message": str(e)})
|
||||
except ScreenerError as e:
|
||||
code = 503 if "未配置 LLM_API_KEY" in str(e) else 502
|
||||
yield _ndjson({"type": "error", "code": code, "message": str(e)})
|
||||
except Exception as e: # noqa: BLE001
|
||||
yield _ndjson({"type": "error", "code": 500, "message": f"选股失败: {e}"})
|
||||
|
||||
return StreamingResponse(gen(), media_type="application/x-ndjson",
|
||||
headers={"Cache-Control": "no-store", "X-Accel-Buffering": "no"})
|
||||
|
||||
|
||||
def _ndjson(obj: dict) -> str:
|
||||
"""dict -> NDJSON 行（json.dumps 保证 default=str 兜底 datetime 等）。"""
|
||||
return json.dumps(obj, ensure_ascii=False, default=str) + "\n"
|
||||
|
||||
|
||||
@router.get("/screener/queries", response_model=ScreenerQueryListResponse)
|
||||
async def screener_queries(
|
||||
limit: int = 20,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> ScreenerQueryListResponse:
|
||||
"""当前用户的提问历史（最新在前，含解析出的条件与命中数，可一键重跑）。"""
|
||||
limit = max(1, min(limit, 100))
|
||||
rows = (
|
||||
await session.execute(
|
||||
select(ScreenerQuery)
|
||||
.where(ScreenerQuery.user_id == user.id)
|
||||
.order_by(ScreenerQuery.created_at.desc())
|
||||
.limit(limit)
|
||||
)
|
||||
).scalars().all()
|
||||
items = []
|
||||
for r in rows:
|
||||
conds = None
|
||||
if r.conditions_json:
|
||||
try:
|
||||
from ..schemas import ScreenConditions
|
||||
conds = ScreenConditions.model_validate_json(r.conditions_json)
|
||||
except Exception: # noqa: BLE001 —— 旧格式/解析失败则只展示文本
|
||||
conds = None
|
||||
items.append(ScreenerQueryOut(
|
||||
id=r.id, text=r.text, conditions=conds, hit_count=r.hit_count, created_at=r.created_at
|
||||
))
|
||||
return ScreenerQueryListResponse(items=items)
|
||||
|
||||
|
||||
@router.delete("/screener/queries/{query_id}", status_code=204)
|
||||
async def screener_query_delete(
|
||||
query_id: int,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> None:
|
||||
await session.execute(
|
||||
text("DELETE FROM screener_queries WHERE id = :i AND user_id = :u"),
|
||||
{"i": query_id, "u": user.id},
|
||||
)
|
||||
await session.commit()
|
||||
|
||||
|
||||
# ---------- 全市场数据同步 ----------
|
||||
@router.post("/screener/sync", response_model=ScreenerSyncStatus)
|
||||
async def screener_sync_start(
|
||||
req: ScreenerSyncRequest, session: AsyncSession = Depends(get_session)
|
||||
) -> ScreenerSyncStatus:
|
||||
"""启动全市场数据同步（后台任务，立即返回状态）。"""
|
||||
try:
|
||||
await market_sync.start_sync(session, req.days, req.force)
|
||||
except ScreenerError as e:
|
||||
raise HTTPException(status_code=503, detail=str(e))
|
||||
status = await market_sync.get_sync_status(session)
|
||||
return ScreenerSyncStatus(**{k: status.get(k) for k in ScreenerSyncStatus.model_fields})
|
||||
|
||||
|
||||
@router.get("/screener/sync/status", response_model=ScreenerSyncStatus)
|
||||
async def screener_sync_status(session: AsyncSession = Depends(get_session)) -> ScreenerSyncStatus:
|
||||
"""同步任务状态 + 数据实况（最新交易日/行数/ready）。"""
|
||||
status = await market_sync.get_sync_status(session)
|
||||
return ScreenerSyncStatus(**{k: status.get(k) for k in ScreenerSyncStatus.model_fields})
|
||||
|
||||
|
||||
# ---------- 个股详情预览 ----------
|
||||
@router.get("/screener/preview/{ts_code}", response_model=PreviewResponse)
|
||||
async def screener_preview(
|
||||
ts_code: str, limit: int = 500, adjust: str = "qfq", timeframe: str = "1d", mas: str = "5,10,20,60",
|
||||
zx: str = "10,20,30,60", end: str | None = None,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
) -> Response:
|
||||
"""个股详情预览：日线（candles 不复权底座 + adj_factor 本地换算 bfq/qfq/hfq，
|
||||
未缓存自动拉取，落后全市场最新交易日则强制刷新）+ 全套指标 + 最新截面信息卡。
|
||||
timeframe 聚合到周/月/年（先复权再聚合）；mas 指定主图 MA 周期（逗号分隔）。
|
||||
end=YYYY-MM-DD 时为「向前翻页」：返回该日之前最近 limit 根（含预热计算指标），
|
||||
has_more 标记窗口前是否还有更早历史，前端据此继续向左滚动加载。"""
|
||||
if adjust not in ADJUST_MODES:
|
||||
raise HTTPException(status_code=400, detail=f"adjust 仅支持 {'/'.join(ADJUST_MODES)}")
|
||||
if timeframe not in ("1d", "1w", "1M", "1y"):
|
||||
raise HTTPException(status_code=400, detail="timeframe 仅支持 1d/1w/1M/1y")
|
||||
try:
|
||||
ma_periods = sorted({int(p) for p in mas.split(",") if p.strip().isdigit() and 1 <= int(p) <= 500})
|
||||
except ValueError:
|
||||
raise HTTPException(status_code=400, detail="mas 格式应为逗号分隔的数字，如 5,10,20,60")
|
||||
if not ma_periods:
|
||||
ma_periods = [5, 10, 20, 60]
|
||||
try:
|
||||
zx_periods = sorted({int(p) for p in zx.split(",") if p.strip().isdigit() and 1 <= int(p) <= 500})
|
||||
except ValueError:
|
||||
raise HTTPException(status_code=400, detail="zx 格式应为逗号分隔的数字，如 10,20,30,60")
|
||||
if not zx_periods:
|
||||
zx_periods = [10, 20, 30, 60]
|
||||
limit = max(30, min(limit, 5000))
|
||||
end_dt: datetime | None = None
|
||||
if end:
|
||||
try:
|
||||
end_dt = datetime.strptime(end.strip()[:10], "%Y-%m-%d")
|
||||
except ValueError:
|
||||
raise HTTPException(status_code=400, detail="end 格式应为 YYYY-MM-DD")
|
||||
symbol = plain_code(ts_code)
|
||||
|
||||
# --- 两级读缓存：历史窗口（end 翻页）只增不改，最新窗口每日由全市场同步推进；
|
||||
# 键含 ver:candles 版本号（同步完成后自增，旧缓存全部失效），TTL 兜底（cache.py）。
|
||||
# 存序列化好的 JSON 直返（j: 前缀），跳过 json.loads + pydantic 校验/序列化（热路径数百 ms → 个位数）。
|
||||
# 注：ma_periods 不参与缓存键 —— 前端已改为本地计算 MA，后端始终返回全量 MA 集合
|
||||
cache_key = cache.digest(
|
||||
"preview", ts_code, timeframe, limit, adjust,
|
||||
end_dt.strftime("%Y-%m-%d") if end_dt else None,
|
||||
await cache.get_version("candles"),
|
||||
)
|
||||
cached = await cached_json_response(f"pvj:{cache_key}")
|
||||
if cached is not None:
|
||||
return cached
|
||||
|
||||
# --- 日线：candles(全量不复权底座)；未缓存拉取，落后于全市场最新交易日则强制刷新 ---
|
||||
# fetcher 只做「不复权」增量 upsert，底座口径恒为 bfq（TDX 全量 + Tushare 增量），
|
||||
# 复权（qfq/hfq）读取时按 adj_factor 表本地换算。
|
||||
# 每次只取「窗口 + 400 根预热」行（MA250/MACD EMA 在 400 根内充分收敛），不拉全量：
|
||||
# 首屏 ~500 根秒开，向左滚动时按 end 参数逐页向前翻。
|
||||
frame_mult = {"1d": 1, "1w": 6, "1M": 24, "1y": 280}[timeframe]
|
||||
fetch_n = min(100000, limit * frame_mult + 400)
|
||||
source = "bfq"
|
||||
mode = "bfq"
|
||||
# 并发约定：注入 session 与 s2 各占一条连接，每次 gather 里每个 session 恰好跑一条查询
|
||||
# （AsyncSession 单连接非并发安全），把 ~6 次串行 DB RTT 折叠成 2 个波次。
|
||||
async with async_session() as s2:
|
||||
if end_dt is not None:
|
||||
# 向前翻页：取 end 之前的历史窗口，不触发同步（历史浏览）；max(ts) 用不到
|
||||
rows = await repository.get_candles_before(session, symbol, "1d", before=end_dt, limit=fetch_n)
|
||||
global_latest = None
|
||||
else:
|
||||
# Wave 1：candles 窗口（注入 session）+ 全市场最新交易日（s2）并行
|
||||
rows, global_latest = await asyncio.gather(
|
||||
repository.get_recent_candles(session, symbol, "1d", limit=fetch_n),
|
||||
s2.scalar(select(func.max(Candle.ts)).where(Candle.timeframe == "1d")),
|
||||
)
|
||||
try:
|
||||
if not rows:
|
||||
await fetcher.sync_symbol(session, symbol, source="auto")
|
||||
rows = await repository.get_recent_candles(session, symbol, "1d", limit=fetch_n)
|
||||
elif global_latest is not None and rows[-1].ts.date() < global_latest.date():
|
||||
await fetcher.sync_symbol(session, symbol, source="auto", force=True)
|
||||
rows = await repository.get_recent_candles(session, symbol, "1d", limit=fetch_n)
|
||||
except Exception: # noqa: BLE001 —— tushare/写库失败时回滚会话（否则毒化后兜底查询 500）
|
||||
await session.rollback()
|
||||
if not rows:
|
||||
rows = []
|
||||
bars = rows_to_bars(rows)
|
||||
|
||||
if not bars and end_dt is None:
|
||||
raise HTTPException(status_code=404, detail=f"无数据: {ts_code}（可先点「同步市场数据」）")
|
||||
# 信息卡取未聚合的日线最新 bar（聚合后 ts 是周期起点，不适用于「最新交易日」）
|
||||
last_daily = bars[-1] if bars else None
|
||||
prev_daily = bars[-2] if len(bars) > 1 else None
|
||||
# 翻页到底（end 之前无数据）：返回空页 + has_more=False，前端停止向前翻页
|
||||
|
||||
# --- Wave 2：复权因子（s2，覆盖索引 Index Only Scan）+ 信息卡（注入 session，LATERAL 一条）并行 ---
|
||||
async def _fetch_factors() -> list | None:
|
||||
if adjust == mode or not bars:
|
||||
return None
|
||||
# 只取因子「变化点」行（覆盖索引 Index Only Scan，免堆访问——adj_factor 堆碎片化
|
||||
# 严重）；bisect 在阶梯函数上取值与日级序列逐字节一致
|
||||
if end_dt is not None:
|
||||
# 分页：窗口 ≤ end 的变化点 + 全局最新因子（qfq 以最新因子归一）
|
||||
win = list((await s2.execute(FACTOR_STEP_SQL, {"code": ts_code, "upto": end_dt})).all())
|
||||
if win:
|
||||
latest_f = (await s2.execute(
|
||||
select(AdjFactor.trade_date, AdjFactor.adj_factor)
|
||||
.where(AdjFactor.ts_code == ts_code)
|
||||
.order_by(AdjFactor.trade_date.desc()).limit(1)
|
||||
)).first()
|
||||
if latest_f is not None:
|
||||
win.append(latest_f)
|
||||
return win or None
|
||||
# 非分页：上界 global_latest（≥ 最新 bar），末项变化点即全局最新因子，比
|
||||
# 「窗口 ≤ bars[-1].ts + 单独 latest」少一次查询
|
||||
return list((await s2.execute(
|
||||
FACTOR_STEP_SQL, {"code": ts_code, "upto": global_latest}
|
||||
)).all()) or None
|
||||
|
||||
factors, info_row = await asyncio.gather(
|
||||
_fetch_factors(),
|
||||
session.execute(INFO_SQL, {"code": ts_code, "target": last_daily.ts if last_daily else None}),
|
||||
)
|
||||
|
||||
# --- 复权换算：请求模式与底座模式不同时按 adj_factor 本地换算（无因子则维持原样） ---
|
||||
if factors:
|
||||
bars = adjust_bars(bars, factors, mode, adjust)
|
||||
mode = adjust
|
||||
source = adjust
|
||||
|
||||
# --- 周期聚合：复权之后按日历聚合到周/月/年，指标在聚合后的序列上计算 ---
|
||||
bars = resample_bars(bars, timeframe)
|
||||
|
||||
# --- 指标（在预热窗口上计算后截尾，保证预热正确；翻页到底的空页跳过） ---
|
||||
has_more = len(bars) > limit # 返回窗口之前还有更早历史（含预热行）
|
||||
indicators: dict[str, dict[str, list[float | None]]] = {}
|
||||
if bars:
|
||||
df = pd.DataFrame({"close": [b.close for b in bars], "high": [b.high for b in bars], "low": [b.low for b in bars]})
|
||||
closes, highs, lows = df["close"], df["high"], df["low"]
|
||||
macd = ind.macd(closes)
|
||||
kdj = ind.kdj(highs, lows, closes)
|
||||
boll = ind.bollinger(closes)
|
||||
indicators = {
|
||||
# MA 始终返回全量集合（前端本地计算 MA，此处仅保留兼容；缓存键不依赖 ma_periods）
|
||||
"ma": {f"ma{p}": series_to_jsonable(ind.ma(closes, p)) for p in FULL_MA_SET},
|
||||
"macd": {
|
||||
"dif": series_to_jsonable(macd["macd"]),
|
||||
"dea": series_to_jsonable(macd["signal"]),
|
||||
"hist": series_to_jsonable(macd["hist"]),
|
||||
},
|
||||
"kdj": {k: series_to_jsonable(kdj[k]) for k in ("k", "d", "j")},
|
||||
"rsi": {
|
||||
"rsi6": series_to_jsonable(ind.rsi(closes, 6)),
|
||||
"rsi12": series_to_jsonable(ind.rsi(closes, 12)),
|
||||
"rsi24": series_to_jsonable(ind.rsi(closes, 24)),
|
||||
},
|
||||
"boll": {k: series_to_jsonable(boll[k]) for k in ("upper", "mid", "lower")},
|
||||
"zx": {
|
||||
"short": series_to_jsonable(ind.ema2(closes)),
|
||||
"duokong": series_to_jsonable(ind.avg_ma(closes, tuple(zx_periods))),
|
||||
},
|
||||
}
|
||||
limit = max(30, min(limit, len(bars)))
|
||||
for group in indicators.values():
|
||||
for key in group:
|
||||
group[key] = group[key][-limit:]
|
||||
|
||||
# --- 信息卡：Wave 2 已并行取回（stock_basic + 与行情同日对齐的快照、缺则最新日，见 INFO_SQL） ---
|
||||
row = info_row.first()
|
||||
if row is not None:
|
||||
m = row._mapping
|
||||
sb_name, sb_industry, sb_area, sb_market, sb_list_date = (
|
||||
m["name"], m["industry"], m["area"], m["market"], m["list_date"]
|
||||
)
|
||||
ds_turnover, ds_pe, ds_pb, ds_tmv, ds_cmv = (
|
||||
m["turnover_rate"], m["pe_ttm"], m["pb"], m["total_mv"], m["circ_mv"]
|
||||
)
|
||||
else:
|
||||
sb_name = sb_industry = sb_area = sb_market = sb_list_date = None
|
||||
ds_turnover = ds_pe = ds_pb = ds_tmv = ds_cmv = None
|
||||
|
||||
def _yi(v) -> float | None:
|
||||
if v is None:
|
||||
return None
|
||||
v = float(v)
|
||||
return None if v != v else round(v / 1e4, 2) # 万元 -> 亿元
|
||||
|
||||
info = PreviewInfoOut(
|
||||
ts_code=ts_code,
|
||||
symbol=symbol,
|
||||
name=sb_name or ts_code,
|
||||
industry=sb_industry,
|
||||
area=sb_area,
|
||||
market=sb_market,
|
||||
list_date=sb_list_date,
|
||||
trade_date=last_daily.ts if last_daily else None,
|
||||
open=last_daily.open if last_daily else None,
|
||||
high=last_daily.high if last_daily else None,
|
||||
low=last_daily.low if last_daily else None,
|
||||
close=last_daily.close if last_daily else None,
|
||||
pre_close=prev_daily.close if prev_daily else None,
|
||||
pct_chg=((last_daily.close / prev_daily.close - 1) * 100)
|
||||
if last_daily and prev_daily and prev_daily.close else None,
|
||||
volume_hand=round(last_daily.volume / 100, 0) if last_daily else None, # 股 -> 手
|
||||
amount_yi=round(last_daily.amount / 1e8, 2) if last_daily and last_daily.amount else None, # 元 -> 亿元
|
||||
turnover_rate=ds_turnover,
|
||||
pe_ttm=ds_pe,
|
||||
pb=ds_pb,
|
||||
total_mv=_yi(ds_tmv),
|
||||
circ_mv=_yi(ds_cmv),
|
||||
)
|
||||
|
||||
candles = [
|
||||
CandleOut(ts=b.ts, open=b.open, high=b.high, low=b.low, close=b.close,
|
||||
volume=b.volume, amount=b.amount, turnover=b.turnover)
|
||||
for b in bars[-limit:]
|
||||
]
|
||||
resp = PreviewResponse(ts_code=ts_code, symbol=symbol, source=source, info=info,
|
||||
candles=candles, indicators=indicators, has_more=has_more)
|
||||
# 只序列化一次：本地（同步，120s）+ Redis（后台写，600s TTL 兜底跨进程/重启）
|
||||
raw = raw_json(resp)
|
||||
cache.local_set(f"pvj:{cache_key}", raw, ttl=120)
|
||||
cache.set_bg(f"pvj:{cache_key}", raw, ttl=600)
|
||||
return Response(content=raw, media_type="application/json")
|
||||
283
backend/app/api/stocks.py
Normal file
283
backend/app/api/stocks.py
Normal file
@@ -0,0 +1,283 @@
|
||||
"""股票域路由：全市场列表 + 筛选项 + 个股公司/财务/分红/参考数据懒加载 + 手动数据同步。"""
|
||||
from __future__ import annotations
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Response
|
||||
from sqlalchemy import text
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from sqlalchemy.sql.elements import TextClause
|
||||
|
||||
from .. import cache
|
||||
from ..auth import require_user
|
||||
from ..config import settings
|
||||
from ..data import company as company_mod
|
||||
from ..data import dividend as dividend_mod
|
||||
from ..data import finance as finance_mod
|
||||
from ..data import reference as reference_mod
|
||||
from ..data import fetcher
|
||||
from ..data.symbols import is_etf_symbol, to_ts_code
|
||||
from ..db import get_session
|
||||
from ..schemas import (
|
||||
FacetItemOut,
|
||||
StockCompanyOut,
|
||||
StockDividendOut,
|
||||
StockFacetsResponse,
|
||||
StockFinanceOut,
|
||||
StockListItemOut,
|
||||
StockListResponse,
|
||||
StockReferenceOut,
|
||||
SyncRequest,
|
||||
SyncResponse,
|
||||
)
|
||||
from ._deps import cached_json_response, raw_json
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.post("/data/sync", response_model=SyncResponse)
|
||||
async def sync_data(req: SyncRequest, session: AsyncSession = Depends(get_session)) -> SyncResponse:
|
||||
"""主动拉取并缓存某标的的日线（Tushare 主 -> AKShare 兜底）。"""
|
||||
try:
|
||||
res = await fetcher.sync_symbol(
|
||||
session, req.symbol, start=req.start, end=req.end, source=req.source, force=req.force
|
||||
)
|
||||
return SyncResponse(**res)
|
||||
except Exception as e: # noqa: BLE001
|
||||
raise HTTPException(status_code=502, detail=str(e))
|
||||
|
||||
|
||||
# ---------- 股票列表（全市场浏览） ----------
|
||||
# 过滤/排序/分页在 stock_basic+watchlist+daily_snapshot 上完成（快照按最新交易日
|
||||
# 走唯一索引 join，便宜），再对「本页」≤limit 只股票补最新价/昨收（LATERAL 扫
|
||||
# candles，贵）——旧写法对全市场 ~5000 只逐个算，每页都白算 50 倍的行情量。
|
||||
# 排序列白名单（键→CTE 内表达式）；order_by 由白名单拼接进模板，不接收用户原文。
|
||||
_STOCKS_SORTS = {
|
||||
"symbol": "sb.symbol",
|
||||
"total_mv": "snap.total_mv",
|
||||
"circ_mv": "snap.circ_mv",
|
||||
"pe_ttm": "snap.pe_ttm",
|
||||
"pb": "snap.pb",
|
||||
"turnover_rate": "snap.turnover_rate",
|
||||
}
|
||||
|
||||
_STOCKS_SQL_TMPL = """
|
||||
WITH page AS (
|
||||
SELECT sb.ts_code, sb.symbol, sb.name, sb.industry, sb.market,
|
||||
(w.id IS NOT NULL) AS watched,
|
||||
(h.id IS NOT NULL) AS held,
|
||||
snap.turnover_rate, snap.pe_ttm, snap.pb, snap.total_mv, snap.circ_mv
|
||||
FROM stock_basic sb
|
||||
LEFT JOIN watchlist_items w ON w.ts_code = sb.ts_code AND w.user_id = :uid
|
||||
LEFT JOIN holding_items h ON h.ts_code = sb.ts_code AND h.user_id = :uid
|
||||
LEFT JOIN daily_snapshot snap ON snap.ts_code = sb.ts_code
|
||||
AND snap.trade_date = (SELECT max(trade_date) FROM daily_snapshot)
|
||||
WHERE sb.list_status = 'L'
|
||||
AND (:search = '' OR sb.symbol LIKE :psearch OR sb.name LIKE :psearch)
|
||||
AND (:market = '' OR sb.market = :market)
|
||||
AND (:industry = '' OR sb.industry = :industry)
|
||||
AND (:area = '' OR sb.area = :area)
|
||||
AND (:watched_only = false OR w.id IS NOT NULL)
|
||||
AND (:held_only = false OR h.id IS NOT NULL)
|
||||
ORDER BY {order_by}
|
||||
LIMIT :limit OFFSET :offset
|
||||
)
|
||||
SELECT p.ts_code, p.symbol, p.name, p.industry, p.market, p.watched, p.held,
|
||||
c.close AS close, prev.close AS prev_close, c.ts AS last_ts,
|
||||
CASE WHEN c.close IS NOT NULL AND prev.close IS NOT NULL AND prev.close <> 0
|
||||
THEN round(((c.close / prev.close - 1) * 100)::numeric, 2) END AS pct_chg,
|
||||
p.turnover_rate, p.pe_ttm, p.pb,
|
||||
round((p.total_mv / 10000.0)::numeric, 2) AS total_mv,
|
||||
round((p.circ_mv / 10000.0)::numeric, 2) AS circ_mv
|
||||
FROM page p
|
||||
LEFT JOIN LATERAL (
|
||||
SELECT close, ts FROM candles
|
||||
WHERE symbol = p.symbol AND timeframe = '1d'
|
||||
ORDER BY ts DESC LIMIT 1
|
||||
) c ON true
|
||||
LEFT JOIN LATERAL (
|
||||
SELECT close FROM candles
|
||||
WHERE symbol = p.symbol AND timeframe = '1d' AND ts < c.ts
|
||||
ORDER BY ts DESC LIMIT 1
|
||||
) prev ON c.ts IS NOT NULL
|
||||
"""
|
||||
|
||||
|
||||
def _stocks_sql(sort: str, order: str) -> TextClause:
|
||||
col = _STOCKS_SORTS.get(sort, _STOCKS_SORTS["symbol"])
|
||||
direction = "DESC" if order == "desc" else "ASC"
|
||||
nulls = " NULLS LAST" if col != "sb.symbol" else "" # 快照缺失/亏损无 PE 的排最后
|
||||
return text(_STOCKS_SQL_TMPL.format(order_by=f"{col} {direction}{nulls}"))
|
||||
|
||||
_STOCKS_COUNT_SQL = text("""
|
||||
SELECT count(*) FROM stock_basic sb
|
||||
LEFT JOIN watchlist_items w ON w.ts_code = sb.ts_code AND w.user_id = :uid
|
||||
LEFT JOIN holding_items h ON h.ts_code = sb.ts_code AND h.user_id = :uid
|
||||
WHERE sb.list_status = 'L'
|
||||
AND (:search = '' OR sb.symbol LIKE :psearch OR sb.name LIKE :psearch)
|
||||
AND (:market = '' OR sb.market = :market)
|
||||
AND (:industry = '' OR sb.industry = :industry)
|
||||
AND (:area = '' OR sb.area = :area)
|
||||
AND (:watched_only = false OR w.id IS NOT NULL)
|
||||
AND (:held_only = false OR h.id IS NOT NULL)
|
||||
""")
|
||||
|
||||
|
||||
@router.get("/stocks", response_model=StockListResponse)
|
||||
async def list_stocks(
|
||||
search: str = "",
|
||||
market: str = "",
|
||||
industry: str = "",
|
||||
area: str = "",
|
||||
watched_only: bool = False,
|
||||
held_only: bool = False,
|
||||
sort: str = "symbol",
|
||||
order: str = "asc",
|
||||
limit: int = 100,
|
||||
offset: int = 0,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> Response:
|
||||
"""全市场股票列表：stock_basic 基本信息 + candles 最新行情 + daily_snapshot 估值指标
|
||||
（换手率/PE-TTM/PB/市值，无快照则这些列为空）。
|
||||
watched_only=true 只看自选，held_only=true 只看持仓（各有独立分类入口，列表不再把它们排最前）。
|
||||
sort ∈ {symbol,total_mv,circ_mv,pe_ttm,pb,turnover_rate}（白名单，其他值回落 symbol），
|
||||
order ∈ asc/desc；快照列排序时缺失值（无快照/亏损无 PE）恒排末尾。
|
||||
缓存：按「用户自选/持仓版本 + 查询参数（含排序）」缓存整页（含 total）；自选/持仓增删即时失效；
|
||||
与 preview 同款序列化 JSON 直返（j 前缀），命中跳过 pydantic 校验/序列化。"""
|
||||
search = search.strip()
|
||||
sort = sort if sort in _STOCKS_SORTS else "symbol"
|
||||
order = "desc" if order.lower() == "desc" else "asc"
|
||||
limit = max(1, min(limit, 500))
|
||||
offset = max(0, offset)
|
||||
key = (
|
||||
f"stocksj:u{user.id}"
|
||||
f":v{await cache.get_version(f'watchlist:{user.id}')}"
|
||||
f":h{await cache.get_version(f'holding:{user.id}')}"
|
||||
f":{cache.digest(search, market, industry, area, watched_only, held_only, sort, order, limit, offset)}"
|
||||
)
|
||||
cached = await cached_json_response(key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
params = {
|
||||
"search": search,
|
||||
"psearch": f"%{search}%",
|
||||
"market": market,
|
||||
"industry": industry,
|
||||
"area": area,
|
||||
"watched_only": watched_only,
|
||||
"held_only": held_only,
|
||||
"uid": user.id,
|
||||
"limit": limit,
|
||||
"offset": offset,
|
||||
}
|
||||
total = (await session.execute(_STOCKS_COUNT_SQL, params)).scalar_one()
|
||||
rows = (await session.execute(_stocks_sql(sort, order), params)).mappings().all()
|
||||
resp = StockListResponse(total=total, items=[StockListItemOut(**r) for r in rows])
|
||||
raw = raw_json(resp)
|
||||
cache.local_set(key, raw, ttl=min(120, settings.stocks_cache_ttl))
|
||||
cache.set_bg(key, raw, ttl=settings.stocks_cache_ttl)
|
||||
return Response(content=raw, media_type="application/json")
|
||||
|
||||
|
||||
@router.get("/stocks/facets", response_model=StockFacetsResponse)
|
||||
async def stock_facets(session: AsyncSession = Depends(get_session)) -> Response:
|
||||
"""看股页筛选项：行业 / 地域（含数量，按数量降序）。stock_basic 很少变，长缓存。"""
|
||||
cached = await cached_json_response("facetsj:stocks")
|
||||
if cached is not None:
|
||||
return cached
|
||||
industries = (
|
||||
await session.execute(text("""
|
||||
SELECT industry AS name, count(*) AS n FROM stock_basic
|
||||
WHERE list_status = 'L' AND industry IS NOT NULL AND industry <> ''
|
||||
GROUP BY industry ORDER BY n DESC
|
||||
"""))
|
||||
).mappings().all()
|
||||
areas = (
|
||||
await session.execute(text("""
|
||||
SELECT area AS name, count(*) AS n FROM stock_basic
|
||||
WHERE list_status = 'L' AND area IS NOT NULL AND area <> ''
|
||||
GROUP BY area ORDER BY n DESC
|
||||
"""))
|
||||
).mappings().all()
|
||||
resp = StockFacetsResponse(
|
||||
industries=[FacetItemOut(name=r["name"], count=r["n"]) for r in industries],
|
||||
areas=[FacetItemOut(name=r["name"], count=r["n"]) for r in areas],
|
||||
)
|
||||
raw = raw_json(resp)
|
||||
cache.local_set("facetsj:stocks", raw, ttl=min(120, settings.facets_cache_ttl))
|
||||
cache.set_bg("facetsj:stocks", raw, ttl=settings.facets_cache_ttl)
|
||||
return Response(content=raw, media_type="application/json")
|
||||
|
||||
|
||||
@router.get("/stocks/{ts_code}/company", response_model=StockCompanyOut)
|
||||
async def stock_company_info(ts_code: str, session: AsyncSession = Depends(get_session)) -> StockCompanyOut:
|
||||
"""公司简介：库内有新鲜行直返；否则锁内单查 tushare（stock_company）并 upsert（行即缓存，
|
||||
30 天新鲜度，无此股写墓碑负缓存）。ETF 前置短路；确认无数据 404；tushare 失败且
|
||||
无旧行可降级时 503（有旧行则在数据层降级返回旧行）。"""
|
||||
code = ts_code.strip().upper()
|
||||
if "." not in code:
|
||||
code = to_ts_code(code) # 防御：兼容 6 位裸代码
|
||||
if is_etf_symbol(code):
|
||||
raise HTTPException(status_code=404, detail="ETF 无公司简介")
|
||||
try:
|
||||
row = await company_mod.get_company(session, code)
|
||||
except Exception:
|
||||
raise HTTPException(status_code=503, detail="tushare 公司简介拉取失败，请稍后重试")
|
||||
if row is None:
|
||||
raise HTTPException(status_code=404, detail=f"无公司信息: {code}")
|
||||
return StockCompanyOut(**row)
|
||||
|
||||
|
||||
@router.get("/stocks/{ts_code}/finance", response_model=StockFinanceOut)
|
||||
async def stock_finance_info(ts_code: str, session: AsyncSession = Depends(get_session)) -> StockFinanceOut:
|
||||
"""财务数据（近五年，按报告期倒序）：库内新鲜直返；否则锁内拉 tushare 四源
|
||||
（fina_indicator/income/balancesheet/cashflow）合并 upsert（7 天新鲜度，无数据写墓碑）。
|
||||
ETF 前置短路；确认无数据 404；tushare 四源全失败且无旧行可降级时 503。"""
|
||||
code = ts_code.strip().upper()
|
||||
if "." not in code:
|
||||
code = to_ts_code(code)
|
||||
if is_etf_symbol(code):
|
||||
raise HTTPException(status_code=404, detail="ETF 无财务数据")
|
||||
try:
|
||||
rows = await finance_mod.get_finance(session, code)
|
||||
except Exception:
|
||||
raise HTTPException(status_code=503, detail="tushare 财务数据拉取失败，请稍后重试")
|
||||
if not rows:
|
||||
raise HTTPException(status_code=404, detail=f"无财务数据: {code}")
|
||||
return StockFinanceOut(ts_code=code, records=rows)
|
||||
|
||||
|
||||
@router.get("/stocks/{ts_code}/dividends", response_model=StockDividendOut)
|
||||
async def stock_dividend_info(ts_code: str, session: AsyncSession = Depends(get_session)) -> StockDividendOut:
|
||||
"""分红送股（全历史，按分红年度倒序）：库内新鲜直返；否则锁内拉 tushare dividend
|
||||
全量替换（7 天新鲜度，无分红写墓碑，空列表是正常返回）。
|
||||
ETF 前置短路；tushare 失败且无旧行可降级时 503。"""
|
||||
code = ts_code.strip().upper()
|
||||
if "." not in code:
|
||||
code = to_ts_code(code)
|
||||
if is_etf_symbol(code):
|
||||
raise HTTPException(status_code=404, detail="ETF 无分红数据")
|
||||
try:
|
||||
rows = await dividend_mod.get_dividends(session, code)
|
||||
except Exception:
|
||||
raise HTTPException(status_code=503, detail="tushare 分红数据拉取失败，请稍后重试")
|
||||
return StockDividendOut(ts_code=code, records=rows)
|
||||
|
||||
|
||||
@router.get("/stocks/{ts_code}/reference/{kind}", response_model=StockReferenceOut)
|
||||
async def stock_reference_info(ts_code: str, kind: str, session: AsyncSession = Depends(get_session)) -> StockReferenceOut:
|
||||
"""参考数据（11 类，kind 白名单见 reference.REFERENCE_KINDS）：单股单分类 JSON 快照
|
||||
懒加载（7 天新鲜度，无数据写墓碑，空 records 是正常返回）。repurchase 为全市场
|
||||
按月回填的特殊管道：首次触发后台回填近 24 个月（本次可能返回空，稍后再看）。
|
||||
ETF 前置短路；未知 kind 404；tushare 失败且无旧行可降级时 503。"""
|
||||
code = ts_code.strip().upper()
|
||||
if "." not in code:
|
||||
code = to_ts_code(code)
|
||||
if is_etf_symbol(code):
|
||||
raise HTTPException(status_code=404, detail="ETF 无参考数据")
|
||||
if kind not in reference_mod.REFERENCE_KINDS:
|
||||
raise HTTPException(status_code=404, detail=f"未知参考数据分类: {kind}")
|
||||
try:
|
||||
rows = await reference_mod.get_reference(session, code, kind)
|
||||
except Exception:
|
||||
raise HTTPException(status_code=503, detail="tushare 参考数据拉取失败，请稍后重试")
|
||||
return StockReferenceOut(ts_code=code, kind=kind, records=rows)
|
||||
291
backend/app/api/user.py
Normal file
291
backend/app/api/user.py
Normal file
@@ -0,0 +1,291 @@
|
||||
"""用户数据路由：偏好 / 自选股 / 交割单（个人实盘买卖点）。"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
from fastapi import APIRouter, Depends, File, HTTPException, UploadFile
|
||||
from sqlalchemy import delete, select, text
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from .. import cache
|
||||
from ..auth import require_user
|
||||
from ..db import get_session
|
||||
from ..models import HoldingItem, StockBasic, UserPreference, UserTrade, WatchlistItem
|
||||
from ..schemas import (
|
||||
HoldingOp,
|
||||
PreferencesOut,
|
||||
PreferencesUpdate,
|
||||
TradesClearResponse,
|
||||
TradesImportResponse,
|
||||
UserTradeOut,
|
||||
WatchlistOp,
|
||||
)
|
||||
from ..trades import parse_statement
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
# ---------- 用户偏好 ----------
|
||||
@router.get("/preferences", response_model=PreferencesOut)
|
||||
async def get_preferences(
|
||||
session: AsyncSession = Depends(get_session), user=Depends(require_user)
|
||||
) -> PreferencesOut:
|
||||
prefs: dict[str, object] = {}
|
||||
rows = (
|
||||
await session.execute(select(UserPreference).where(UserPreference.user_id == user.id))
|
||||
).scalars().all()
|
||||
for r in rows:
|
||||
try:
|
||||
prefs[r.key] = json.loads(r.value_json)
|
||||
except Exception: # noqa: BLE001
|
||||
prefs[r.key] = None
|
||||
return PreferencesOut(prefs=prefs)
|
||||
|
||||
|
||||
@router.put("/preferences", response_model=PreferencesOut)
|
||||
async def put_preferences(
|
||||
req: PreferencesUpdate,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> PreferencesOut:
|
||||
"""部分更新：只覆盖出现的 key；值为 null 表示删除该 key。返回更新后的全量。"""
|
||||
for key, value in req.prefs.items():
|
||||
if not key or len(key) > 64:
|
||||
continue
|
||||
if value is None:
|
||||
await session.execute(
|
||||
text("DELETE FROM user_preferences WHERE user_id = :u AND key = :k"),
|
||||
{"u": user.id, "k": key},
|
||||
)
|
||||
continue
|
||||
existing = (
|
||||
await session.execute(
|
||||
select(UserPreference).where(
|
||||
UserPreference.user_id == user.id, UserPreference.key == key
|
||||
)
|
||||
)
|
||||
).scalars().first()
|
||||
vj = json.dumps(value, ensure_ascii=False)
|
||||
if existing:
|
||||
existing.value_json = vj
|
||||
else:
|
||||
session.add(UserPreference(user_id=user.id, key=key, value_json=vj))
|
||||
await session.commit()
|
||||
return await get_preferences(session=session, user=user)
|
||||
|
||||
|
||||
# ---------- 自选股 ----------
|
||||
@router.get("/watchlist", response_model=list[str])
|
||||
async def get_watchlist(
|
||||
session: AsyncSession = Depends(get_session), user=Depends(require_user)
|
||||
) -> list[str]:
|
||||
"""当前用户自选股 ts_code 列表（加入时间倒序）。"""
|
||||
rows = (
|
||||
await session.execute(
|
||||
select(WatchlistItem.ts_code)
|
||||
.where(WatchlistItem.user_id == user.id)
|
||||
.order_by(WatchlistItem.created_at.desc(), WatchlistItem.id.desc())
|
||||
)
|
||||
).scalars().all()
|
||||
return list(rows)
|
||||
|
||||
|
||||
@router.post("/watchlist", response_model=list[str])
|
||||
async def add_watchlist(
|
||||
req: WatchlistOp,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> list[str]:
|
||||
exists = (
|
||||
await session.execute(
|
||||
select(WatchlistItem.id).where(
|
||||
WatchlistItem.user_id == user.id, WatchlistItem.ts_code == req.ts_code
|
||||
)
|
||||
)
|
||||
).scalar_one_or_none()
|
||||
if exists is None:
|
||||
session.add(WatchlistItem(user_id=user.id, ts_code=req.ts_code))
|
||||
await session.commit()
|
||||
await cache.bump_version(f"watchlist:{user.id}") # 作废该用户的股票列表缓存
|
||||
return await get_watchlist(session=session, user=user)
|
||||
|
||||
|
||||
@router.delete("/watchlist/{ts_code}", response_model=list[str])
|
||||
async def remove_watchlist(
|
||||
ts_code: str,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> list[str]:
|
||||
await session.execute(
|
||||
text("DELETE FROM watchlist_items WHERE user_id = :u AND ts_code = :c"),
|
||||
{"u": user.id, "c": ts_code},
|
||||
)
|
||||
await session.commit()
|
||||
await cache.bump_version(f"watchlist:{user.id}") # 作废该用户的股票列表缓存
|
||||
return await get_watchlist(session=session, user=user)
|
||||
|
||||
|
||||
# ---------- 持仓股 ----------
|
||||
@router.get("/holdings", response_model=list[str])
|
||||
async def get_holdings(
|
||||
session: AsyncSession = Depends(get_session), user=Depends(require_user)
|
||||
) -> list[str]:
|
||||
"""当前用户持仓股 ts_code 列表（加入时间倒序）。"""
|
||||
rows = (
|
||||
await session.execute(
|
||||
select(HoldingItem.ts_code)
|
||||
.where(HoldingItem.user_id == user.id)
|
||||
.order_by(HoldingItem.created_at.desc(), HoldingItem.id.desc())
|
||||
)
|
||||
).scalars().all()
|
||||
return list(rows)
|
||||
|
||||
|
||||
@router.post("/holdings", response_model=list[str])
|
||||
async def add_holding(
|
||||
req: HoldingOp,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> list[str]:
|
||||
exists = (
|
||||
await session.execute(
|
||||
select(HoldingItem.id).where(
|
||||
HoldingItem.user_id == user.id, HoldingItem.ts_code == req.ts_code
|
||||
)
|
||||
)
|
||||
).scalar_one_or_none()
|
||||
if exists is None:
|
||||
session.add(HoldingItem(user_id=user.id, ts_code=req.ts_code))
|
||||
await session.commit()
|
||||
await cache.bump_version(f"holding:{user.id}") # 作废该用户的股票列表缓存
|
||||
return await get_holdings(session=session, user=user)
|
||||
|
||||
|
||||
@router.delete("/holdings/{ts_code}", response_model=list[str])
|
||||
async def remove_holding(
|
||||
ts_code: str,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> list[str]:
|
||||
await session.execute(
|
||||
text("DELETE FROM holding_items WHERE user_id = :u AND ts_code = :c"),
|
||||
{"u": user.id, "c": ts_code},
|
||||
)
|
||||
await session.commit()
|
||||
await cache.bump_version(f"holding:{user.id}") # 作废该用户的股票列表缓存
|
||||
return await get_holdings(session=session, user=user)
|
||||
|
||||
|
||||
# ---------- 交割单（个人实盘买卖点） ----------
|
||||
def _trade_out(r: UserTrade) -> UserTradeOut:
|
||||
return UserTradeOut(
|
||||
id=r.id, ts_code=r.ts_code, name=r.name, trade_date=r.trade_date,
|
||||
direction=r.direction, price=r.price, qty=r.qty, amount=r.amount, fee=r.fee,
|
||||
)
|
||||
|
||||
|
||||
@router.get("/trades", response_model=list[UserTradeOut])
|
||||
async def list_trades(
|
||||
ts_code: str | None = None,
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> list[UserTradeOut]:
|
||||
"""当前用户导入的实盘成交（可选 ts_code 过滤，按日期升序；K线买卖点数据源）。"""
|
||||
q = (
|
||||
select(UserTrade)
|
||||
.where(UserTrade.user_id == user.id)
|
||||
.order_by(UserTrade.trade_date, UserTrade.id)
|
||||
)
|
||||
if ts_code:
|
||||
q = q.where(UserTrade.ts_code == ts_code)
|
||||
rows = (await session.execute(q)).scalars().all()
|
||||
return [_trade_out(r) for r in rows]
|
||||
|
||||
|
||||
@router.post("/trades/import", response_model=TradesImportResponse)
|
||||
async def import_trades(
|
||||
file: UploadFile = File(...),
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> TradesImportResponse:
|
||||
"""上传券商交割单（CSV/Excel/HTML 表格均可，自动识别列名），解析出买卖成交入库。
|
||||
|
||||
同一笔成交（同日同股同向同价同量）重复上传会跳过，重复导出幂等。
|
||||
"""
|
||||
data = await file.read()
|
||||
if not data:
|
||||
raise HTTPException(status_code=422, detail="文件是空的")
|
||||
if len(data) > 20 * 1024 * 1024:
|
||||
raise HTTPException(status_code=413, detail="文件超过 20MB，请分时间段导出")
|
||||
|
||||
parsed = parse_statement(data, file.filename or "")
|
||||
|
||||
# 无证券代码列的导出（招商式）：按证券名称反查 stock_basic 补 ts_code；同名多码或查不到则弃行
|
||||
unnamed = {t.name for t in parsed.trades if not t.ts_code and t.name}
|
||||
if unnamed:
|
||||
name_map: dict[str, str] = {}
|
||||
for ts_code, name in (await session.execute(
|
||||
select(StockBasic.ts_code, StockBasic.name).where(StockBasic.name.in_(unnamed))
|
||||
)).all():
|
||||
name_map[name] = "" if name in name_map else ts_code
|
||||
for t in parsed.trades:
|
||||
if not t.ts_code and t.name:
|
||||
tc = name_map.get(t.name, "")
|
||||
if tc:
|
||||
t.ts_code, t.code = tc, tc.split(".")[0]
|
||||
else:
|
||||
parsed.skipped_bad.append(f"{t.trade_date} {t.name} 名称无法唯一对应代码，未入库")
|
||||
|
||||
def _key(t) -> tuple:
|
||||
return (t.trade_date, t.ts_code, t.direction, None if t.price is None else round(t.price, 4), round(t.qty, 4))
|
||||
|
||||
# Python 侧去重兜底（唯一约束对 NULL price 不生效）
|
||||
existing = {
|
||||
(r.trade_date, r.ts_code, r.direction, None if r.price is None else round(r.price, 4), round(r.qty, 4))
|
||||
for r in (
|
||||
await session.execute(
|
||||
select(UserTrade.trade_date, UserTrade.ts_code, UserTrade.direction, UserTrade.price, UserTrade.qty)
|
||||
.where(UserTrade.user_id == user.id, UserTrade.ts_code.in_({t.ts_code for t in parsed.trades}))
|
||||
)
|
||||
).all()
|
||||
}
|
||||
inserted: list[UserTrade] = []
|
||||
seen: set[tuple] = set()
|
||||
skipped_dup = 0
|
||||
for t in parsed.trades:
|
||||
if not t.ts_code:
|
||||
continue # 名称反查失败的行，已在 bad 里说明
|
||||
k = _key(t)
|
||||
if k in existing or k in seen:
|
||||
skipped_dup += 1
|
||||
continue
|
||||
seen.add(k)
|
||||
inserted.append(UserTrade(
|
||||
user_id=user.id, ts_code=t.ts_code, code=t.code, name=t.name or None,
|
||||
trade_date=t.trade_date, direction=t.direction, price=t.price,
|
||||
qty=t.qty, amount=t.amount, fee=t.fee,
|
||||
raw_json=json.dumps(t.raw, ensure_ascii=False, default=str),
|
||||
))
|
||||
if inserted:
|
||||
session.add_all(inserted)
|
||||
await session.commit()
|
||||
|
||||
return TradesImportResponse(
|
||||
inserted=len(inserted),
|
||||
skipped_dup=skipped_dup,
|
||||
skipped_other=parsed.skipped_other,
|
||||
stocks=len({t.ts_code for t in parsed.trades}),
|
||||
bad=parsed.skipped_bad[:5],
|
||||
sample=[_trade_out(r) for r in inserted[:5]],
|
||||
)
|
||||
|
||||
|
||||
@router.delete("/trades", response_model=TradesClearResponse)
|
||||
async def clear_trades(
|
||||
session: AsyncSession = Depends(get_session),
|
||||
user=Depends(require_user),
|
||||
) -> TradesClearResponse:
|
||||
"""清空当前用户导入的全部成交（重新导入前用）。"""
|
||||
res = await session.execute(delete(UserTrade).where(UserTrade.user_id == user.id))
|
||||
await session.commit()
|
||||
return TradesClearResponse(deleted=res.rowcount or 0)
|
||||
233
backend/app/data/limit_board.py
Normal file
233
backend/app/data/limit_board.py
Normal file
@@ -0,0 +1,233 @@
|
||||
"""首页打板专题（tushare 同花顺版：limit_list_ths / limit_step / limit_cpt_list）。
|
||||
|
||||
整包 SWR（仿 index_global 列表层）：进程内 state 新鲜直返 -> Redis 回填 ->
|
||||
有旧值先返 + 后台刷新 -> 冷启动同步拉。盘中（交易日 09:15-15:30）数据源即有
|
||||
当日快照（实测 quicksync 镜像盘中可取当日）-> fresh TTL 压到 5 分钟；其余时段 4 小时。
|
||||
|
||||
镜像坑（见 reference.py 注释）：不传 fields；limit_list_ths 必须显式传 trade_date
|
||||
（缺省返回多日混包且 4000 行封顶）；涨停/连扳池才有 tag/status/lu_desc/封单额，
|
||||
炸板池只有价格与打开次数，跌停池几乎只有价格——行模型统一、字段可选。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import math
|
||||
import time
|
||||
from datetime import date, datetime, timedelta
|
||||
|
||||
from .. import cache
|
||||
from ..config import settings
|
||||
from .sync_utils import call_retry, f_clean, get_pro_lazy, s_clean
|
||||
|
||||
_BOARD_KEY = "limit_board:daily:v1" # Redis 整包缓存键（v1 起版）
|
||||
_REDIS_TTL = 3600 # 进程重启后的回填来源
|
||||
_INTRADAY_TTL = 300.0 # 交易时段内的 fresh TTL（5 分钟准实时）
|
||||
_MAX_DATE_BACKTRACK = 5 # trade_date 定位回退天数（覆盖节假日/盘前）
|
||||
_BLOCKS_OUT = 12 # 最强板块输出条数
|
||||
|
||||
|
||||
class LimitBoardError(RuntimeError):
|
||||
"""三池全部拉不到（token/网络故障）——接口层转 503。"""
|
||||
|
||||
|
||||
def _yi(v) -> float | None:
|
||||
"""元 -> 亿元（2 位小数）。"""
|
||||
f = f_clean(v)
|
||||
return None if f is None else round(f / 1e8, 2)
|
||||
|
||||
|
||||
def _fetch_pool_sync(pro, trade_date: str, limit_type: str):
|
||||
time.sleep(settings.screener_sync_interval)
|
||||
return call_retry(pro.limit_list_ths, trade_date=trade_date, limit_type=limit_type)
|
||||
|
||||
|
||||
def _pool_rows(df, mode: str) -> list[dict]:
|
||||
"""行裁剪 + 单位换算。mode: up / broken / down。"""
|
||||
if df is None or df.empty:
|
||||
return []
|
||||
rows: list[dict] = []
|
||||
for _, r in df.iterrows():
|
||||
row = {
|
||||
"ts_code": s_clean(r.get("ts_code")),
|
||||
"name": s_clean(r.get("name")),
|
||||
"price": f_clean(r.get("price")),
|
||||
"pct_chg": f_clean(r.get("pct_chg")),
|
||||
}
|
||||
if not row["ts_code"]:
|
||||
continue
|
||||
if mode == "up":
|
||||
row.update({
|
||||
"tag": s_clean(r.get("tag")),
|
||||
"status": s_clean(r.get("status")),
|
||||
"lu_desc": s_clean(r.get("lu_desc")),
|
||||
"open_num": f_clean(r.get("open_num")),
|
||||
"limit_amount_yi": _yi(r.get("limit_amount")), # 封单额（亿）
|
||||
"turnover_yi": _yi(r.get("turnover")), # 成交额（亿）
|
||||
"first_lu_time": s_clean(r.get("first_lu_time")),
|
||||
"limit_up_suc_rate": f_clean(r.get("limit_up_suc_rate")),
|
||||
})
|
||||
elif mode == "broken":
|
||||
row.update({
|
||||
"open_num": f_clean(r.get("open_num")),
|
||||
"first_lu_time": s_clean(r.get("first_lu_time")),
|
||||
"last_lu_time": s_clean(r.get("last_lu_time")),
|
||||
})
|
||||
rows.append(row)
|
||||
if mode == "up":
|
||||
# 封单额降序（打板看封单强度）；封单额缺失（镜像个别行）沉底
|
||||
rows.sort(key=lambda x: (x.get("limit_amount_yi") is None, -(x.get("limit_amount_yi") or 0)))
|
||||
return rows
|
||||
|
||||
|
||||
def _fetch_board_sync() -> dict:
|
||||
"""定位交易日并拉三池 + 天梯 + 最强板块（同步网络 IO，需在 to_thread 里跑）。"""
|
||||
pro = get_pro_lazy()
|
||||
errors: list[str] = []
|
||||
|
||||
# trade_date 定位：今日起逐日回退，取第一个涨停池非空的日期
|
||||
# （盘前/节假日当日为空；tushare 错误直接抛——定位失败无意义继续）
|
||||
trade_date: str | None = None
|
||||
up_rows: list[dict] = []
|
||||
for i in range(_MAX_DATE_BACKTRACK):
|
||||
d = (date.today() - timedelta(days=i)).strftime("%Y%m%d")
|
||||
df = _fetch_pool_sync(pro, d, "涨停池")
|
||||
if df is not None and not df.empty:
|
||||
trade_date = d
|
||||
up_rows = _pool_rows(df, "up")
|
||||
break
|
||||
if trade_date is None:
|
||||
raise LimitBoardError(f"近 {_MAX_DATE_BACKTRACK} 天均无涨停池数据（节假日或数据源故障）")
|
||||
|
||||
broken_rows: list[dict] = []
|
||||
try:
|
||||
broken_rows = _pool_rows(_fetch_pool_sync(pro, trade_date, "炸板池"), "broken")
|
||||
except Exception as e: # noqa: BLE001 —— 单池失败不拖垮整包
|
||||
errors.append(f"炸板池: {str(e)[:60]}")
|
||||
|
||||
down_rows: list[dict] = []
|
||||
try:
|
||||
down_rows = _pool_rows(_fetch_pool_sync(pro, trade_date, "跌停池"), "down")
|
||||
except Exception as e: # noqa: BLE001
|
||||
errors.append(f"跌停池: {str(e)[:60]}")
|
||||
|
||||
ladder: list[dict] = []
|
||||
try:
|
||||
time.sleep(settings.screener_sync_interval)
|
||||
step = call_retry(pro.limit_step, trade_date=trade_date)
|
||||
if step is not None and not step.empty:
|
||||
for _, r in step.iterrows():
|
||||
code = s_clean(r.get("ts_code"))
|
||||
n = f_clean(r.get("nums"))
|
||||
if code and n:
|
||||
ladder.append({"ts_code": code, "name": s_clean(r.get("name")), "nums": int(n)})
|
||||
ladder.sort(key=lambda x: -x["nums"])
|
||||
except Exception as e: # noqa: BLE001
|
||||
errors.append(f"连板天梯: {str(e)[:60]}")
|
||||
|
||||
blocks: list[dict] = []
|
||||
try:
|
||||
time.sleep(settings.screener_sync_interval)
|
||||
cpt = call_retry(pro.limit_cpt_list, trade_date=trade_date)
|
||||
if cpt is not None and not cpt.empty:
|
||||
for _, r in cpt.head(_BLOCKS_OUT).iterrows():
|
||||
blocks.append({
|
||||
"name": s_clean(r.get("name")),
|
||||
"days": f_clean(r.get("days")),
|
||||
"up_stat": s_clean(r.get("up_stat")),
|
||||
"cons_nums": f_clean(r.get("cons_nums")),
|
||||
"up_nums": f_clean(r.get("up_nums")),
|
||||
"pct_chg": f_clean(r.get("pct_chg")),
|
||||
})
|
||||
except Exception as e: # noqa: BLE001
|
||||
errors.append(f"最强板块: {str(e)[:60]}")
|
||||
|
||||
# 连板分布（limit_step 只含 2 板及以上；1 板 = 涨停池 tag 首板数）
|
||||
dist: dict[int, int] = {}
|
||||
for x in ladder:
|
||||
dist[x["nums"]] = dist.get(x["nums"], 0) + 1
|
||||
summary = {
|
||||
"up_count": len(up_rows),
|
||||
"broken_count": len(broken_rows),
|
||||
"down_count": len(down_rows),
|
||||
"first_board_count": sum(1 for x in up_rows if x.get("tag") == "首板"),
|
||||
"max_ladder": ladder[0] if ladder else None,
|
||||
"ladder_dist": [{"nums": k, "count": v} for k, v in sorted(dist.items())],
|
||||
}
|
||||
return {
|
||||
"trade_date": f"{trade_date[:4]}-{trade_date[4:6]}-{trade_date[6:]}",
|
||||
"summary": summary,
|
||||
"up": up_rows,
|
||||
"broken": broken_rows,
|
||||
"down": down_rows,
|
||||
"ladder": ladder,
|
||||
"blocks": blocks,
|
||||
"errors": errors,
|
||||
}
|
||||
|
||||
|
||||
# ---------- 整包 SWR（进程内 -> Redis 回填 -> 旧值先返 + 后台刷新 -> 冷启动同步拉） ----------
|
||||
|
||||
_state: dict = {"payload": None}
|
||||
_refreshing = False
|
||||
_refresh_error: str | None = None
|
||||
_bg_tasks: set[asyncio.Task] = set()
|
||||
|
||||
|
||||
def _fresh_ttl(is_trading_day: bool | None) -> float:
|
||||
"""交易时段 5 分钟（镜像盘中即有当日快照）；其余 4 小时（盘后数据不变）。"""
|
||||
if is_trading_day is None:
|
||||
is_trading_day = datetime.now().weekday() < 5 # 判定失败回退 weekday 启发式
|
||||
if is_trading_day:
|
||||
now = datetime.now()
|
||||
t = now.hour * 60 + now.minute
|
||||
if 9 * 60 + 15 <= t <= 15 * 60 + 30:
|
||||
return _INTRADAY_TTL
|
||||
return float(settings.market_eod_fresh_ttl)
|
||||
|
||||
|
||||
async def _refresh() -> dict:
|
||||
data = await asyncio.to_thread(_fetch_board_sync)
|
||||
payload = {**data, "updated_at": datetime.now().isoformat(), "fetched_ts": time.time()}
|
||||
_state["payload"] = payload
|
||||
await cache.cache_set(_BOARD_KEY, payload, ttl=_REDIS_TTL)
|
||||
return payload
|
||||
|
||||
|
||||
async def _refresh_wrapped() -> None:
|
||||
global _refresh_error, _refreshing
|
||||
try:
|
||||
await _refresh()
|
||||
_refresh_error = None
|
||||
except Exception as e: # noqa: BLE001 —— 后台刷新失败静默记错，下次并入 errors
|
||||
_refresh_error = f"打板专题后台刷新: {str(e)[:60]}"
|
||||
finally:
|
||||
_refreshing = False
|
||||
|
||||
|
||||
def _spawn_refresh() -> None:
|
||||
global _refreshing
|
||||
if _refreshing:
|
||||
return
|
||||
_refreshing = True
|
||||
task = asyncio.create_task(_refresh_wrapped())
|
||||
_bg_tasks.add(task)
|
||||
task.add_done_callback(_bg_tasks.discard)
|
||||
|
||||
|
||||
async def fetch_limit_board(is_trading_day: bool | None) -> dict:
|
||||
"""打板专题整包读取（SWR）。冷启动同步拉（5 次调用约 2-4s）；此后盘中 5 分钟/盘后 4 小时。"""
|
||||
ttl = _fresh_ttl(is_trading_day)
|
||||
p = _state["payload"]
|
||||
if p is not None and time.time() - p["fetched_ts"] < ttl:
|
||||
return p
|
||||
if p is None:
|
||||
cached = await cache.cache_get(_BOARD_KEY)
|
||||
if cached:
|
||||
p = cached
|
||||
_state["payload"] = p
|
||||
if p is not None:
|
||||
_spawn_refresh()
|
||||
if _refresh_error and not p.get("errors"):
|
||||
p = {**p, "errors": [_refresh_error]}
|
||||
return p
|
||||
return await _refresh()
|
||||
242
backend/app/data/ths_board.py
Normal file
242
backend/app/data/ths_board.py
Normal file
@@ -0,0 +1,242 @@
|
||||
"""同花顺概念/行业板块（ths_index 列表 + ths_daily 行情快照 + ths_member 成分）。
|
||||
|
||||
缓存分层（数据特性决定）：
|
||||
- 板块列表：一天不变 -> 直缓存（进程内 -> Redis 24h）
|
||||
- 行情快照：ths_daily 盘中即有当日（实测镜像），全市场一日 1877 行单次拿全
|
||||
-> 整包 SWR（同 limit_board：盘中 5 分钟 / 盘后 4 小时，trade_date 回退定位）
|
||||
- 成分：每板块懒加载直缓存 24h；成分股行情 enrich（candles 最新+前收 LATERAL）
|
||||
每次请求现算，不进缓存
|
||||
|
||||
type 代码：N 概念 / I 行业 / TH 主题 / S 特色 / R 地域 / BB 宽基 / ST 风格。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import time
|
||||
from datetime import date, datetime, timedelta
|
||||
|
||||
from sqlalchemy import text
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from .. import cache
|
||||
from ..config import settings
|
||||
from .sync_utils import call_retry, f_clean, get_pro_lazy, s_clean
|
||||
|
||||
_LIST_KEY = "ths_boards:list:v1"
|
||||
_DAILY_KEY = "ths_boards:daily:v1"
|
||||
_REDIS_TTL = 3600
|
||||
_LIST_TTL = 86400
|
||||
_INTRADAY_TTL = 300.0
|
||||
_MAX_DATE_BACKTRACK = 5
|
||||
|
||||
|
||||
class ThsBoardError(RuntimeError):
|
||||
"""列表/行情全部拉不到 —— 接口层转 503。"""
|
||||
|
||||
|
||||
# ---------- 板块列表（直缓存：进程内 -> Redis 24h -> 拉取） ----------
|
||||
|
||||
_list_cache: list[dict] | None = None
|
||||
|
||||
|
||||
def _fetch_list_sync() -> list[dict]:
|
||||
time.sleep(settings.screener_sync_interval)
|
||||
df = call_retry(get_pro_lazy().ths_index, exchange="A")
|
||||
if df is None or df.empty:
|
||||
raise ThsBoardError("ths_index 板块列表为空")
|
||||
rows: list[dict] = []
|
||||
for _, r in df.iterrows():
|
||||
code = s_clean(r.get("ts_code"))
|
||||
if not code:
|
||||
continue
|
||||
rows.append({
|
||||
"ts_code": code,
|
||||
"name": s_clean(r.get("name")),
|
||||
"type": s_clean(r.get("type")),
|
||||
"count": f_clean(r.get("count")),
|
||||
"list_date": s_clean(r.get("list_date")),
|
||||
})
|
||||
return rows
|
||||
|
||||
|
||||
async def get_board_list() -> list[dict]:
|
||||
global _list_cache
|
||||
if _list_cache is not None:
|
||||
return _list_cache
|
||||
cached = await cache.cache_get(_LIST_KEY)
|
||||
if isinstance(cached, list) and cached:
|
||||
_list_cache = cached
|
||||
return cached
|
||||
rows = await asyncio.to_thread(_fetch_list_sync)
|
||||
_list_cache = rows
|
||||
await cache.cache_set(_LIST_KEY, rows, ttl=_LIST_TTL)
|
||||
return rows
|
||||
|
||||
|
||||
# ---------- 行情快照（整包 SWR，同 limit_board.py 三件套） ----------
|
||||
|
||||
_daily_state: dict = {"payload": None}
|
||||
_daily_refreshing = False
|
||||
_daily_refresh_error: str | None = None
|
||||
_bg_tasks: set[asyncio.Task] = set()
|
||||
|
||||
|
||||
def _fresh_ttl(is_trading_day: bool | None) -> float:
|
||||
"""交易时段 5 分钟（镜像盘中即有当日快照）；其余 4 小时。"""
|
||||
if is_trading_day is None:
|
||||
is_trading_day = datetime.now().weekday() < 5
|
||||
if is_trading_day:
|
||||
now = datetime.now()
|
||||
t = now.hour * 60 + now.minute
|
||||
if 9 * 60 + 15 <= t <= 15 * 60 + 30:
|
||||
return _INTRADAY_TTL
|
||||
return float(settings.market_eod_fresh_ttl)
|
||||
|
||||
|
||||
def _fetch_daily_sync() -> dict:
|
||||
pro = get_pro_lazy()
|
||||
for i in range(_MAX_DATE_BACKTRACK):
|
||||
d = (date.today() - timedelta(days=i)).strftime("%Y%m%d")
|
||||
time.sleep(settings.screener_sync_interval)
|
||||
df = call_retry(pro.ths_daily, trade_date=d)
|
||||
if df is None or df.empty:
|
||||
continue
|
||||
quotes: dict[str, dict] = {}
|
||||
for _, r in df.iterrows():
|
||||
code = s_clean(r.get("ts_code"))
|
||||
if code:
|
||||
quotes[code] = {
|
||||
"close": f_clean(r.get("close")),
|
||||
"pct_change": f_clean(r.get("pct_change")),
|
||||
"vol": f_clean(r.get("vol")),
|
||||
"turnover_rate": f_clean(r.get("turnover_rate")),
|
||||
}
|
||||
return {"trade_date": f"{d[:4]}-{d[4:6]}-{d[6:]}", "quotes": quotes}
|
||||
raise ThsBoardError(f"近 {_MAX_DATE_BACKTRACK} 天均无 ths_daily 板块行情")
|
||||
|
||||
|
||||
async def _refresh_daily() -> dict:
|
||||
data = await asyncio.to_thread(_fetch_daily_sync)
|
||||
payload = {**data, "updated_at": datetime.now().isoformat(), "fetched_ts": time.time()}
|
||||
_daily_state["payload"] = payload
|
||||
await cache.cache_set(_DAILY_KEY, payload, ttl=_REDIS_TTL)
|
||||
return payload
|
||||
|
||||
|
||||
async def _refresh_daily_wrapped() -> None:
|
||||
global _daily_refresh_error, _daily_refreshing
|
||||
try:
|
||||
await _refresh_daily()
|
||||
_daily_refresh_error = None
|
||||
except Exception as e: # noqa: BLE001
|
||||
_daily_refresh_error = f"板块行情后台刷新: {str(e)[:60]}"
|
||||
finally:
|
||||
_daily_refreshing = False
|
||||
|
||||
|
||||
def _spawn_daily_refresh() -> None:
|
||||
global _daily_refreshing
|
||||
if _daily_refreshing:
|
||||
return
|
||||
_daily_refreshing = True
|
||||
task = asyncio.create_task(_refresh_daily_wrapped())
|
||||
_bg_tasks.add(task)
|
||||
task.add_done_callback(_bg_tasks.discard)
|
||||
|
||||
|
||||
async def _get_daily(is_trading_day: bool | None) -> dict:
|
||||
ttl = _fresh_ttl(is_trading_day)
|
||||
p = _daily_state["payload"]
|
||||
if p is not None and time.time() - p["fetched_ts"] < ttl:
|
||||
return p
|
||||
if p is None:
|
||||
cached = await cache.cache_get(_DAILY_KEY)
|
||||
if cached:
|
||||
p = cached
|
||||
_daily_state["payload"] = p
|
||||
if p is not None:
|
||||
_spawn_daily_refresh()
|
||||
return p
|
||||
return await _refresh_daily()
|
||||
|
||||
|
||||
async def fetch_boards(is_trading_day: bool | None) -> dict:
|
||||
"""列表 + 当日行情合并（行情缺失的板块价格为 null）。"""
|
||||
boards, daily = await asyncio.gather(get_board_list(), _get_daily(is_trading_day))
|
||||
quotes: dict = daily.get("quotes", {})
|
||||
merged = [{**b, **quotes.get(b["ts_code"], {})} for b in boards]
|
||||
errors = [_daily_refresh_error] if _daily_refresh_error else []
|
||||
return {
|
||||
"trade_date": daily.get("trade_date"),
|
||||
"updated_at": daily.get("updated_at"),
|
||||
"boards": merged,
|
||||
"errors": errors,
|
||||
}
|
||||
|
||||
|
||||
# ---------- 成分（每板块懒加载直缓存 24h + 行情 enrich 现算） ----------
|
||||
|
||||
_member_cache: dict[str, list[dict]] = {}
|
||||
|
||||
|
||||
def _fetch_members_sync(board_code: str) -> list[dict]:
|
||||
time.sleep(settings.screener_sync_interval)
|
||||
df = call_retry(get_pro_lazy().ths_member, ts_code=board_code)
|
||||
if df is None or df.empty:
|
||||
return []
|
||||
rows: list[dict] = []
|
||||
for _, r in df.iterrows():
|
||||
code = s_clean(r.get("con_code"))
|
||||
if code:
|
||||
rows.append({"con_code": code, "con_name": s_clean(r.get("con_name"))})
|
||||
rows.sort(key=lambda x: x["con_code"])
|
||||
return rows
|
||||
|
||||
|
||||
async def get_raw_members(board_code: str) -> list[dict]:
|
||||
hit = _member_cache.get(board_code)
|
||||
if hit is not None:
|
||||
return hit
|
||||
key = f"ths_members:{board_code}"
|
||||
cached = await cache.cache_get(key)
|
||||
if isinstance(cached, list):
|
||||
_member_cache[board_code] = cached
|
||||
return cached
|
||||
rows = await asyncio.to_thread(_fetch_members_sync, board_code)
|
||||
_member_cache[board_code] = rows
|
||||
await cache.cache_set(key, rows, ttl=_LIST_TTL)
|
||||
return rows
|
||||
|
||||
|
||||
# 成分股行情：candles 最新价 + 前收算涨跌幅（北交所等无底座数据的为 NULL）
|
||||
_MEMBERS_ENRICH_SQL = text("""
|
||||
SELECT m.code AS con_code,
|
||||
c.close AS close,
|
||||
CASE WHEN c.close IS NOT NULL AND prev.close IS NOT NULL AND prev.close <> 0
|
||||
THEN round(((c.close / prev.close - 1) * 100)::numeric, 2) END AS pct_chg
|
||||
FROM (SELECT unnest(CAST(:codes AS text[])) AS code) m
|
||||
LEFT JOIN LATERAL (
|
||||
SELECT close, ts FROM candles
|
||||
WHERE symbol = split_part(m.code, '.', 1) AND timeframe = '1d'
|
||||
ORDER BY ts DESC LIMIT 1
|
||||
) c ON true
|
||||
LEFT JOIN LATERAL (
|
||||
SELECT close FROM candles
|
||||
WHERE symbol = split_part(m.code, '.', 1) AND timeframe = '1d' AND ts < c.ts
|
||||
ORDER BY ts DESC LIMIT 1
|
||||
) prev ON c.ts IS NOT NULL
|
||||
""")
|
||||
|
||||
|
||||
async def get_members(session: AsyncSession, board_code: str) -> list[dict]:
|
||||
"""成分 + 现价/涨跌幅（行情不缓存，每请求现算）。"""
|
||||
members = await get_raw_members(board_code)
|
||||
if not members:
|
||||
return []
|
||||
rows = (await session.execute(_MEMBERS_ENRICH_SQL, {
|
||||
"codes": [m["con_code"] for m in members],
|
||||
})).mappings().all()
|
||||
quote = {r["con_code"]: {"close": float(r["close"]) if r["close"] is not None else None,
|
||||
"pct_chg": float(r["pct_chg"]) if r["pct_chg"] is not None else None}
|
||||
for r in rows}
|
||||
return [{**m, **quote.get(m["con_code"], {"close": None, "pct_chg": None})} for m in members]
|
||||
@@ -312,6 +312,20 @@ class WatchlistItem(Base):
|
||||
)
|
||||
|
||||
|
||||
class HoldingItem(Base):
|
||||
"""持仓股（手动标记进「持仓」分类的股票）。"""
|
||||
__tablename__ = "holding_items"
|
||||
|
||||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||||
user_id: Mapped[int] = mapped_column(BigInteger, ForeignKey("users.id", ondelete="CASCADE"), index=True)
|
||||
ts_code: Mapped[str] = mapped_column(String(12), index=True)
|
||||
created_at: Mapped[datetime] = mapped_column(DateTime, default=_utcnow)
|
||||
|
||||
__table_args__ = (
|
||||
UniqueConstraint("user_id", "ts_code", name="uq_holding_user_code"),
|
||||
)
|
||||
|
||||
|
||||
class UserTrade(Base):
|
||||
"""交割单导入的实盘成交流水（K线买卖点的数据源，价格为券商成交原始价、不复权）。"""
|
||||
__tablename__ = "user_trades"
|
||||
|
||||
114
backend/app/scheduler.py
Normal file
114
backend/app/scheduler.py
Normal file
@@ -0,0 +1,114 @@
|
||||
"""夜间定时任务：收盘后自动全市场同步（A股 + ETF）+ 过期会话清理。
|
||||
|
||||
进程内 asyncio 循环（单进程部署假设）。start_sync 均幂等（已在跑直接返回），
|
||||
即使多 worker / 手动触发与定时撞车也不会重复跑。关闭：NIGHTLY_SYNC_ENABLED=false。
|
||||
|
||||
补跑语义：进程启动时若已过触发点、今天是交易日、且当日 candles 尚未落库
|
||||
（例如定时点机器没开机），立即补跑一次，不让数据断档等到第二天。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
from sqlalchemy import delete, func, or_, select
|
||||
|
||||
from .auth import utcnow
|
||||
from .config import settings
|
||||
from .models import AuthSession, Candle, TradeCalendar
|
||||
|
||||
log = logging.getLogger(__name__)
|
||||
|
||||
_TRIGGER_MINUTE = 5 # 触发点 = nightly_sync_hour:05（避开整点拥挤，纯本地任务习惯）
|
||||
|
||||
|
||||
def _seconds_until_next_run() -> float:
|
||||
now = datetime.now()
|
||||
target = now.replace(hour=settings.nightly_sync_hour, minute=_TRIGGER_MINUTE,
|
||||
second=0, microsecond=0)
|
||||
if target <= now:
|
||||
target += timedelta(days=1)
|
||||
return (target - now).total_seconds()
|
||||
|
||||
|
||||
async def cleanup_sessions() -> int:
|
||||
"""删除过期 / 吊销超 7 天的会话行（登录路径只清本人，长跑进程需要兜底）。"""
|
||||
from .db import async_session # 延迟导入避免循环
|
||||
|
||||
now = utcnow()
|
||||
async with async_session() as s:
|
||||
res = await s.execute(delete(AuthSession).where(or_(
|
||||
AuthSession.expires_at < now,
|
||||
AuthSession.revoked_at.is_not(None) & (AuthSession.revoked_at < now - timedelta(days=7)),
|
||||
)))
|
||||
await s.commit()
|
||||
return res.rowcount or 0
|
||||
|
||||
|
||||
async def _nightly_routine() -> None:
|
||||
"""当日例行：A 股全市场同步 -> ETF 同步（先后跑，避免两路 tushare 控频挤兑）-> 会话清理。"""
|
||||
from .data import etf_sync
|
||||
from .db import async_session
|
||||
from .screener import market_sync
|
||||
|
||||
log.info("夜间任务开始：全市场同步窗口 %d 个交易日", settings.screener_market_days)
|
||||
try:
|
||||
async with async_session() as session:
|
||||
await market_sync.start_sync(session, days=settings.screener_market_days, force=False)
|
||||
# 等日线同步收尾再触发 ETF（轮询模块内状态；start_sync 是即发即忘的）
|
||||
while market_sync._sync_state["running"]:
|
||||
await asyncio.sleep(30)
|
||||
except Exception: # noqa: BLE001
|
||||
log.exception("夜间 A 股同步触发失败")
|
||||
try:
|
||||
await etf_sync.start_sync(full=False)
|
||||
except Exception: # noqa: BLE001
|
||||
log.exception("夜间 ETF 同步触发失败")
|
||||
try:
|
||||
n = await cleanup_sessions()
|
||||
if n:
|
||||
log.info("夜间会话清理：%d 行", n)
|
||||
except Exception: # noqa: BLE001
|
||||
log.exception("夜间会话清理失败")
|
||||
log.info("夜间任务结束")
|
||||
|
||||
|
||||
async def _should_run_on_startup() -> bool:
|
||||
"""启动补跑判定：已过触发点 + 今天是交易日 + 当日 candles 还没落库。"""
|
||||
now = datetime.now()
|
||||
if now.hour * 60 + now.minute < settings.nightly_sync_hour * 60 + _TRIGGER_MINUTE:
|
||||
return False
|
||||
today8 = now.strftime("%Y%m%d")
|
||||
from .db import async_session
|
||||
|
||||
async with async_session() as s:
|
||||
is_trade_day = bool(await s.scalar(
|
||||
select(TradeCalendar.id).where(TradeCalendar.trade_date == today8).limit(1)))
|
||||
if not is_trade_day:
|
||||
return False
|
||||
# 当日未收盘/数据未生成时 max(ts) < 今日，同步会拉到空——那正是要补跑的信号
|
||||
latest = await s.scalar(select(func.max(Candle.ts)).where(Candle.timeframe == "1d"))
|
||||
return latest is None or latest.strftime("%Y%m%d") < today8
|
||||
|
||||
|
||||
async def run_nightly_loop() -> None:
|
||||
"""每日触发点跑一次；启动时满足补跑条件先补跑。由 main.lifespan 拉起。"""
|
||||
if not settings.nightly_sync_enabled:
|
||||
log.info("夜间自动同步未启用（NIGHTLY_SYNC_ENABLED=false）")
|
||||
return
|
||||
try:
|
||||
if await _should_run_on_startup():
|
||||
log.info("启动补跑：已过 %02d:%02d 且当日数据未落库", settings.nightly_sync_hour, _TRIGGER_MINUTE)
|
||||
await _nightly_routine()
|
||||
except Exception: # noqa: BLE001
|
||||
log.exception("启动补跑判定失败（跳过，等待每日定时点）")
|
||||
while True:
|
||||
try:
|
||||
await asyncio.sleep(_seconds_until_next_run())
|
||||
await _nightly_routine()
|
||||
except asyncio.CancelledError:
|
||||
raise
|
||||
except Exception: # noqa: BLE001 —— 循环体不能死
|
||||
log.exception("夜间任务循环异常，60s 后继续")
|
||||
await asyncio.sleep(60)
|
||||
@@ -474,6 +474,7 @@ class StockListItemOut(BaseModel):
|
||||
total_mv: float | None = None # 总市值（亿元）
|
||||
circ_mv: float | None = None # 流通市值（亿元）
|
||||
watched: bool = False # 是否自选（当前用户）
|
||||
held: bool = False # 是否持仓（当前用户）
|
||||
|
||||
|
||||
class StockListResponse(BaseModel):
|
||||
@@ -544,6 +545,10 @@ class WatchlistOp(BaseModel):
|
||||
ts_code: str = Field(min_length=6, max_length=12)
|
||||
|
||||
|
||||
class HoldingOp(BaseModel):
|
||||
ts_code: str = Field(min_length=6, max_length=12)
|
||||
|
||||
|
||||
class ScreenerQueryOut(BaseModel):
|
||||
id: int
|
||||
text: str
|
||||
|
||||
Reference in New Issue
Block a user