mirror of
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shy3130
918c7ade7e
- 策略: 引擎只加载 data/strategies/{custom,ai,composite} 与研究模板目录,
原 25 个内置策略一次性迁移为用户自定义文件(ID 不变, 引用零迁移);
研究模板移至 app/strategy/research, 打包 spec 同步; 新装环境策略库为空
- 信号: 管线不再硬编码任何信号表达式; 涨跌停判定价成为运行时列
limit_up_price/limit_down_price(生效价∓0.005 容差), 20 个信号转为
data/user_data/custom_signals 定义(显式 column 沿用 signal_* 原列名);
依赖解析/注入顺序/当日路径 prev-join 全部定义驱动; 语义统一为历史路径
口径(顺带修正当日路径 BOLL 比较符与翘板/炸板空值两处既有偏差)
- 前端: 信号库单列表(全部可编辑), SignalPicker/监控选项/信号标签全走
定义接口; 回测页新增免责声明(模拟性质/数据源准确性不作保证/不构成
投资建议)
- 测试: 25 个策略夹具与 20 个信号种子入库 tests/fixtures, 受影响测试
全部自包含化(不依赖运行目录用户数据); 77 万行 MA 死叉新旧表达式对拍
逐行一致; 回测实跑 45 笔卖点信号出场验证矩阵链路
- 同批包含工作区既有进度: 策略结果 ext 列同日投影修复(含测试)、数据源插件、fuyao/auth/api_gateway/data_integrity 调整、README 信号库
描述与 strategy.md 导入路径补充
验证: 后端 2592 passed(空数据目录 CI 模拟 2588 passed, 4 例为模拟环境
伪影复验排除); 前端 vitest 125 passed + tsc 0 错 + vite build 通过
627 lines
26 KiB
Python
627 lines
26 KiB
Python
"""自选页 enriched 端点的 LEFT JOIN 回归测试.
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核心契约 (修复 inner-filter bug 后):
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自选列表里的每一只标的都必须出现在返回结果中, 即使它不在 enriched 缓存里
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(新股 / 冷门股 / 新用户未同步). 缺失标的的指标字段为 null, 前端渲染为 "—".
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旧 bug: `df_e.filter(is_in(stock_symbols))` 以 enriched 为主表, 会把不在缓存
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universe 里的自选静默丢弃.
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"""
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from __future__ import annotations
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from datetime import date
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from types import SimpleNamespace
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import polars as pl
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import pytest
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from app.api import watchlist as wl_api
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class _FakeRepo:
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"""最小化 repo mock: 只实现 watchlist_enriched 调用到的方法."""
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def __init__(self, enriched_df, enriched_date, etf_df=None, etf_date=None,
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instruments_df=None, name_map=None, etf_set=None,
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index_df=None, index_date=None, index_set=None,
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history_span=None, hist_df=None, history_raises=False):
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self._enriched = enriched_df
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self._enriched_date = enriched_date
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self._etf = etf_df
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self._etf_date = etf_date
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self._index = index_df
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self._index_date = index_date
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self._instruments = instruments_df or pl.DataFrame()
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self._name_map = name_map or {}
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self._etf_set = etf_set or set()
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self._index_set = index_set or set()
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# 加入后涨跌幅基准价所需的内存历史缓存 (未注入时端点按 null 降级)
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self._history_span = history_span
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self._hist = hist_df if hist_df is not None else pl.DataFrame()
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self._history_raises = history_raises
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def get_enriched_history_span(self):
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return self._history_span
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def get_enriched_range(self, start, end, symbols=None, columns=None):
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if self._history_raises:
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raise RuntimeError("history cache exploded")
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if self._hist.is_empty():
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return self._hist
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# 与真实实现同语义: 按日期区间 + symbol 过滤
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return self._hist.filter(
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(pl.col("date") >= start) & (pl.col("date") <= end)
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& pl.col("symbol").is_in(list(symbols or []))
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)
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def get_enriched_latest(self):
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return self._enriched, self._enriched_date
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def get_enriched_latest_asset(self, asset):
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if asset == "etf":
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etf = self._etf if self._etf is not None else pl.DataFrame()
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return etf, self._etf_date
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if asset == "index":
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idx = self._index if self._index is not None else pl.DataFrame()
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return idx, self._index_date
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return pl.DataFrame(), None
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def get_etf_symbol_set(self):
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return self._etf_set
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def get_index_symbol_set(self):
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return self._index_set
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def get_instruments(self):
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return self._instruments
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def get_name_map(self, symbols):
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return {s: n for s, n in self._name_map.items() if s in (symbols or [])}
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def _make_request(repo):
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return SimpleNamespace(app=SimpleNamespace(state=SimpleNamespace(repo=repo)))
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def _enriched_df(symbols_data):
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"""symbols_data: [(symbol, close, change_pct, amount), ...]"""
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return pl.DataFrame(
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[{"symbol": s, "close": c, "change_pct": p, "amount": a, "turnover_rate": 1.0}
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for s, c, p, a in symbols_data],
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schema_overrides={
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"close": pl.Float64, "change_pct": pl.Float64,
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"amount": pl.Float64, "turnover_rate": pl.Float64,
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},
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)
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def test_watchlist_symbol_not_in_enriched_still_returned(monkeypatch):
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"""核心回归: 自选里有但 enriched 缓存里没有的标的, 必须仍返回一行 (指标 null)."""
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# enriched 缓存只覆盖 600519, 不覆盖 999999 (新加的冷门股)
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monkeypatch.setattr(wl_api.watchlist, "list_symbols",
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lambda: [{"symbol": "600519"}, {"symbol": "999999"}])
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repo = _FakeRepo(
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enriched_df=_enriched_df([("600519", 1800.0, 1.2, 1e9)]),
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enriched_date="2026-07-08",
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name_map={"600519": "贵州茅台", "999999": "未知股"},
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)
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# ext_columns 显式传 None 绕过 FastAPI Query 默认值
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res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
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syms = [r["symbol"] for r in res["rows"]]
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assert "600519" in syms, "缓存里有的标的必须返回"
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assert "999999" in syms, "缓存里没有的自选标的也必须返回 (修复的核心)"
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# 缺失标的指标应为 null
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row_999 = next(r for r in res["rows"] if r["symbol"] == "999999")
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assert row_999["close"] is None, f"缺失指标应为 null, 实际: {row_999['close']}"
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assert row_999["name"] == "未知股", "name 走 get_name_map, 应正常返回"
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# 命中标的指标正常
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row_519 = next(r for r in res["rows"] if r["symbol"] == "600519")
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assert row_519["close"] == 1800.0
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def test_all_watchlist_missing_from_enriched(monkeypatch):
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"""股票 enriched 缓存未就绪时, 自选仍返回占位行."""
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syms = ["000001", "000002"]
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monkeypatch.setattr(wl_api.watchlist, "list_symbols",
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lambda: [{"symbol": s} for s in syms])
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repo = _FakeRepo(
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enriched_df=pl.DataFrame(schema={"symbol": pl.Utf8}),
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enriched_date=None,
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)
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res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
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assert [r["symbol"] for r in res["rows"]] == syms
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assert all(r.get("close") is None for r in res["rows"])
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assert res["as_of"] is None
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def test_partial_coverage_preserves_count(monkeypatch):
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"""多只自选, 部分覆盖: 返回行数必须 == 自选只数."""
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syms = ["600519", "000001", "999888", "888999"]
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monkeypatch.setattr(wl_api.watchlist, "list_symbols",
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lambda: [{"symbol": s} for s in syms])
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repo = _FakeRepo(
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enriched_df=_enriched_df([
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("600519", 1800.0, 1.2, 1e9),
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("000001", 15.0, 0.3, 2e9),
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]),
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enriched_date="2026-07-08",
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)
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res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
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assert len(res["rows"]) == len(syms), \
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f"返回行数应等于自选数 {len(syms)}, 实际 {len(res['rows'])}"
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returned = {r["symbol"] for r in res["rows"]}
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assert returned == set(syms)
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def test_etf_not_in_enriched_still_returned(monkeypatch):
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"""ETF 同样: 自选了但 ETF enriched 缓存没有的, 也应返回 (指标 null)."""
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monkeypatch.setattr(wl_api.watchlist, "list_symbols",
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lambda: [{"symbol": "510300"}, {"symbol": "599999"}])
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repo = _FakeRepo(
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enriched_df=pl.DataFrame(schema={"symbol": pl.Utf8}), # 无股票自选
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enriched_date=None,
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etf_df=_enriched_df([("510300", 4.0, 0.5, 1e8)]),
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etf_date="2026-07-08",
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etf_set={"510300", "599999"},
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)
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res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
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syms = [r["symbol"] for r in res["rows"]]
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assert "510300" in syms
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assert "599999" in syms, "ETF enriched 缺失的自选标的也必须返回"
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row_missing = next(r for r in res["rows"] if r["symbol"] == "599999")
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assert row_missing["close"] is None
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def test_all_etf_watchlist_missing_from_enriched(monkeypatch):
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"""ETF enriched 缓存未就绪时, 自选仍返回占位行."""
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syms = ["510300", "599999"]
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monkeypatch.setattr(wl_api.watchlist, "list_symbols",
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lambda: [{"symbol": s} for s in syms])
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repo = _FakeRepo(
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enriched_df=pl.DataFrame(schema={"symbol": pl.Utf8}),
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enriched_date=None,
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etf_df=pl.DataFrame(schema={"symbol": pl.Utf8}),
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etf_date=None,
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etf_set=set(syms),
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)
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res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
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assert [r["symbol"] for r in res["rows"]] == syms
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assert all(r.get("close") is None for r in res["rows"])
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assert res["as_of"] is None
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def test_mixed_watchlist_keeps_pending_stock_rows(monkeypatch):
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"""股票缓存未就绪不应影响 ETF 行, 且保持自选原始顺序."""
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syms = ["510300", "000001", "510500"]
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monkeypatch.setattr(wl_api.watchlist, "list_symbols",
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lambda: [{"symbol": s} for s in syms])
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repo = _FakeRepo(
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enriched_df=pl.DataFrame(schema={"symbol": pl.Utf8}),
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enriched_date=None,
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etf_df=_enriched_df([("510300", 4.0, 0.5, 1e8), ("510500", 6.0, -0.2, 2e8)]),
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etf_date="2026-07-08",
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etf_set={"510300", "510500"},
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)
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res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
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assert [r["symbol"] for r in res["rows"]] == syms
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assert next(r for r in res["rows"] if r["symbol"] == "000001").get("close") is None
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assert next(r for r in res["rows"] if r["symbol"] == "510300")["close"] == 4.0
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assert res["as_of"] == "2026-07-08"
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def test_mixed_watchlist_keeps_pending_etf_rows(monkeypatch):
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"""ETF 缓存未就绪不应影响股票行, 且保持自选原始顺序."""
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syms = ["510300", "000001", "510500"]
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monkeypatch.setattr(wl_api.watchlist, "list_symbols",
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lambda: [{"symbol": s} for s in syms])
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repo = _FakeRepo(
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enriched_df=_enriched_df([("000001", 15.0, 0.3, 2e9)]),
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enriched_date="2026-07-08",
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etf_df=pl.DataFrame(schema={"symbol": pl.Utf8}),
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etf_date=None,
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etf_set={"510300", "510500"},
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)
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res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
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assert [r["symbol"] for r in res["rows"]] == syms
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assert next(r for r in res["rows"] if r["symbol"] == "000001")["close"] == 15.0
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assert all(next(r for r in res["rows"] if r["symbol"] == symbol).get("close") is None
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for symbol in ("510300", "510500"))
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assert res["as_of"] == "2026-07-08"
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def test_watchlist_enriched_index_branch(monkeypatch):
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"""自选含指数: 行走 index enriched, asset_type=index, 名称回填, 股票/ETF 行不受影响。
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断言 (计划 Task 4 Step 1):
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- 指数行存在, close == 3000.0, asset_type == "index", name == "上证指数"
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- 指数行 turnover_rate 为 None (列不存在或 null, 不报错)
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- 股票行 asset_type == "stock"; ETF 行 == "etf"
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- as_of == min(股票日期, etf日期, index日期)
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"""
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monkeypatch.setattr(wl_api.watchlist, "list_symbols",
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lambda: [{"symbol": "600000.SH"}, {"symbol": "510300.SH"},
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{"symbol": "000001.SH"}])
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repo = _FakeRepo(
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enriched_df=_enriched_df([("600000.SH", 10.0, 0.3, 2e9)]),
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enriched_date="2026-07-23",
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etf_df=_enriched_df([("510300.SH", 4.0, 0.5, 1e8)]),
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etf_date="2026-07-24",
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etf_set={"510300.SH"},
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index_df=pl.DataFrame([{"symbol": "000001.SH", "close": 3000.0, "change_pct": 0.01,
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"amount": 1e9, "ma5": 2990.0}]),
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index_date="2026-07-24",
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index_set={"000001.SH"},
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name_map={"600000.SH": "浦发银行", "510300.SH": "沪深300ETF", "000001.SH": "上证指数"},
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)
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res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
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rows = {r["symbol"]: r for r in res["rows"]}
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# 指数行
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idx = rows["000001.SH"]
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assert idx["close"] == 3000.0
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assert idx["asset_type"] == "index"
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assert idx["name"] == "上证指数"
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# 指数无换手率: 列缺失或 null, 不报错
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assert idx.get("turnover_rate") is None
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# 股票行 / ETF 行 asset_type
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assert rows["600000.SH"]["asset_type"] == "stock"
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assert rows["510300.SH"]["asset_type"] == "etf"
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# as_of == min(三类缓存日期)
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assert res["as_of"] == "2026-07-23"
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def _quote_df(rows):
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"""rows: [(symbol, close, prev_close, volume, open, high, low), ...]"""
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return pl.DataFrame(
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[{"symbol": s, "close": c, "prev_close": pc, "volume": v,
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"open": o, "high": h, "low": lo, "amount": 1e9, "change_pct": 1.0}
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for s, c, pc, v, o, h, lo in rows],
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schema_overrides={k: pl.Float64 for k in
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("close", "prev_close", "volume", "open", "high", "low",
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"amount", "change_pct")},
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)
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def test_watchlist_enriched_limit_prices_and_quote_cols(monkeypatch):
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"""昨收/成交量透传; 股票行涨跌停价按板块现算 (划断后 ST=10%), ETF 行置 null。
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涨停价口径: prev_close x (1+pct) 整数分半进位 (polars_limit_price)。
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- 600519.SH 主板 10%: 1800.0 → 涨停 1980.00 / 跌停 1620.00
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- 300001.SZ 创业 20%: 10.0 → 12.00 / 8.00
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- 600029.SH 主板 ST (2026-07-08 ≥ 划断日) 10%: 10.0 → 11.00 / 9.00
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"""
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monkeypatch.setattr(wl_api.watchlist, "list_symbols",
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lambda: [{"symbol": s} for s in
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("600519.SH", "300001.SZ", "600029.SH", "510300.SH")])
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repo = _FakeRepo(
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enriched_df=_quote_df([
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("600519.SH", 1900.0, 1800.0, 123456.0, 1810.0, 1950.0, 1799.0),
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("300001.SZ", 10.5, 10.0, 88_000.0, 10.1, 10.8, 9.9),
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("600029.SH", 10.6, 10.0, 55_000.0, 10.0, 10.9, 9.7),
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]),
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enriched_date="2026-07-08",
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etf_df=_quote_df([("510300.SH", 4.1, 4.0, 900_000.0, 4.0, 4.2, 3.9)]),
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etf_date="2026-07-08",
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etf_set={"510300.SH"},
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name_map={
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"600519.SH": "贵州茅台", "300001.SZ": "特锐德", "600029.SH": "ST 南航",
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"510300.SH": "沪深300ETF",
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},
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)
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res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
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rows = {r["symbol"]: r for r in res["rows"]}
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# 昨收/成交量 透传 (此前被 _WATCHLIST_COLS 裁掉)
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row = rows["600519.SH"]
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assert row["prev_close"] == 1800.0
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assert row["volume"] == 123456.0
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assert row["open"] == 1810.0 and row["high"] == 1950.0 and row["low"] == 1799.0
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# 股票行涨跌停价
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assert rows["600519.SH"]["limit_up_price"] == 1980.0
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assert rows["600519.SH"]["limit_down_price"] == 1620.0
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assert rows["300001.SZ"]["limit_up_price"] == 12.0
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assert rows["300001.SZ"]["limit_down_price"] == 8.0
|
|
# 主板 ST 在 2026-07-06 划断后恢复 10%
|
|
assert rows["600029.SH"]["limit_up_price"] == 11.0
|
|
assert rows["600029.SH"]["limit_down_price"] == 9.0
|
|
|
|
# ETF 行: prev_close/volume 正常透传, 涨跌停价置 null
|
|
etf = rows["510300.SH"]
|
|
assert etf["prev_close"] == 4.0 and etf["volume"] == 900_000.0
|
|
assert etf["limit_up_price"] is None
|
|
assert etf["limit_down_price"] is None
|
|
|
|
|
|
def test_watchlist_enriched_limit_prices_legacy_st(monkeypatch):
|
|
"""数据日在 2026-07-06 划断之前: 主板 ST 涨跌幅为 5% 老规则, 非 ST 不受影响。"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: [{"symbol": s} for s in ("600029.SH", "600519.SH")])
|
|
repo = _FakeRepo(
|
|
enriched_df=_quote_df([
|
|
("600029.SH", 10.2, 10.0, 66_000.0, 10.0, 10.4, 9.8),
|
|
("600519.SH", 1900.0, 1800.0, 123456.0, 1810.0, 1950.0, 1799.0),
|
|
]),
|
|
enriched_date="2026-07-01",
|
|
name_map={"600029.SH": "ST 南航", "600519.SH": "贵州茅台"},
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
rows = {r["symbol"]: r for r in res["rows"]}
|
|
|
|
assert rows["600029.SH"]["limit_up_price"] == 10.5
|
|
assert rows["600029.SH"]["limit_down_price"] == 9.5
|
|
assert rows["600519.SH"]["limit_up_price"] == 1980.0
|
|
|
|
|
|
# ===== 加入日期 / 加入后涨跌幅 =====
|
|
|
|
def _hist_df(rows):
|
|
"""rows: [(symbol, date, close), ...]"""
|
|
return pl.DataFrame(
|
|
[{"symbol": s, "date": d, "close": c} for s, d, c in rows],
|
|
schema={"symbol": pl.Utf8, "date": pl.Date, "close": pl.Float64},
|
|
)
|
|
|
|
|
|
def _entries(*pairs):
|
|
"""(symbol, added_at) 对 → list_symbols 返回值"""
|
|
return [{"symbol": s, "added_at": a} for s, a in pairs]
|
|
|
|
|
|
def _span():
|
|
return (date(2026, 9, 1), date(2026, 9, 18))
|
|
|
|
|
|
def test_pct_since_added_baseline_is_added_day_close(monkeypatch):
|
|
"""正常路径: 基准 = 加入日收盘 (<= 语义), 结果为小数口径, added_at 原样透传。"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: _entries(("600519.SH", "2026-09-10T03:21:07")))
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 11.0, 1.0, 1e9)]),
|
|
enriched_date="2026-09-18",
|
|
history_span=_span(),
|
|
hist_df=_hist_df([("600519.SH", date(2026, 9, 9), 9.0),
|
|
("600519.SH", date(2026, 9, 10), 10.0),
|
|
("600519.SH", date(2026, 9, 11), 10.5)]),
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
row = res["rows"][0]
|
|
|
|
# 基准取 09-10 收盘 10.0 (不是更早的 9.0, 也不是更晚的 10.5)
|
|
assert row["pct_since_added"] == pytest.approx(11.0 / 10.0 - 1.0)
|
|
# 小数口径: 10% 存 0.1 而非 10 (与 momentum_* 一致, 前端 fmtPct 期望小数)
|
|
assert row["pct_since_added"] == pytest.approx(0.1)
|
|
assert row["pct_since_added"] < 1, "必须是小数口径, 不能写成百分数"
|
|
# added_at 原样透传 (前端负责 UTC→北京换算)
|
|
assert row["added_at"] == "2026-09-10T03:21:07"
|
|
# 中间量不得泄漏到响应
|
|
assert "base_close" not in row
|
|
|
|
|
|
def test_pct_since_added_snaps_back_to_previous_trading_day(monkeypatch):
|
|
"""周末/节假日加入: 基准回落到 <= 加入日的最近交易日 (周五), 而非无值。"""
|
|
# 2026-09-19 是周六 (北京时间), 无 bar
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: _entries(("600519.SH", "2026-09-19T02:00:00")))
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 13.2, 1.0, 1e9)]),
|
|
enriched_date="2026-09-18",
|
|
history_span=_span(),
|
|
hist_df=_hist_df([("600519.SH", date(2026, 9, 17), 10.0),
|
|
("600519.SH", date(2026, 9, 18), 12.0)]),
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
assert res["rows"][0]["pct_since_added"] == pytest.approx(13.2 / 12.0 - 1.0)
|
|
|
|
|
|
def test_pct_since_added_uses_beijing_date_not_utc(monkeypatch):
|
|
"""added_at 是 naive UTC: 北京时间 09-19 04:30 加入的, 基准必须取 09-19 收盘。
|
|
|
|
该字符串的 UTC 日期是 09-18 —— 若按 UTC 日取基准会错取到 10.0 (结果 1.2),
|
|
正确结果 0.1。两者可区分, 故本用例能捕捉口径回归。
|
|
"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: _entries(("600519.SH", "2026-09-18T20:30:00")))
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 22.0, 1.0, 1e9)]),
|
|
enriched_date="2026-09-19",
|
|
history_span=(date(2026, 9, 1), date(2026, 9, 19)),
|
|
hist_df=_hist_df([("600519.SH", date(2026, 9, 18), 10.0),
|
|
("600519.SH", date(2026, 9, 19), 20.0)]),
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
pct = res["rows"][0]["pct_since_added"]
|
|
assert pct == pytest.approx(22.0 / 20.0 - 1.0), \
|
|
f"基准应取北京日 09-19 的收盘 20.0; 按 UTC 日会得到 1.2, 实际 {pct}"
|
|
|
|
|
|
@pytest.mark.parametrize("history_span,history_raises,keeps_added_at", [
|
|
(None, False, True), # 历史缓存不可用 (冷启动/预热中): 只降级涨跌幅
|
|
(_span(), True, False), # 取数抛异常: 整个装饰块降级
|
|
])
|
|
def test_pct_since_added_degrades_without_breaking_rows(
|
|
monkeypatch, history_span, history_raises, keeps_added_at,
|
|
):
|
|
"""装饰列取不到时不得 fail 整个请求: 返回完整 rows, 新列为 null。"""
|
|
syms = ["600519.SH", "000001.SZ"]
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: _entries(("600519.SH", "2026-09-10T03:00:00"),
|
|
("000001.SZ", "2026-09-11T03:00:00")))
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 11.0, 1.0, 1e9),
|
|
("000001.SZ", 15.0, 0.3, 2e9)]),
|
|
enriched_date="2026-09-18",
|
|
history_span=history_span,
|
|
history_raises=history_raises,
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
|
|
assert [r["symbol"] for r in res["rows"]] == syms
|
|
assert all(r["pct_since_added"] is None for r in res["rows"])
|
|
assert all(bool(r["added_at"]) is keeps_added_at for r in res["rows"])
|
|
# 中间量不得残留在响应里
|
|
assert all("base_close" not in r for r in res["rows"])
|
|
# 主表数据完好
|
|
assert res["rows"][0]["close"] == 11.0
|
|
|
|
|
|
def test_pct_since_added_null_when_added_before_history_span(monkeypatch):
|
|
"""加入日早于可查询历史范围 (约 300 天) 的标的显式降级, 同表其它标的不受影响。"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: _entries(("600519.SH", "2026-09-10T03:00:00"),
|
|
("000001.SZ", "2025-01-05T03:00:00")))
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 11.0, 1.0, 1e9),
|
|
("000001.SZ", 15.0, 0.3, 2e9)]),
|
|
enriched_date="2026-09-18",
|
|
history_span=_span(), # 只覆盖 2026-09-01 起
|
|
hist_df=_hist_df([("600519.SH", date(2026, 9, 10), 10.0)]),
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
rows = {r["symbol"]: r for r in res["rows"]}
|
|
|
|
assert rows["000001.SZ"]["pct_since_added"] is None, "超窗应降级为 null"
|
|
assert rows["000001.SZ"]["added_at"] == "2025-01-05T03:00:00", "加入日期仍应返回"
|
|
assert rows["600519.SH"]["pct_since_added"] == pytest.approx(0.1), \
|
|
"一只超窗不得拖垮同表其它标的"
|
|
|
|
|
|
def test_added_at_empty_string_normalized_to_null(monkeypatch):
|
|
"""老 schema 迁移补的空串归一为 null, 不抛异常也不渲染成空日期。"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: _entries(("600519.SH", "")))
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 11.0, 1.0, 1e9)]),
|
|
enriched_date="2026-09-18",
|
|
history_span=_span(),
|
|
hist_df=_hist_df([("600519.SH", date(2026, 9, 10), 10.0)]),
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
row = res["rows"][0]
|
|
assert row["added_at"] is None
|
|
assert row["pct_since_added"] is None
|
|
|
|
|
|
def test_pct_since_added_null_for_etf_row(monkeypatch):
|
|
"""ETF 显式降级: 加入日期正常返回, 加入后涨跌幅为 null。"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: _entries(("510300.SH", "2026-09-10T03:00:00")))
|
|
repo = _FakeRepo(
|
|
enriched_df=pl.DataFrame(schema={"symbol": pl.Utf8}),
|
|
enriched_date=None,
|
|
etf_df=_enriched_df([("510300.SH", 4.0, 0.5, 1e8)]),
|
|
etf_date="2026-09-18",
|
|
etf_set={"510300.SH"},
|
|
history_span=_span(),
|
|
hist_df=_hist_df([("510300.SH", date(2026, 9, 10), 3.8)]),
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
row = res["rows"][0]
|
|
assert row["added_at"] == "2026-09-10T03:00:00"
|
|
assert row["pct_since_added"] is None, "ETF 无历史缓存, 显式降级为 —"
|
|
|
|
|
|
def test_pct_since_added_null_for_invalid_baseline(monkeypatch):
|
|
"""基准价非正/NaN 时返回 null, 不得产出 inf 或 NaN 这类会污染前端排序的值。"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: _entries(("600519.SH", "2026-09-10T03:00:00"),
|
|
("000001.SZ", "2026-09-10T03:00:00")))
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 11.0, 1.0, 1e9),
|
|
("000001.SZ", 15.0, 0.3, 2e9)]),
|
|
enriched_date="2026-09-18",
|
|
history_span=_span(),
|
|
hist_df=_hist_df([("600519.SH", date(2026, 9, 10), 0.0),
|
|
("000001.SZ", date(2026, 9, 10), float("nan"))]),
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
for row in res["rows"]:
|
|
assert row["pct_since_added"] is None, f"{row['symbol']} 应降级为 null"
|
|
|
|
|
|
def test_empty_watchlist_returns_no_rows(monkeypatch):
|
|
"""空自选: 保持既有早退契约, 不因新字段改变响应结构。"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols", lambda: [])
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 11.0, 1.0, 1e9)]),
|
|
enriched_date="2026-09-18",
|
|
history_span=_span(),
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
assert res == {"rows": [], "as_of": None, "elapsed_ms": 0,
|
|
"dates": {"stock": None, "etf": None, "index": None}}
|
|
|
|
|
|
# ===== 按资产类型行情日期 (dates) =====
|
|
|
|
def test_dates_reports_per_asset_type_quote_dates(monkeypatch):
|
|
"""dates 契约: 股票当日实时 / ETF 停在旧日 (未开实时拉退回旧日K缓存)。
|
|
|
|
前端分时缩略图续画只对 dates[asset_type] == 当日 的标的用行情 close 拼尾K;
|
|
ETF 旧日期 (如 09-24 收盘 1.105) 不得被拼进当日 1.03x 的分钟序列尾部。
|
|
"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: [{"symbol": "600519.SH"}, {"symbol": "510300.SH"}])
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 1900.0, 1.2, 1e9)]),
|
|
enriched_date="2026-10-08",
|
|
etf_df=_enriched_df([("510300.SH", 4.0, 0.5, 1e8)]),
|
|
etf_date="2026-09-29",
|
|
etf_set={"510300.SH"},
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
|
|
assert res["dates"] == {"stock": "2026-10-08", "etf": "2026-09-29", "index": None}
|
|
# 全局 as_of 取 min, 与分类型 dates 各自独立 (as_of 分不清哪类过期)
|
|
assert res["as_of"] == "2026-09-29"
|
|
|
|
|
|
def test_dates_etf_none_when_no_etf_in_watchlist(monkeypatch):
|
|
"""自选无 ETF 时不触发 ETF 缓存懒加载 → dates.etf = None (前端按不新鲜处理)。
|
|
|
|
锁定端点「仅自选真的含 ETF 才去加载」的懒加载契约不被 dates 字段破坏。
|
|
"""
|
|
monkeypatch.setattr(wl_api.watchlist, "list_symbols",
|
|
lambda: [{"symbol": "600519.SH"}])
|
|
repo = _FakeRepo(
|
|
enriched_df=_enriched_df([("600519.SH", 1900.0, 1.2, 1e9)]),
|
|
enriched_date="2026-10-08",
|
|
# etf_df 有数据但自选无 ETF: 端点不应调用 get_enriched_latest_asset("etf")
|
|
etf_df=_enriched_df([("510300.SH", 4.0, 0.5, 1e8)]),
|
|
etf_date="2026-09-29",
|
|
)
|
|
|
|
res = wl_api.watchlist_enriched(_make_request(repo), ext_columns=None)
|
|
|
|
assert res["dates"]["stock"] == "2026-10-08"
|
|
assert res["dates"]["etf"] is None
|