mirror of
https://ghfast.top/https://github.com/aeroxw/easy_tdx_max.git
synced 2026-09-12 19:14:19 +08:00
Justin Gu
2b86a7d588
- /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
205 lines
6.5 KiB
Python
205 lines
6.5 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 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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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]) -> object:
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for filename, spec in specs.items():
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exchange = filename[:2]
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lday = tmp_path / exchange / "lday"
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lday.mkdir(parents=True, exist_ok=True)
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data = b"".join(
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_day(d, c) for d, c in zip(spec["dates"], spec["closes"])
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)
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(lday / f"{filename}.day").write_bytes(data)
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return tmp_path
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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(
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{"sh600100": {"dates": [20260801, 20260802], "closes": [10.0, 11.0]}}
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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(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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