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看股功能更新

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cirry
2026-08-15 15:36:11 +08:00
parent c1c43d2ff7
commit 9cce670b74
26 changed files with 957 additions and 427 deletions
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135
backend/app/api.py
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@@ -12,6 +12,7 @@ from __future__ import annotations
import bisect
import json
from datetime import datetime
import pandas as pd
from fastapi import APIRouter, Depends, HTTPException
@@ -86,7 +87,13 @@ def _series_to_jsonable(s: pd.Series) -> list[float | None]:
def _rows_to_bars(rows) -> list[Bar]:
return [Bar(ts=r.ts, open=r.open, high=r.high, low=r.low, close=r.close, volume=r.volume) for r in rows]
return [
Bar(
ts=r.ts, open=r.open, high=r.high, low=r.low, close=r.close, volume=r.volume,
amount=getattr(r, "amount", None), turnover=getattr(r, "turnover", None),
)
for r in rows
]
_ADJUST_MODES = ("bfq", "qfq", "hfq")
@@ -120,6 +127,8 @@ def _adjust_bars(bars: list[Bar], factors, from_mode: str, to_mode: str) -> list
open=round(b.open * m, 3), high=round(b.high * m, 3),
low=round(b.low * m, 3), close=round(b.close * m, 3),
volume=b.volume,
# 成交额/换手率是名义量，不随复权缩放
amount=b.amount, turnover=b.turnover,
))
return out
@@ -131,10 +140,14 @@ async def get_candles(
limit: int = 5000,
session: AsyncSession = Depends(get_session),
) -> list[CandleOut]:
# 始终以日线为基底，再聚合到目标周期
rows = await repository.get_candles(session, symbol, "1d", limit=limit)
# 始终以日线为基底，再聚合到目标周期（取最新 limit 根）
rows = await repository.get_recent_candles(session, symbol, "1d", limit=limit)
bars = resample_bars(_rows_to_bars(rows), timeframe)
return [CandleOut(ts=b.ts, open=b.open, high=b.high, low=b.low, close=b.close, volume=b.volume) for b in bars]
return [
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
]
@router.post("/data/sync", response_model=SyncResponse)
@@ -305,7 +318,9 @@ async def backtest(
candles = [
CandleOut(ts=r["ts"], open=r["open"], high=r["high"], low=r["low"],
close=r["close"], volume=r["volume"])
close=r["close"], volume=r["volume"],
amount=r["amount"] if "amount" in df.columns else None,
turnover=r["turnover"] if "turnover" in df.columns else None)
for _, r in df.iterrows()
]
signals = [
@@ -576,11 +591,14 @@ async def screener_sync_status(session: AsyncSession = Depends(get_session)) ->
@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",
end: str | None = None,
session: AsyncSession = Depends(get_session),
) -> PreviewResponse:
"""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，失败退 market_daily 近段）+ 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）。"""
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"):
@@ -591,6 +609,13 @@ async def screener_preview(
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]
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)
# 先取 market_daily 最新行：既做缓存过期判断，也做信息卡数据源
@@ -601,36 +626,48 @@ async def screener_preview(
).scalars().first()
# --- 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） ---
# fetcher 增量拉取写入的是 qfq（settings.data_adjust），此时底座模式记为 qfq。
rows = await repository.get_candles(session, symbol, "1d", limit=100000)
# fetcher 现在只做「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，mode 无需再推断。
# 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：
# 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 + 800)
source = "bfq"
mode = "bfq"
try:
if not rows:
await fetcher.sync_symbol(session, symbol, source="auto")
rows = await repository.get_candles(session, symbol, "1d", limit=100000)
mode = settings.data_adjust if settings.data_adjust in _ADJUST_MODES else "qfq"
elif md is not None and rows and rows[-1].ts.date() < md.trade_date.date():
await fetcher.sync_symbol(session, symbol, source="auto", force=True)
rows = await repository.get_candles(session, symbol, "1d", limit=100000)
mode = settings.data_adjust if settings.data_adjust in _ADJUST_MODES else "qfq"
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 = []
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）
rows = await repository.get_candles_before(session, symbol, "1d", before=end_dt, limit=fetch_n)
else:
# 注意取「最新 fetch_n 根」而非最旧：get_candles 是 asc+limit（取最旧），窗口化后首屏会停在过期日期
rows = await repository.get_recent_candles(session, symbol, "1d", limit=fetch_n)
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 md is not None and rows and rows[-1].ts.date() < md.trade_date.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:
if not bars and end_dt is None:
source = "market"
res = await session.execute(
select(MarketDaily).where(MarketDaily.ts_code == ts_code).order_by(MarketDaily.trade_date)
)
bars = [
Bar(ts=r.trade_date, open=r.open, high=r.high, low=r.low, close=r.close, volume=r.vol * 100.0)
Bar(
ts=r.trade_date, open=r.open, high=r.high, low=r.low, close=r.close,
volume=r.vol * 100.0, amount=r.amount * 1000.0 if r.amount else None, # 千元 -> 元
)
for r in res.scalars()
]
if not bars:
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」）")
# 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
# --- 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 adjust != mode:
@@ -648,27 +685,30 @@ async def screener_preview(
# --- 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（在全量历史上计算后截尾，保证预热正确） ---
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: dict[str, dict[str, list[float | None]]] = {
"ma": {f"ma{p}": _series_to_jsonable(ind.ma(closes, p)) for p in ma_periods},
"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")},
}
# --- 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": {f"ma{p}": _series_to_jsonable(ind.ma(closes, p)) for p in ma_periods},
"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")},
}
limit = max(30, min(limit, len(bars)))
for group in indicators.values():
for key in group:
@@ -724,7 +764,8 @@ async def screener_preview(
)
candles = [
CandleOut(ts=b.ts, open=b.open, high=b.high, low=b.low, close=b.close, volume=b.volume)
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:]
]
return PreviewResponse(ts_code=ts_code, symbol=symbol, source=source, info=info, candles=candles, indicators=indicators)
return PreviewResponse(ts_code=ts_code, symbol=symbol, source=source, info=info, candles=candles, indicators=indicators, has_more=has_more)