feat: 市场情绪栏目 — 盘中情绪采样器 + 宽度分时 + 涨停史离线回补

- /sentiment 市场情绪：温度卡（实时上涨占比/涨跌停/总成交，五档情绪判定）
  + 今日宽度分时（上涨/下跌/涨停家数三线）+ 近 60 日涨停跌停家数与上涨占比
- SentimentSampler：交易时段每分钟采样全市场广度（get_market_stat），
  停牌/盘外自动跳过、失败不中断；SentimentStore 落 SQLite
  （~/.easy_tdx/sentiment.db，(date,minute) 幂等主键，重启不丢）
- /market/sentiment/today|history：当日分钟曲线 + 逐日聚合（收盘快照占比/峰值）
- /market/limitup-history：涨停跌停家数逐日历史由 vipdoc 离线回补，
  无需采样积累即时可用；缓存按 days 分键（修复 10 天缓存被 60 天请求命中）
- 采样历史需交易日积累，页面空态有明示；涨停/跌停历史开箱即有 60 天

tests/unit/test_sentiment.py

@@ -0,0 +1,204 @@
+"""市场情绪采样（store / sampler / 端点）与涨停历史回补单测。
+
+sentiment_store 用 EASY_TDX_CONFIG_DIR 指向临时目录；limitup 历史复用
+合成 .day 文件；端点侧验证 DictResponse 包装与缓存命中。
+"""
+
+from __future__ import annotations
+
+import asyncio
+
+import pytest
+
+
+@pytest.fixture
+def store(tmp_path, monkeypatch):
+    """独立配置目录 + 全新单例的 SentimentStore。"""
+    from easy_tdx.web import sentiment_store as ss
+
+    monkeypatch.setenv("EASY_TDX_CONFIG_DIR", str(tmp_path / "cfg"))
+    ss._store = None
+    s = ss.get_sentiment_store()
+    yield s
+    ss._store = None
+
+
+def _sample(date: int, minute: int, up=2000, down=2000, limit_up=50, limit_down=10, amount=8e11):
+    from datetime import datetime
+
+    return {
+        "date": date,
+        "minute": minute,
+        "ts": int(datetime(2026, 9, 4).timestamp()),
+        "up_count": up,
+        "down_count": down,
+        "neutral_count": 100,
+        "total_count": up + down + 100,
+        "limit_up_count": limit_up,
+        "limit_down_count": limit_down,
+        "total_amount": amount,
+    }
+
+
+def test_store_day_samples_and_idempotent(store):
+    store.insert(_sample(20260904, 935))
+    store.insert(_sample(20260904, 930))
+    # 同 (date, minute) 覆盖不累积
+    store.insert(_sample(20260904, 930, limit_up=77))
+
+    rows = store.day_samples(20260904)
+    assert [r["minute"] for r in rows] == [930, 935]  # 升序
+    assert rows[0]["limit_up_count"] == 77  # 覆盖生效
+    assert store.latest_date() == 20260904
+
+
+def test_store_daily_history_close_snapshot_and_peak(store):
+    # 收盘快照 = 当日最后一条采样；峰值 = 当日涨停最大值
+    store.insert(_sample(20260903, 930, up=1500, limit_up=30, limit_down=40, amount=7e11))
+    store.insert(
+        _sample(20260903, 1500, up=2500, down=1500, limit_up=90, limit_down=5, amount=9e11)
+    )
+    store.insert(
+        _sample(20260904, 930, up=1800, down=2200, limit_up=20, limit_down=60, amount=6e11)
+    )
+
+    days = store.daily_history(10)
+    assert [d["date"] for d in days] == [20260903, 20260904]  # 升序
+
+    d3 = days[0]
+    assert d3["limit_up_peak"] == 90  # 日内峰值（930 点只有 30，1500 点 90）
+    assert d3["limit_up_close"] == 90  # 收盘快照取当日最后一条
+    assert d3["up_count"] == 2500
+    assert d3["up_ratio"] == 62.5  # 2500 / (2500+1500)
+
+    d4 = days[1]
+    assert d4["limit_up_peak"] == 20
+    assert d4["up_ratio"] == 45.0  # 1800 / 4000
+
+
+def test_sampler_inserts_store_rows(store):
+    import pandas as pd
+
+    from easy_tdx.web.sentiment_sampler import SentimentSampler
+
+    df = pd.DataFrame(
+        [
+            {
+                "up_count": 2100,
+                "down_count": 2300,
+                "neutral_count": 120,
+                "total_count": 4520,
+                "limit_up_count": 44,
+                "limit_down_count": 9,
+                "total_amount": 8.5e11,
+            }
+        ]
+    )
+
+    class FakeClient:
+        async def get_market_stat(self):
+            return df
+
+    sampler = SentimentSampler(FakeClient().get_market_stat, store=store, interval=1.0)
+    asyncio.run(sampler._sample_once())
+
+    rows = store.day_samples(store.latest_date())
+    assert len(rows) == 1
+    assert rows[0]["limit_up_count"] == 44
+    assert rows[0]["total_amount"] == 8.5e11
+
+
+@pytest.fixture
+def vipdoc_factory(tmp_path):
+    """按 {文件名: {dates, closes}} 合成 vipdoc 目录的工厂。"""
+    from easy_tdx.offline.daily_bar import _DAILY_FMT
+
+    def _day(date: int, close: float) -> bytes:
+        return _DAILY_FMT.pack(
+            date,
+            round((close - 0.05) * 100),
+            round(close * 100),
+            round((close - 0.10) * 100),
+            round(close * 100),
+            5_000_000.0,
+            1_000_000,
+            0,
+        )
+
+    def factory(specs: dict[str, dict]) -> object:
+        for filename, spec in specs.items():
+            exchange = filename[:2]
+            lday = tmp_path / exchange / "lday"
+            lday.mkdir(parents=True, exist_ok=True)
+            data = b"".join(
+                _day(d, c) for d, c in zip(spec["dates"], spec["closes"])
+            )
+            (lday / f"{filename}.day").write_bytes(data)
+        return tmp_path
+
+    return factory
+
+
+def test_limitup_history_counts(vipdoc_factory):
+    from easy_tdx.screen.limitup import compute_limitup_history
+
+    v = vipdoc_factory(
+        # A 股票：0802、0803 连续两日涨停
+        {
+            "sh600100": {
+                "dates": [20260801, 20260802, 20260803, 20260804],
+                "closes": [10.00, 11.00, 12.10, 12.50],
+            },
+            # B 股票：0804 跌停
+            "sz000200": {
+                "dates": [20260801, 20260802, 20260803, 20260804],
+                "closes": [10.00, 10.00, 10.00, 9.00],
+            },
+        }
+    )
+    rows = compute_limitup_history(v, days=10)
+    by_date = {r["date"]: r for r in rows}
+    assert by_date[20260802]["limit_up"] == 1
+    assert by_date[20260803]["limit_up"] == 1
+    assert by_date[20260804]["limit_down"] == 1
+    assert by_date[20260804]["limit_up"] == 0
+    # 升序
+    dates = [r["date"] for r in rows]
+    assert dates == sorted(dates)
+
+
+def test_limitup_history_endpoint_cache(vipdoc_factory, monkeypatch):
+    pytest.importorskip("fastapi")
+    from fastapi import FastAPI
+    from fastapi.testclient import TestClient
+
+    from easy_tdx.screen import limitup as limitup_mod
+    from easy_tdx.web.errors import register_exception_handlers
+    from easy_tdx.web.routers import market as market_mod
+
+    v = vipdoc_factory(
+        {"sh600100": {"dates": [20260801, 20260802], "closes": [10.0, 11.0]}}
+    )
+    calls = {"n": 0}
+    real = limitup_mod.compute_limitup_history
+
+    def counting(*a, **kw):
+        calls["n"] += 1
+        return real(*a, **kw)
+
+    monkeypatch.setattr(limitup_mod, "compute_limitup_history", counting)
+
+    app = FastAPI()
+    register_exception_handlers(app)
+    app.include_router(market_mod.router, prefix="/api/v1")
+    app.state.tdx_client = object()
+
+    with TestClient(app) as client:
+        r1 = client.get("/api/v1/market/limitup-history", params={"days": 10, "vipdoc": str(v)})
+        assert r1.status_code == 200
+        body = r1.json()["data"]
+        # 仅 0802 有一天涨停（0801 无前收不计数）
+        assert body["count"] == 1
+        assert body["days"][0] == {"date": 20260802, "limit_up": 1, "limit_down": 0}
+        client.get("/api/v1/market/limitup-history", params={"days": 10, "vipdoc": str(v)})
+    assert calls["n"] == 1  # 缓存命中