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shy3130
8fb23fcf09
- 数据页提供股票、ETF、指数历史日K自检与报告，区分已确认异常和待核实缺口 - 按异常股票和日期暂存校验、备份并修补，使用完整原始历史重算受影响指标 - 跨重启保留异常与待重算状态，失败或取消后可继续处理 - 修补完成后更新行情、指标、矩阵、策略和前端查询缓存，重算市场环境与主线 - 对已知异常阻止相关计算，提示历史回测和优化结果的数据版本过期 - 复用插件日K取数，修正 ETF 历史回补起点及任务阶段进度重置 补充自检 API、精准修补、失败恢复、资产隔离、缓存失效及前端交互测试。 前端全量 389 项及构建通过，后端执行完整回归。 Signed-off-by: shy3130 <shy3130@qq.com>
107 lines
3.9 KiB
Python
107 lines
3.9 KiB
Python
"""get_daily 复用 enriched 历史缓存的等价性测试。
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个股对话框打开时 /api/kline/daily 每个行情 tick 调用一次; 旧路径每次
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150 天扫描 + 全套指标重算, 新路径优先从预计算历史缓存裁剪。
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本测试证明: 同一份数据下两条路径输出逐列一致, 且缓存命中时不触发扫描。
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"""
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from __future__ import annotations
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from datetime import date, timedelta
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import polars as pl
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from polars.testing import assert_frame_equal
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from app.tickflow.repository import KlineRepository
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SYM = "600001.SH"
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def _raw_frame(days: int = 80) -> pl.DataFrame:
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"""构造 ~57 个交易日的 14 列形态数据 (复权价与原始价一致, 无除权)。"""
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base = date(2026, 4, 1)
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rows = []
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price = 10.0
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d = base
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while len(rows) < days:
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if d.weekday() < 5:
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open_ = price * (1 + ((len(rows) % 7) - 3) * 0.004)
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close = price * (1 + ((len(rows) % 5) - 2) * 0.006)
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high = max(open_, close) * 1.01
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low = min(open_, close) * 0.99
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price = close
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rows.append({
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"symbol": SYM, "date": d,
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"open": round(open_, 4), "high": round(high, 4),
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"low": round(low, 4), "close": round(close, 4),
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"volume": 10000.0 + (len(rows) % 10) * 500.0,
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"amount": 1.0e7,
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"raw_close": round(close, 4), "raw_high": round(high, 4),
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"raw_low": round(low, 4),
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})
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d += timedelta(days=1)
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return pl.DataFrame(rows).sort(["symbol", "date"])
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def _bare_repo(raw: pl.DataFrame) -> tuple[KlineRepository, dict]:
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repo = KlineRepository.__new__(KlineRepository)
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repo._enriched_history_cache = None
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repo._enriched_history_start = None
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repo._enriched_cache = None
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repo._enriched_cache_date = None
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repo.get_instruments = lambda: pl.DataFrame() # type: ignore[method-assign]
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repo.get_historical_shares = lambda: pl.DataFrame() # type: ignore[method-assign]
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repo.get_enriched_latest = lambda **kwargs: (pl.DataFrame(), None) # type: ignore[method-assign]
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calls = {"scan": 0}
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def _scan(symbol, start, end, columns):
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calls["scan"] += 1
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return raw.filter((pl.col("date") >= start) & (pl.col("date") <= end))
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repo._scan_daily_symbol = _scan # type: ignore[method-assign]
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return repo, calls
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def test_get_daily_cache_path_matches_scan_path():
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raw = _raw_frame()
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dates = raw["date"].to_list()
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start, end = dates[30], dates[-1]
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# 旧路径: 无历史缓存 → 扫描 + 即时计算
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repo_old, calls_old = _bare_repo(raw)
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result_old = repo_old.get_daily(SYM, start, end)
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assert calls_old["scan"] == 1
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# 新路径: 预计算历史缓存 (同一真实计算栈 _compute_enriched_range 构建)
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repo_new, calls_new = _bare_repo(raw)
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hist = repo_new._compute_enriched_range(raw)
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repo_new._enriched_history_cache = hist
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repo_new._enriched_history_start = hist["date"].min()
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result_new = repo_new.get_daily(SYM, start, end)
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assert calls_new["scan"] == 0, "缓存命中时不得回退到扫描路径"
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assert result_new.height == result_old.height
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common = sorted(set(result_old.columns) & set(result_new.columns))
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assert {"open", "close", "ma5", "ma20", "ma60", "rsi_14"} <= set(common)
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assert_frame_equal(
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result_old.sort("date").select(common),
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result_new.sort("date").select(common),
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check_exact=False,
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rel_tol=1e-9,
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)
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def test_get_daily_falls_back_to_scan_when_cache_does_not_cover_start():
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raw = _raw_frame()
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dates = raw["date"].to_list()
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repo, calls = _bare_repo(raw)
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hist = repo._compute_enriched_range(raw)
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repo._enriched_history_cache = hist
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repo._enriched_history_start = hist["date"].min()
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# 请求起点早于缓存覆盖 → 必须回退扫描路径
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result = repo.get_daily(SYM, dates[0] - timedelta(days=5), dates[-1])
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assert calls["scan"] == 1
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assert not result.is_empty()
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