mirror of
https://ghfast.top/https://github.com/aeroxw/easy_tdx_max.git
synced 2026-09-12 16:54:20 +08:00
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。
377 lines
13 KiB
Python
377 lines
13 KiB
Python
"""市场情绪采样（store / sampler / 端点）与涨停历史回补单测。
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sentiment_store 用 EASY_TDX_CONFIG_DIR 指向临时目录；limitup 历史复用
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合成 .day 文件；端点侧验证 DictResponse 包装与缓存命中。
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"""
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from __future__ import annotations
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import asyncio
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import pathlib
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import pytest
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@pytest.fixture
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def store(tmp_path, monkeypatch):
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"""独立配置目录 + 全新单例的 SentimentStore。"""
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from easy_tdx.web import sentiment_store as ss
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monkeypatch.setenv("EASY_TDX_CONFIG_DIR", str(tmp_path / "cfg"))
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ss._store = None
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s = ss.get_sentiment_store()
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yield s
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ss._store = None
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def _sample(date: int, minute: int, up=2000, down=2000, limit_up=50, limit_down=10, amount=8e11):
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from datetime import datetime
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return {
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"date": date,
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"minute": minute,
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"ts": int(datetime(2026, 9, 4).timestamp()),
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"up_count": up,
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"down_count": down,
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"neutral_count": 100,
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"total_count": up + down + 100,
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"limit_up_count": limit_up,
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"limit_down_count": limit_down,
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"total_amount": amount,
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}
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def test_store_day_samples_and_idempotent(store):
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store.insert(_sample(20260904, 935))
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store.insert(_sample(20260904, 930))
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# 同 (date, minute) 覆盖不累积
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store.insert(_sample(20260904, 930, limit_up=77))
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rows = store.day_samples(20260904)
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assert [r["minute"] for r in rows] == [930, 935] # 升序
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assert rows[0]["limit_up_count"] == 77 # 覆盖生效
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assert store.latest_date() == 20260904
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def test_store_daily_history_close_snapshot_and_peak(store):
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# 收盘快照 = 当日最后一条采样；峰值 = 当日涨停最大值
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store.insert(_sample(20260903, 930, up=1500, limit_up=30, limit_down=40, amount=7e11))
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store.insert(
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_sample(20260903, 1500, up=2500, down=1500, limit_up=90, limit_down=5, amount=9e11)
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)
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store.insert(
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_sample(20260904, 930, up=1800, down=2200, limit_up=20, limit_down=60, amount=6e11)
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)
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days = store.daily_history(10)
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assert [d["date"] for d in days] == [20260903, 20260904] # 升序
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d3 = days[0]
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assert d3["limit_up_peak"] == 90 # 日内峰值（930 点只有 30，1500 点 90）
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assert d3["limit_up_close"] == 90 # 收盘快照取当日最后一条
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assert d3["up_count"] == 2500
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assert d3["up_ratio"] == 62.5 # 2500 / (2500+1500)
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d4 = days[1]
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assert d4["limit_up_peak"] == 20
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assert d4["up_ratio"] == 45.0 # 1800 / 4000
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def test_sampler_inserts_store_rows(store):
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import pandas as pd
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from easy_tdx.web.sentiment_sampler import SentimentSampler
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df = pd.DataFrame(
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[
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{
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"up_count": 2100,
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"down_count": 2300,
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"neutral_count": 120,
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"total_count": 4520,
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"limit_up_count": 44,
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"limit_down_count": 9,
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"total_amount": 8.5e11,
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}
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]
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)
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class FakeClient:
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async def get_market_stat(self):
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return df
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sampler = SentimentSampler(FakeClient().get_market_stat, store=store, interval=1.0)
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asyncio.run(sampler._sample_once())
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rows = store.day_samples(store.latest_date())
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assert len(rows) == 1
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assert rows[0]["limit_up_count"] == 44
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assert rows[0]["total_amount"] == 8.5e11
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@pytest.fixture
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def vipdoc_factory(tmp_path):
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"""按 {文件名: {dates, closes}} 合成 vipdoc 目录的工厂。
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``factory(specs, root=None)``：root 缺省写 tmp_path；同一测试需要多个
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独立 vipdoc 目录时传不同 root。
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"""
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from easy_tdx.offline.daily_bar import _DAILY_FMT
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def _day(date: int, close: float) -> bytes:
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return _DAILY_FMT.pack(
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date,
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round((close - 0.05) * 100),
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round(close * 100),
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round((close - 0.10) * 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 factory(specs: dict[str, dict], root=None) -> object:
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base = pathlib.Path(root) if root is not None else tmp_path
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for filename, spec in specs.items():
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exchange = filename[:2]
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lday = base / exchange / "lday"
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lday.mkdir(parents=True, exist_ok=True)
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data = b"".join(_day(d, c) for d, c in zip(spec["dates"], spec["closes"]))
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(lday / f"{filename}.day").write_bytes(data)
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return base
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return factory
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def test_limitup_history_counts(vipdoc_factory):
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from easy_tdx.screen.limitup import compute_limitup_history
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v = vipdoc_factory(
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# A 股票：0802、0803 连续两日涨停
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{
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"sh600100": {
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"dates": [20260801, 20260802, 20260803, 20260804],
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"closes": [10.00, 11.00, 12.10, 12.50],
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},
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# B 股票：0804 跌停
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"sz000200": {
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"dates": [20260801, 20260802, 20260803, 20260804],
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"closes": [10.00, 10.00, 10.00, 9.00],
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},
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}
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)
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rows = compute_limitup_history(v, days=10)
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by_date = {r["date"]: r for r in rows}
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assert by_date[20260802]["limit_up"] == 1
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assert by_date[20260803]["limit_up"] == 1
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assert by_date[20260804]["limit_down"] == 1
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assert by_date[20260804]["limit_up"] == 0
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# 升序
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dates = [r["date"] for r in rows]
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assert dates == sorted(dates)
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def test_limitup_history_endpoint_cache(vipdoc_factory, monkeypatch):
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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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v = vipdoc_factory({"sh600100": {"dates": [20260801, 20260802], "closes": [10.0, 11.0]}})
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calls = {"n": 0}
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real = limitup_mod.compute_limitup_history
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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_history", 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/market/limitup-history", params={"days": 10, "vipdoc": str(v)})
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assert r1.status_code == 200
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body = r1.json()["data"]
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# 仅 0802 有一天涨停（0801 无前收不计数）
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assert body["count"] == 1
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assert body["days"][0] == {"date": 20260802, "limit_up": 1, "limit_down": 0}
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client.get("/api/v1/market/limitup-history", params={"days": 10, "vipdoc": str(v)})
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assert calls["n"] == 1 # 缓存命中
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def test_board_fund_history_null_main_net_no_type_error(tmp_path):
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"""历史遗留的 main_net NULL 行不得让 /market/board-fund/history 抛 TypeError。
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正式 schema 的 main_net 是 REAL NOT NULL（NaN 会被 SQLite 存成 NULL 而
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被 NOT NULL 拒绝），但手工编辑/旧版本库可能存在 NULL 行——读侧须兜底。
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旧实现：float(None) 抛 TypeError。
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"""
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import sqlite3
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db = tmp_path / "legacy_sentiment.db"
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conn = sqlite3.connect(db)
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conn.executescript(
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"""
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CREATE TABLE samples (date INTEGER NOT NULL, minute INTEGER NOT NULL, ts INTEGER NOT NULL,
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up_count INTEGER NOT NULL, down_count INTEGER NOT NULL, neutral_count INTEGER NOT NULL,
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total_count INTEGER NOT NULL, limit_up_count INTEGER NOT NULL,
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limit_down_count INTEGER NOT NULL, total_amount REAL NOT NULL,
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PRIMARY KEY (date, minute));
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CREATE TABLE board_fund (date INTEGER NOT NULL, rank INTEGER NOT NULL,
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code TEXT NOT NULL, name TEXT NOT NULL, main_net REAL,
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PRIMARY KEY (date, rank));
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"""
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)
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conn.execute(
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"INSERT INTO board_fund (date, rank, code, name, main_net) VALUES (?,?,?,?,?)",
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(20260901, 1, "881001", "银行", None),
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)
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conn.commit()
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conn.close()
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from easy_tdx.web.sentiment_store import SentimentStore
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store = SentimentStore(db_path=db)
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assert store.list_fund_days(5) == [
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{
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"date": 20260901,
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"boards": [{"rank": 1, "code": "881001", "name": "银行", "main_net": 0.0}],
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}
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]
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def test_upsert_fund_day_nan_main_net_stored_as_zero(store):
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"""写入口径：NaN 主力净流入落库为 0.0（REAL NOT NULL 列不吃 NaN）。"""
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store.upsert_fund_day(
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20260902,
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[{"code": "881001", "name": "银行", "main_net": float("nan")}],
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)
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days = store.list_fund_days(5)
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assert days[0]["boards"][0]["main_net"] == 0.0
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def test_limitup_history_cache_key_includes_vipdoc(vipdoc_factory, monkeypatch, tmp_path):
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"""limitup-history 缓存键须含 (days, vipdoc)，不同 vipdoc 不互相命中。"""
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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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v1 = vipdoc_factory({"sh600100": {"dates": [20260801, 20260802], "closes": [10.0, 11.0]}})
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v2_dir = tmp_path / "vipdoc_v2"
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(v2_dir / "sh" / "lday").mkdir(parents=True)
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v2 = vipdoc_factory(
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{
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"sh600100": {"dates": [20260801, 20260802], "closes": [10.0, 11.0]},
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"sz000200": {"dates": [20260801, 20260802], "closes": [10.0, 9.0]},
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},
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root=v2_dir,
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)
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calls = {"n": 0}
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real = limitup_mod.compute_limitup_history
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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_history", 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/market/limitup-history", params={"days": 10, "vipdoc": str(v1)})
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assert r1.status_code == 200
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r2 = client.get("/api/v1/market/limitup-history", params={"days": 10, "vipdoc": str(v2)})
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assert r2.status_code == 200
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# v2 多一只跌停股 → 结果必须不同（不允许命中 v1 的缓存）
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assert r2.json()["data"]["days"][0]["limit_down"] == 1
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assert calls["n"] == 2
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# ── 采样器时区统一（v1.32.6）：日期/分钟键一律取沪市时区 ─────────────────────
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class _RecorderDatetime:
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"""记录 now(tz) 实参的 datetime 替身。"""
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captured: dict = {}
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@classmethod
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def now(cls, tz=None):
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cls.captured["tz"] = tz
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from datetime import datetime as _dt
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return _dt(2026, 9, 6, 2, 30, tzinfo=tz) if tz else _dt(2026, 9, 6, 2, 30)
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def test_sentiment_sampler_uses_shanghai_tz(store, monkeypatch):
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"""SentimentSampler._sample_once 的 (date, minute) 键必须取沪市时区。"""
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import asyncio
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import pandas as pd
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from easy_tdx.realtime.session import SHANGHAI_TZ
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from easy_tdx.web import sentiment_sampler as ss_mod
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async def fake_stat():
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return pd.DataFrame(
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[
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{
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"up_count": 2000,
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"down_count": 2000,
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"neutral_count": 100,
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"total_count": 4100,
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"limit_up_count": 50,
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"limit_down_count": 10,
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"total_amount": 8e11,
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}
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]
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)
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monkeypatch.setattr(ss_mod, "datetime", _RecorderDatetime)
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sampler = ss_mod.SentimentSampler(fake_stat, store=store)
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asyncio.run(sampler._sample_once())
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assert _RecorderDatetime.captured["tz"] is SHANGHAI_TZ
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rows = store.day_samples(20260906)
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assert len(rows) == 1 and rows[0]["minute"] == 230
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def test_fund_flow_sampler_uses_shanghai_tz(store, monkeypatch):
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"""FundFlowSampler._sample_once 的采样日期必须取沪市时区。"""
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import asyncio
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import pandas as pd
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from easy_tdx.realtime.session import SHANGHAI_TZ
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from easy_tdx.web import sentiment_sampler as ss_mod
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class _FakeMac:
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async def get_board_ranking(self, **kw):
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return pd.DataFrame(
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[
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{"code": "881001", "name": "银行", "main_net_amount": 1.2e9},
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]
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)
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monkeypatch.setattr(ss_mod, "datetime", _RecorderDatetime)
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sampler = ss_mod.FundFlowSampler(_FakeMac(), store=store)
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asyncio.run(sampler._sample_once())
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assert _RecorderDatetime.captured["tz"] is SHANGHAI_TZ
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days = store.list_fund_days(5)
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assert days[0]["date"] == 20260906
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