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https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
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shy3130
3d627aba5e
- fuyao 客户端新增 short-term-benchmark 端点透传 - auction_benchmark 服务: 历史按日 JSON 缓存(当日不缓存)、交易日回退、 四态降级(ok/fallback_prev/source_unavailable/no_data) - 读取时从相邻日K分区现算当日/次日收益对照, 不落缓存 - 复盘 user prompt 注入「盘前风向标(竞价)」上下文 - 11 个测试覆盖回退/缓存/富化数学/上下文
289 lines
11 KiB
Python
289 lines
11 KiB
Python
"""短线风向标服务 (fuyao 专有) — 复盘页卡片 + AI 复盘上下文。
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非路由数据集: tickflow 无对应能力, 直接经 custom_sources 调 fuyao provider;
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fuyao 未配置时返回 source_unavailable 状态, 前端降级提示。
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数据契约 (实测 2026-08-30, 60 交易日回测 353 样本):
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- 每日 5~6 只, 服务端筛选的竞价异动股, 附概念标签
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- 名单当日 (开盘买→收盘卖) 均值 +0.54% vs 全市场 +0.10%, 有真实当日选股能力;
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但高开≥5% 子集当日 -1.97% (追高陷阱) → 前端对高开子集标「追高风险」
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- 次日无显著优势 (+0.08%), 定位为「当日观察名单」而非隔夜轮动信号
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缓存策略 (与 dragon_tiger 同模式):
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- 历史名单不可变 → 按日落 JSON 缓存 (data/auction_benchmark/date=YYYY-MM-DD.json),
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缓存命中不触发插件注册表加载
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- 收益 enrich (当日oc/全天/次日) 不落缓存 — 次日数据晚到, 读取时现算
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- 当日名单不缓存 (竞价阶段名单可能变动, 以现拉为准)
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- 显式日期失败 → 回退上一交易日一次 (state=fallback_prev)
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日期解析: 接口对显式非交易日报 code=1002, 本层用本地 kline_daily 分区日期
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把目标日回退到「≤目标日的最近交易日」, 规避报错。
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"""
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from __future__ import annotations
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import contextlib
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import json
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import logging
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import re
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from datetime import date as date_cls
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from pathlib import Path
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import polars as pl
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from app.market_time import cn_today
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logger = logging.getLogger(__name__)
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_DATE_DIR_RE = re.compile(r"^date=(\d{4}-\d{2}-\d{2})$")
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def _local_trading_days(data_dir: Path) -> list[date_cls]:
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"""本地日K分区日期 = 已知交易日集合 (升序)。扫描失败返回空。"""
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root = data_dir / "kline_daily"
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out: list[date_cls] = []
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try:
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for d in root.iterdir():
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m = _DATE_DIR_RE.match(d.name)
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if d.is_dir() and m:
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try:
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out.append(date_cls.fromisoformat(m.group(1)))
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except ValueError:
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continue
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except OSError:
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return []
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return sorted(out)
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def resolve_trade_date(data_dir: Path, target: date_cls | None) -> date_cls | None:
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"""目标日 → ≤目标日的最近本地交易日。None → None (由 fuyao 取当日)。"""
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if target is None:
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return None
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days = _local_trading_days(data_dir)
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if not days:
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return target
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candidates = [d for d in days if d <= target]
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return max(candidates) if candidates else target
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def _prev_trading_day(data_dir: Path, d: date_cls) -> date_cls | None:
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days = _local_trading_days(data_dir)
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earlier = [x for x in days if x < d]
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return max(earlier) if earlier else None
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def _next_trading_day(data_dir: Path, d: date_cls) -> date_cls | None:
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days = _local_trading_days(data_dir)
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later = [x for x in days if x > d]
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return min(later) if later else None
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def _provider():
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from app.data_providers import custom as custom_sources
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if not custom_sources.is_custom_provider("fuyao"):
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return None
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return custom_sources.get_provider("fuyao")
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def _cache_path(data_dir: Path, d: date_cls) -> Path:
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return data_dir / "auction_benchmark" / f"date={d.isoformat()}.json"
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def _load_cache(path: Path) -> dict | None:
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try:
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return json.loads(path.read_text(encoding="utf-8"))
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except (OSError, ValueError):
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return None
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def _store_cache(path: Path, payload: dict) -> None:
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path.parent.mkdir(parents=True, exist_ok=True)
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tmp = path.with_name(path.name + ".part")
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tmp.write_text(json.dumps(payload, ensure_ascii=False), encoding="utf-8")
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tmp.replace(path)
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def _raw_items(data: dict) -> list[dict]:
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items = data.get("item")
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return [r for r in items if isinstance(r, dict)] if isinstance(items, list) else []
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def _read_kline_closes(data_dir: Path, d: date_cls) -> dict[str, float]:
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"""某交易日全市场 {symbol: close}; 无分区/读失败返回空。"""
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root = data_dir / "kline_daily" / f"date={d.isoformat()}"
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try:
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files = sorted(root.glob("*.parquet"))
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if not files:
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return {}
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df = pl.concat([pl.read_parquet(f, columns=["symbol", "close"]) for f in files])
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return dict(zip(df["symbol"].to_list(), df["close"].to_list()))
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except (OSError, pl.exceptions.PolarsError):
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return {}
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def _enrich(data_dir: Path, trade_date: date_cls, items: list[dict]) -> list[dict]:
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"""名单叠加真实收益: day0_oc (开盘买→收盘卖) / day0_pct (全天) / d1_pct (次日)。
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用相邻 kline_daily 分区现算, 不落缓存 — 次日分区晚到时先给 None, 到了自然补上。
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"""
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root = data_dir / "kline_daily" / f"date={trade_date.isoformat()}"
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day0: dict[str, tuple[float, float]] = {} # symbol -> (open, close)
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try:
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files = sorted(root.glob("*.parquet"))
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if files:
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df = pl.concat([pl.read_parquet(f, columns=["symbol", "open", "close"]) for f in files])
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day0 = dict(zip(df["symbol"].to_list(), zip(df["open"].to_list(), df["close"].to_list())))
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except (OSError, pl.exceptions.PolarsError):
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day0 = {}
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prev = _prev_trading_day(data_dir, trade_date)
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prev_close = _read_kline_closes(data_dir, prev) if prev else {}
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nxt = _next_trading_day(data_dir, trade_date)
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next_close = _read_kline_closes(data_dir, nxt) if nxt else {}
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out: list[dict] = []
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for r in items:
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sym = str(r.get("thscode") or "")
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oc = pct = d1 = None
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if sym in day0:
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o, c = day0[sym]
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if o and o > 0 and c is not None:
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oc = c / o - 1.0
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pc = prev_close.get(sym)
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if pc and pc > 0 and c is not None:
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pct = c / pc - 1.0
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nc = next_close.get(sym)
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if c and c > 0 and nc is not None:
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d1 = nc / c - 1.0
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out.append({
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"thscode": sym,
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"ticker": r.get("ticker"),
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"name": r.get("name"),
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"auction_pct": r.get("auction_pct"),
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"tags": [str(t) for t in (r.get("tags") or [])],
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"day0_oc": oc,
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"day0_pct": pct,
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"d1_pct": d1,
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})
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return out
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def _base_payload(data_dir: Path, trade_date: date_cls, data: dict) -> dict:
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return {
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"state": "ok",
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"requested_date": trade_date.isoformat(),
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"trade_date": str(data.get("date") or trade_date.isoformat()),
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"count": len(_raw_items(data)),
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"raw_items": _raw_items(data),
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}
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def get_auction_benchmark(data_dir: Path, target: date_cls | None = None) -> dict:
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"""取短线风向标名单 (含当日/次日真实收益)。返回给前端的统一容器。
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state: ok (正常) | fallback_prev (目标日拉取失败, 已回退上一期)
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| source_unavailable (未配置 fuyao) | no_data (拉取失败)
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"""
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days = _local_trading_days(data_dir)
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if target is None:
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target = max(days) if days else None
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trade_date = resolve_trade_date(data_dir, target)
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today = cn_today()
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# 历史日缓存优先 (纯本地, 不触发插件注册表加载)
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if trade_date is not None and trade_date < today:
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cached = _load_cache(_cache_path(data_dir, trade_date))
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if cached is not None:
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return _respond(data_dir, trade_date, cached, cached.get("state") or "ok")
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provider = _provider()
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if provider is None:
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return {"state": "source_unavailable"}
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from app.plugins.fuyao.client import FuyaoError
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explicit = trade_date.isoformat() if trade_date is not None else None
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try:
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data = provider.short_term_benchmark(explicit)
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try:
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actual = date_cls.fromisoformat(str(data.get("date")))
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except ValueError:
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actual = trade_date
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base = _base_payload(data_dir, actual, data)
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# 历史日不可变 → 落缓存; 当日不缓存 (竞价阶段名单可能变动)
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if actual is not None and actual < today:
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with contextlib.suppress(OSError):
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_store_cache(_cache_path(data_dir, actual), base)
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return _respond(data_dir, actual, base, "ok")
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except FuyaoError as e:
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# 显式日期失败 (非交易日/边界日) → 回退上一交易日一次
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if trade_date is not None:
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prev = _prev_trading_day(data_dir, trade_date)
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if prev is not None:
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try:
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cached_prev = _load_cache(_cache_path(data_dir, prev))
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if cached_prev is not None:
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return _respond(data_dir, prev, cached_prev, "fallback_prev",
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requested=explicit)
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data_prev = provider.short_term_benchmark(prev.isoformat())
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base = _base_payload(data_dir, prev, data_prev)
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with contextlib.suppress(OSError):
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_store_cache(_cache_path(data_dir, prev), base)
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return _respond(data_dir, prev, base, "fallback_prev",
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requested=explicit)
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except FuyaoError:
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pass
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logger.warning("短线风向标拉取失败: %s", e)
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return {"state": "no_data", "message": str(e)}
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def _respond(
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data_dir: Path,
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trade_date: date_cls | None,
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base: dict,
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state: str,
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requested: str | None = None,
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) -> dict:
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"""缓存/现拉的原始容器 → 叠加收益 enrich 后的前端容器。"""
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if trade_date is None:
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return {**base, "state": state}
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payload = {
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"state": state,
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"requested_date": requested if requested is not None else base.get("requested_date"),
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"trade_date": base.get("trade_date") or trade_date.isoformat(),
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"count": base.get("count") or 0,
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"items": _enrich(data_dir, trade_date, base.get("raw_items") or []),
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}
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return payload
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def build_recap_context(data_dir: Path) -> str:
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"""AI 复盘的盘前风向标摘要段 (纯文本, 失败返回空串不影响复盘)。"""
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try:
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payload = get_auction_benchmark(data_dir, None)
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if payload.get("state") not in ("ok", "fallback_prev"):
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return ""
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items = payload.get("items") or []
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if not items:
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return ""
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trade_date = payload.get("trade_date") or ""
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lines = [f"(数据日期: {trade_date})"]
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segs = []
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for i in items:
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seg = (f"{i.get('name')}({i.get('thscode')}) 竞价{(i.get('auction_pct') or 0):+.2f}%"
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f"[{'·'.join(i.get('tags') or [])}]")
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if i.get("day0_oc") is not None:
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seg += f" → 当日开盘买{i['day0_oc']*100:+.2f}%"
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if i.get("d1_pct") is not None:
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seg += f", 次日{i['d1_pct']*100:+.2f}%"
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segs.append(seg)
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lines.append("盘前风向标名单: " + "; ".join(segs))
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ocs = [i["day0_oc"] for i in items if i.get("day0_oc") is not None]
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if ocs:
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lines.append(f"名单当日(开盘买→收盘卖)均值 {sum(ocs)/len(ocs)*100:+.2f}%")
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return "\n".join(lines)
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except Exception as e: # noqa: BLE001 — 摘要失败不影响复盘主流程
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logger.debug("盘前风向标复盘摘要构建失败: %s", e)
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return ""
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