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https://ghfast.top/https://github.com/aeroxw/easy_tdx_max.git
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Justin Gu
e374a0da28
对 v1.21→v1.32.5 的 249 文件 4.2 万行改动做六路专项审查，本轮落地全部发现： 回测正确性：组合收益 fillna(0) 虚增、轮动停牌日过期价成交、单标的 WF 逐窗指标 被预热区稀释（三件套均带先红后绿回归）；worst_drawdown 方向、grading 容错、 组合体检品种费率、寻优端点费率透传。 安全：LLM api_url 仅 http/https 且禁 userinfo（封死 file:// 读取与 Key 外送链）、 错误响应不回显原始 body、响应体 2MB 上限、配置原子写、坏配置字段级防御。 数据：涨跌停价整数分币舍入（67/318/90 个价位错 1 分漏判清零）、交易时段/采样/ provisional 统一沪时区、warehouse 增量缺口自动全量重拉、provisional 定点转正、 baostock 真故障抛错 + W/M 去 tradestatus（实测服务端报错，周月兜底此前从未工作） + 指数 vol 股→手（实测锚定）、ccpm 结构变更抛错。 Web API：缓存键补 count/vipdoc、NaN 清洗先于缓存、count>800 分页取全量、 submit 透传真实状态、pending 不再被淘汰成幽灵、watchlist/server 入参约束。 公式：FILTER 去副作用、0-1 值域误判收严、递归深度上限、REF 负移位显式禁止。 前端：4 处请求竞态序号守卫、Sparkline viewBox、北交所 market=2 映射、 空数据缓存死角、AI 弹窗卸载中止轮询、量能/资金日历口径修正。 CLI/CI：warehouse sync 失败 exit 1、参数校验干净报错、release 真实发布 SHA256、 CI 超时与缓存、spec 补 baostock 前提。 约 60 条回归测试先红后绿；pytest 1820 全过，ruff/mypy/vue-tsc/node --test 全绿。
267 lines
10 KiB
Python
267 lines
10 KiB
Python
"""涨停生态（screen.limitup + /limitup-ecology 端点）单测。
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用合成 .day 二进制文件验证：涨停/连板/炸板/跌停判定、20cm 创业板、
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主板 5% 疑似 ST、汇总统计与排序；端点侧验证 DictResponse 包装与 60s 缓存。
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"""
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from __future__ import annotations
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import pytest
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from easy_tdx.offline.daily_bar import _DAILY_FMT
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def _day(date: int, open_: float, high: float, low: float, close: float) -> bytes:
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"""按 .day 真实格式打包一根日线（价格 ×100 存 uint，成交额 f32）。"""
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return _DAILY_FMT.pack(
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date,
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round(open_ * 100),
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round(high * 100),
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round(low * 100),
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round(close * 100),
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5_000_000.0,
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1_000_000,
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0,
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)
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def _write_stock(
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vipdoc,
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exchange: str,
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code: str,
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closes: list[float],
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highs: list[float] | None = None,
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dates: list[int] | None = None,
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) -> None:
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"""写一只股票的 .day 文件；closes 逐日收盘，highs 缺省=每日收盘。"""
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lday = vipdoc / exchange / "lday"
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lday.mkdir(parents=True, exist_ok=True)
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highs = highs or closes
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dates = dates or [20260801 + i for i in range(len(closes))]
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data = b"".join(_day(d, c - 0.05, h, c - 0.10, c) for d, c, h in zip(dates, closes, highs))
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(lday / f"{exchange}{code}.day").write_bytes(data)
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@pytest.fixture
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def vipdoc(tmp_path):
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"""合成市场（全部股票最后 bar 对齐 20260804，模拟真实"同一交易日"）。"""
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last4 = [20260801, 20260802, 20260803, 20260804]
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# 主板 3 连板：10.00 → 11.00 → 12.10 → 13.31（每根恰为 round(prev×1.1, 2)）
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_write_stock(tmp_path, "sh", "600100", [10.00, 11.00, 12.10, 13.31])
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# 创业板 2 连板（20cm）：20.00 → 24.00 → 28.80（首根铺垫同价）
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_write_stock(tmp_path, "sz", "300200", [20.00, 20.00, 24.00, 28.80], dates=last4)
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# 主板 5%（疑似 ST，前收 ≥3 才启用 ST 判定）：10.00 → 10.50
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_write_stock(tmp_path, "sh", "600300", [10.00, 10.00, 10.00, 10.50], dates=last4)
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# 炸板：前收 10.00，最高触 11.00，收 10.80（离开 5% 价位避免歧义）
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_write_stock(
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tmp_path,
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"sh",
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"600400",
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[10.00, 10.00, 10.00, 10.80],
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highs=[10.20, 10.20, 10.50, 11.00],
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dates=last4,
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)
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# 跌停：10.00 → 9.00
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_write_stock(tmp_path, "sz", "000500", [10.00, 10.00, 10.00, 9.00], dates=last4)
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# 平盘（无事件）
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_write_stock(tmp_path, "sh", "600600", [10.00, 10.00, 10.00, 10.20], dates=last4)
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# 陈旧文件：数据停在 20260703，当年的"3连板"不得进入今日生态
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_write_stock(
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tmp_path,
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"sh",
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"600700",
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[10.00, 11.00, 12.10],
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dates=[20260701, 20260702, 20260703],
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)
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# 低价 ST 护栏：前收 2.00（<3）恰收 +5%（2.10）不算涨停
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_write_stock(tmp_path, "sh", "600800", [2.00, 2.00, 2.00, 2.10], dates=last4)
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return tmp_path
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def test_limitup_core_detection(vipdoc):
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from easy_tdx.screen.limitup import compute_limitup_ecology
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eco = compute_limitup_ecology(vipdoc)
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assert eco.data_date == 20260804
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assert eco.total == 8
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up = {e.code: e for e in eco.limit_up}
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assert set(up) == {"600100", "300200", "600300"} # 600700 陈旧排除、600800 低价护栏
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board3 = up["600100"]
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assert board3.streak == 3
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assert board3.market == "SH"
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assert board3.pct == pytest.approx(10.0, abs=0.01)
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assert board3.st is False
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cyb = up["300200"]
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assert cyb.streak == 2 # 20cm 创业板
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assert cyb.pct == pytest.approx(20.0, abs=0.01)
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assert up["600300"].streak == 1
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assert up["600300"].st is True # 主板 5% → 疑似 ST
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# 连板天梯排序：高度降序
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assert [e.streak for e in eco.limit_up] == [3, 2, 1]
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# 炸板与跌停
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assert [e.code for e in eco.blown] == ["600400"]
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assert eco.blown[0].pct == pytest.approx(8.0, abs=0.01)
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assert [e.code for e in eco.limit_down] == ["000500"]
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assert eco.limit_down[0].streak == 1
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s = eco.summary()
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assert s["limit_up_count"] == 3
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assert s["blown_count"] == 1
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assert s["limit_down_count"] == 1
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assert s["max_streak"] == 3
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assert s["first_board"] == 1 # 仅 600300 首板；600100 三板、300200 二板
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assert s["blown_rate"] == 25.0 # 3 封住 + 1 炸板
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def test_limitup_empty_vipdoc(tmp_path):
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from easy_tdx.screen.limitup import compute_limitup_ecology
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eco = compute_limitup_ecology(tmp_path / "nonexistent")
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assert eco.total == 0
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assert eco.data_date == 0
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assert eco.summary()["limit_up_count"] == 0
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# ── 涨跌停价舍入（回归：浮点 floor(x*100+0.5) 在半分边界错 1 分）──────────────
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def test_limit_price_matches_exchange_rounding_all_range():
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"""_limit_price 与交易所 ROUND_HALF_UP 对 1.00~600.00 全价位零差异。
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旧实现（float 乘后 floor）在 ±10% 档 67/318 个价位、±5% 档 90/884 个
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价位算低 1 分（如 prev=1.15：涨停价应 1.27，旧算 1.26）。
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"""
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from decimal import ROUND_HALF_UP, Decimal
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from easy_tdx.screen.limitup import _limit_price
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for pct in (10, 5, 20, -10, -5, -20):
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for cents in range(100, 60001):
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prev = Decimal(cents).scaleb(-2)
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expected = (
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int(
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(Decimal(cents) * (100 + pct) / 100).quantize(
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Decimal("1"), rounding=ROUND_HALF_UP
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)
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)
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/ 100
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)
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got = _limit_price(float(prev), pct)
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assert got == expected, (prev, pct, got, expected)
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def test_exchange_boundary_prices_detected(tmp_path):
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"""半分边界价位的真实涨跌停不因浮点舍入漏判。
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选点依据：.day 读回（raw×0.01）的浮点误差会抵消部分边界，33.05→36.36
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与 2.65→2.39 是经读回仿真验证后旧实现（floor 浮点版）仍漏判的价位。
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"""
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from easy_tdx.screen.limitup import compute_limitup_ecology
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# prev=33.05 → 交易所涨停价 36.36（旧实现误算 36.35 → 漏判涨停）
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_write_stock(tmp_path, "sh", "600901", [33.05, 36.36])
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# prev=2.65 → 交易所跌停价 2.39（旧实现误算 2.38 → 漏判跌停）
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_write_stock(tmp_path, "sz", "000902", [2.65, 2.39])
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eco = compute_limitup_ecology(tmp_path)
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up = {e.code: e for e in eco.limit_up}
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down = {e.code: e for e in eco.limit_down}
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assert "600901" in up, f"33.05→36.36 应判涨停，实际 limit_up={up}"
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assert up["600901"].streak == 1
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assert "000902" in down, f"2.65→2.39 应判跌停，实际 limit_down={down}"
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def test_history_boundary_prices_counted(tmp_path):
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"""历史回补同样按交易所口径计涨跌停（33.05→36.36 / 2.65→2.39）。"""
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from easy_tdx.screen.limitup import compute_limitup_history
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_write_stock(tmp_path, "sh", "600901", [33.05, 36.36])
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_write_stock(tmp_path, "sz", "000902", [2.65, 2.39])
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rows = {r["date"]: r for r in compute_limitup_history(tmp_path, days=5)}
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assert rows[20260802]["limit_up"] == 1
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assert rows[20260802]["limit_down"] == 1
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def test_limitup_endpoint_and_cache(vipdoc, monkeypatch):
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"""端点返回 DictResponse 包装；60s 内命中缓存（扫描只跑一次）。"""
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pytest.importorskip("fastapi")
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from fastapi import FastAPI
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from fastapi.testclient import TestClient
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from easy_tdx.screen import limitup as limitup_mod
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from easy_tdx.web.errors import register_exception_handlers
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from easy_tdx.web.routers import market as market_mod
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calls = {"n": 0}
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real = limitup_mod.compute_limitup_ecology
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def counting(*a, **kw):
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calls["n"] += 1
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return real(*a, **kw)
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monkeypatch.setattr(limitup_mod, "compute_limitup_ecology", counting)
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app = FastAPI()
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register_exception_handlers(app)
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app.include_router(market_mod.router, prefix="/api/v1")
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app.state.tdx_client = object()
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with TestClient(app) as client:
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r1 = client.get("/api/v1/limitup-ecology", params={"vipdoc": str(vipdoc)})
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assert r1.status_code == 200
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d1 = r1.json()["data"]
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assert d1["summary"]["limit_up_count"] == 3
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assert d1["limit_up"][0]["code"] == "600100"
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r2 = client.get("/api/v1/limitup-ecology", params={"vipdoc": str(vipdoc)})
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assert r2.status_code == 200
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assert r2.json()["data"] == d1
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assert calls["n"] == 1 # 第二次命中缓存
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def test_limitup_endpoint_cache_key_includes_vipdoc(vipdoc, tmp_path, monkeypatch):
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"""缓存键须含 vipdoc：不同 vipdoc 的请求在 TTL 内不互相命中。
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旧实现 _limitup_cache 是单值缓存，先到的 vipdoc=A 结果会被 vipdoc=B
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的请求在 60s TTL 内复用。
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"""
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pytest.importorskip("fastapi")
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from fastapi import FastAPI
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from fastapi.testclient import TestClient
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from easy_tdx.web.errors import register_exception_handlers
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from easy_tdx.web.routers import market as market_mod
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other = tmp_path / "vipdoc_other"
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(other / "sh" / "lday").mkdir(parents=True)
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(other / "sh" / "lday" / "sh600100.day").write_bytes(
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_day(20260801, 9.95, 11.0, 9.9, 11.0) + _day(20260802, 11.0, 12.1, 10.9, 12.1)
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)
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app = FastAPI()
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register_exception_handlers(app)
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app.include_router(market_mod.router, prefix="/api/v1")
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app.state.tdx_client = object()
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with TestClient(app) as client:
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r1 = client.get("/api/v1/limitup-ecology", params={"vipdoc": str(vipdoc)})
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assert r1.status_code == 200
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r2 = client.get("/api/v1/limitup-ecology", params={"vipdoc": str(other)})
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assert r2.status_code == 200
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# 同 vipdoc 的第二次请求才命中缓存；不同 vipdoc 必须各自扫描
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with TestClient(app) as client:
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client.get("/api/v1/limitup-ecology", params={"vipdoc": str(vipdoc)})
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client.get("/api/v1/limitup-ecology", params={"vipdoc": str(vipdoc)})
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d = client.get("/api/v1/limitup-ecology", params={"vipdoc": str(other)}).json()["data"]
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# other 目录只有 600100 一只 2 连板，不含 vipdoc 目录的 3 连板数据
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assert d["summary"]["limit_up_count"] == 1
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