看股功能更新
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@@ -17,7 +17,7 @@ from datetime import datetime
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import pandas as pd
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from fastapi import APIRouter, Depends, File, HTTPException, UploadFile
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from sqlalchemy import delete, select, text
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from sqlalchemy import delete, func, select, 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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@@ -38,8 +38,8 @@ from .trades import parse_statement
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from .models import (
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AdjFactor,
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BacktestRun,
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Candle,
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DailySnapshot,
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MarketDaily,
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ScreenerQuery,
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StockBasic,
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UserPreference,
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@@ -780,11 +780,11 @@ async def screener_sync_status(session: AsyncSession = Depends(get_session)) ->
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@router.get("/screener/preview/{ts_code}", response_model=PreviewResponse)
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async def screener_preview(
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ts_code: str, limit: int = 500, adjust: str = "qfq", timeframe: str = "1d", mas: str = "5,10,20,60",
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end: str | None = None,
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zx: str = "10,20,30,60", end: str | None = None,
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session: AsyncSession = Depends(get_session),
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) -> PreviewResponse:
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"""个股详情预览：日线（candles 不复权底座 + adj_factor 本地换算 bfq/qfq/hfq，
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未缓存自动拉取，失败退 market_daily 近段）+ 全套指标 + 最新截面信息卡。
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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。
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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）。
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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），
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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。"""
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@@ -798,6 +798,12 @@ async def screener_preview(
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raise HTTPException(status_code=400, detail="mas 格式应为逗号分隔的数字，如 5,10,20,60")
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if not ma_periods:
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ma_periods = [5, 10, 20, 60]
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try:
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zx_periods = sorted({int(p) for p in zx.split(",") if p.strip().isdigit() and 1 <= int(p) <= 500})
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except ValueError:
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raise HTTPException(status_code=400, detail="zx 格式应为逗号分隔的数字，如 10,20,30,60")
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if not zx_periods:
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zx_periods = [10, 20, 30, 60]
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limit = max(30, min(limit, 5000))
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end_dt: datetime | None = None
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if end:
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@@ -807,20 +813,27 @@ async def screener_preview(
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raise HTTPException(status_code=400, detail="end 格式应为 YYYY-MM-DD")
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symbol = plain_code(ts_code)
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# 先取 market_daily 最新行：既做缓存过期判断，也做信息卡数据源
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md = (
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await session.execute(
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select(MarketDaily).where(MarketDaily.ts_code == ts_code).order_by(MarketDaily.trade_date.desc()).limit(1)
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)
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).scalars().first()
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# --- Redis 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；
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# 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）---
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cache_key = cache.digest(
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"preview", ts_code, timeframe, limit, adjust,
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end_dt.strftime("%Y-%m-%d") if end_dt else None, ma_periods, zx_periods,
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await cache.get_version("candles"),
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)
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cached = await cache.cache_get(f"pv:{cache_key}")
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if cached is not None:
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return PreviewResponse.model_validate(cached)
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# --- 日线：candles(不复权底座) 优先；未缓存拉取，缓存落后于全市场最新交易日则强制刷新（每日至多一次） ---
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# fetcher 现在只做「不复权」增量 upsert，底座口径恒为 bfq（TDX 全量 + Tushare 增量），
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# 复权（qfq/hfq）读取时按 adj_factor 表本地换算，mode 无需再推断。
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# 每次只取「窗口 + 800 根预热」行（MA250/MACD EMA 在 800 根内充分收敛），不拉全量：
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# --- 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 ---
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# fetcher 只做「不复权」增量 upsert，底座口径恒为 bfq（TDX 全量 + Tushare 增量），
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# 复权（qfq/hfq）读取时按 adj_factor 表本地换算。
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# 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：
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# 首屏 ~500 根秒开，向左滚动时按 end 参数逐页向前翻。
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global_latest = await session.scalar(
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select(func.max(Candle.ts)).where(Candle.timeframe == "1d")
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)
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frame_mult = {"1d": 1, "1w": 6, "1M": 24, "1y": 280}[timeframe]
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fetch_n = min(100000, limit * frame_mult + 800)
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fetch_n = min(100000, limit * frame_mult + 400)
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source = "bfq"
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mode = "bfq"
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if end_dt is not None:
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@@ -833,7 +846,7 @@ async def screener_preview(
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if not rows:
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await fetcher.sync_symbol(session, symbol, source="auto")
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rows = await repository.get_recent_candles(session, symbol, "1d", limit=fetch_n)
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elif md is not None and rows and rows[-1].ts.date() < md.trade_date.date():
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elif global_latest is not None and rows[-1].ts.date() < global_latest.date():
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await fetcher.sync_symbol(session, symbol, source="auto", force=True)
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rows = await repository.get_recent_candles(session, symbol, "1d", limit=fetch_n)
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except Exception: # noqa: BLE001 —— tushare/写库失败时回滚会话（否则毒化后兜底查询 500）
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@@ -842,34 +855,33 @@ async def screener_preview(
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rows = []
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bars = _rows_to_bars(rows)
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if not bars and end_dt is None:
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source = "market"
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res = await session.execute(
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select(MarketDaily).where(MarketDaily.ts_code == ts_code).order_by(MarketDaily.trade_date)
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)
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bars = [
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Bar(
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ts=r.trade_date, open=r.open, high=r.high, low=r.low, close=r.close,
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volume=r.vol * 100.0, amount=r.amount * 1000.0 if r.amount else None, # 千元 -> 元
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)
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for r in res.scalars()
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]
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if not bars and end_dt is None:
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raise HTTPException(status_code=404, detail=f"无数据: {ts_code}（可先点「同步市场数据」）")
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# 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」）
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last_daily = bars[-1] if bars else None
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prev_daily = bars[-2] if len(bars) > 1 else None
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# 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
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# --- 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） ---
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if adjust != mode:
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factors = (
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await session.execute(
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select(AdjFactor).where(AdjFactor.ts_code == ts_code).order_by(AdjFactor.trade_date)
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)
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).scalars().all()
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# 只取窗口内因子（qfq 归一还需全局最新因子，追加到最后一行即可，_adjust_bars 取 f_latest=末项）
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if adjust != mode and bars:
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fq = select(AdjFactor).where(AdjFactor.ts_code == ts_code)
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window_end = end_dt if end_dt is not None else bars[-1].ts
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if window_end is not None:
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fq = fq.where(AdjFactor.trade_date <= window_end)
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factors = list((await session.execute(fq.order_by(AdjFactor.trade_date))).scalars().all())
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if factors:
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latest_f = (
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await session.execute(
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select(AdjFactor).where(AdjFactor.ts_code == ts_code)
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.order_by(AdjFactor.trade_date.desc()).limit(1)
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)
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).scalars().first()
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if latest_f is not None:
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factors.append(latest_f)
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bars = _adjust_bars(bars, factors, mode, adjust)
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mode = adjust
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if source != "market":
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source = adjust
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source = adjust
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# --- 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 ---
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bars = resample_bars(bars, timeframe)
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@@ -897,21 +909,25 @@ async def screener_preview(
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"rsi24": _series_to_jsonable(ind.rsi(closes, 24)),
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},
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"boll": {k: _series_to_jsonable(boll[k]) for k in ("upper", "mid", "lower")},
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"zx": {
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"short": _series_to_jsonable(ind.ema2(closes)),
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"duokong": _series_to_jsonable(ind.avg_ma(closes, tuple(zx_periods))),
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},
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}
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limit = max(30, min(limit, len(bars)))
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for group in indicators.values():
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for key in group:
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group[key] = group[key][-limit:]
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# --- 信息卡：stock_basic + 最新 market_daily + 与其对齐的快照（避免混用不同交易日） ---
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# --- 信息卡：stock_basic + candles 最新日线 bar + 与其对齐的快照（避免混用不同交易日） ---
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sb = (await session.execute(select(StockBasic).where(StockBasic.ts_code == ts_code))).scalars().first()
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ds = None
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if md is not None:
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if last_daily is not None:
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# 优先取与行情同日的快照；缺当日快照时退最新（字段可能与行情差日期，罕见）
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ds = (
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await session.execute(
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select(DailySnapshot).where(
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DailySnapshot.ts_code == ts_code, DailySnapshot.trade_date == md.trade_date
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DailySnapshot.ts_code == ts_code, DailySnapshot.trade_date == last_daily.ts
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)
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)
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).scalars().first()
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@@ -936,15 +952,16 @@ async def screener_preview(
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area=sb.area if sb else None,
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market=sb.market if sb else None,
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list_date=sb.list_date if sb else None,
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trade_date=md.trade_date if md else None,
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open=md.open if md else None,
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high=md.high if md else None,
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low=md.low if md else None,
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close=md.close if md else None,
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pre_close=md.pre_close if md else None,
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pct_chg=md.pct_chg if md else None,
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volume_hand=round(md.vol, 0) if md else None,
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amount_yi=round(md.amount / 100000, 2) if md else None, # 千元 -> 亿元
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trade_date=last_daily.ts if last_daily else None,
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open=last_daily.open if last_daily else None,
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high=last_daily.high if last_daily else None,
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low=last_daily.low if last_daily else None,
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close=last_daily.close if last_daily else None,
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pre_close=prev_daily.close if prev_daily else None,
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pct_chg=((last_daily.close / prev_daily.close - 1) * 100)
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if last_daily and prev_daily and prev_daily.close else None,
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volume_hand=round(last_daily.volume / 100, 0) if last_daily else None, # 股 -> 手
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amount_yi=round(last_daily.amount / 1e8, 2) if last_daily and last_daily.amount else None, # 元 -> 亿元
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turnover_rate=ds.turnover_rate if ds else None,
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pe_ttm=ds.pe_ttm if ds else None,
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pb=ds.pb if ds else None,
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@@ -957,4 +974,7 @@ async def screener_preview(
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volume=b.volume, amount=b.amount, turnover=b.turnover)
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for b in bars[-limit:]
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]
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return PreviewResponse(ts_code=ts_code, symbol=symbol, source=source, info=info, candles=candles, indicators=indicators, has_more=has_more)
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resp = PreviewResponse(ts_code=ts_code, symbol=symbol, source=source, info=info,
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candles=candles, indicators=indicators, has_more=has_more)
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await cache.cache_set(f"pv:{cache_key}", resp.model_dump(mode="json"), ttl=600)
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return resp
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