Simon
ef09d5b419
- DailyBarRepository.get_range_many / stream_range_many_columns 增加 adjust 参数 （默认 'none'）→ SQL 层过滤口径，消除 stock_daily 混 source/adjust 污染因子的风险 - ResearchSpec / SelectionQuery 增加 price_adjustment（none|qfq），随 config_snapshot 落库可溯源；ResearchService._load_daily 与 SelectionService 装配按口径取数 - tests/test_price_adjustment.py：repo 读取按 adjust 过滤（none/qfq 各自命中）、 spec 默认与字段记录；全量 pytest 通过
229 lines
8.4 KiB
Python
229 lines
8.4 KiB
Python
"""M6.2 条件选股测试：结构化条件（static.*/tech 字段与因子/fundamental.*）与未来函数防护。
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Fake（内存）Repository；财务行显式携带 announce_date 验证 as_of 可见性。
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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 decimal import Decimal
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import pandas as pd
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import pytest
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from app.application.services.selection_service import SelectionService
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from app.domain.entities.market import FinancialIndicator, Stock
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from app.domain.entities.research import UniverseSpec
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from app.domain.entities.selection import SelectionQuery
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from conftest_quant import bars_dataframe_to_daily_bars, synthetic_daily
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_SYMS = ["600000.SH", "600001.SH", "600002.SH"]
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def _stocks(industries: dict[str, str] | None = None) -> list[Stock]:
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industries = industries or {}
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return [
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Stock(
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symbol=s, name=f"股{i}", industry=industries.get(s),
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list_date=date(1999, 1, 1),
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)
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for i, s in enumerate(_SYMS)
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]
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class _MemDailyRepo:
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def __init__(self, df: pd.DataFrame) -> None:
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self._bars_all = bars_dataframe_to_daily_bars(df)
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def get_range(self, symbol, start, end):
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return [b for b in self._bars_all if b.symbol == symbol and start <= b.trade_date <= end]
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def get_range_many(self, symbols, start, end, adjust="none"):
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syms = set(symbols)
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return [b for b in self._bars_all if b.symbol in syms and start <= b.trade_date <= end]
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def latest_date(self, symbol):
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rows = [b.trade_date for b in self._bars_all if b.symbol == symbol]
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return max(rows) if rows else None
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class _MemFinancialRepo:
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def __init__(self, rows: list[FinancialIndicator]) -> None:
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self._rows = rows
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def list_announced(self, symbol, as_of_date, report_start=None):
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return [
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r for r in self._rows
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if r.symbol == symbol and r.announce_date <= as_of_date
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and (report_start is None or r.report_date >= report_start)
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]
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def list_announced_many(self, symbols, as_of_date):
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syms = set(symbols)
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return [
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r for r in self._rows
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if r.symbol in syms and r.announce_date <= as_of_date
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]
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def _svc(df, stocks=None, fin_rows=None) -> SelectionService:
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return SelectionService(
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_MemStockRepo(stocks or _stocks()),
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_MemDailyRepo(df),
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_MemFinancialRepo(fin_rows or []),
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)
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class _MemStockRepo:
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def __init__(self, stocks) -> None:
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self._stocks = stocks
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def list(self):
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return self._stocks
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def get_by_symbol(self, symbol):
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return next((s for s in self._stocks if s.symbol == symbol), None)
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def _cond_query(conditions, **kw) -> SelectionQuery:
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base = dict(method="condition", conditions=conditions, as_of=date(2024, 12, 31))
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base.update(kw)
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return SelectionQuery(**base)
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class TestStaticCondition:
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def test_industry_filter(self) -> None:
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df = synthetic_daily({s: 0.002 for s in _SYMS}, n=320)
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industries = {_SYMS[0]: "白酒", _SYMS[1]: "银行", _SYMS[2]: "白酒"}
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svc = _svc(df, stocks=_stocks(industries))
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res = svc.select(
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_cond_query(
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[{"field": "static.industry", "op": "in", "value": ["白酒"]}],
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universe=UniverseSpec(min_listing_days=0),
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)
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)
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got = {c.symbol for c in res.candidates}
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assert got == {_SYMS[0], _SYMS[2]}
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assert res.statistics.selected == 2
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# 每候选带条件状态与理由
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assert all(c.filter_status for c in res.candidates)
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assert all(c.selection_reason for c in res.candidates)
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def test_static_ne(self) -> None:
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df = synthetic_daily({s: 0.002 for s in _SYMS}, n=320)
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industries = {_SYMS[0]: "白酒", _SYMS[1]: "银行", _SYMS[2]: "白酒"}
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svc = _svc(df, stocks=_stocks(industries))
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res = svc.select(
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_cond_query(
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[{"field": "static.industry", "op": "ne", "value": "白酒"}],
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universe=UniverseSpec(min_listing_days=0),
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)
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)
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assert {c.symbol for c in res.candidates} == {_SYMS[1]}
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class TestTechCondition:
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def test_momentum_gt_zero(self) -> None:
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df = synthetic_daily({_SYMS[0]: 0.008, _SYMS[1]: -0.008, _SYMS[2]: 0.002}, n=320)
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svc = _svc(df)
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res = svc.select(
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_cond_query(
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[{"field": "momentum_60", "op": "gt", "value": 0}],
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universe=UniverseSpec(min_listing_days=0),
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)
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)
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got = {c.symbol for c in res.candidates}
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assert _SYMS[1] not in got # 下跌股 60 日动量为负
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assert _SYMS[0] in got and _SYMS[2] in got
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def test_close_above_ma60_ref(self) -> None:
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df = synthetic_daily({_SYMS[0]: 0.006, _SYMS[1]: -0.006, _SYMS[2]: 0.0005}, n=320)
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svc = _svc(df)
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res = svc.select(
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_cond_query(
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[{"field": "close", "op": "gt", "ref": "ma60"}],
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universe=UniverseSpec(min_listing_days=0),
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)
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)
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got = {c.symbol for c in res.candidates}
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assert _SYMS[1] not in got # 下跌股收盘在 MA60 之下
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assert _SYMS[0] in got
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def test_lte_threshold(self) -> None:
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df = synthetic_daily({_SYMS[0]: 0.01, _SYMS[1]: -0.01, _SYMS[2]: 0.0001}, n=320)
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svc = _svc(df)
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res = svc.select(
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_cond_query(
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[{"field": "momentum_60", "op": "lte", "value": 0}],
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universe=UniverseSpec(min_listing_days=0),
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)
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)
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got = {c.symbol for c in res.candidates}
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assert _SYMS[1] in got
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assert _SYMS[0] not in got
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class TestFundamentalCondition:
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def _fin_rows(self) -> list[FinancialIndicator]:
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return [
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FinancialIndicator(
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symbol=_SYMS[0], report_date=date(2024, 9, 30), announce_date=date(2024, 10, 25),
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eps=Decimal("3.5"), roe=Decimal("20.0"), source="tushare",
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),
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# B：只在 as_of 之后才公告（未来数据）→ as_of 时不可见
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FinancialIndicator(
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symbol=_SYMS[1], report_date=date(2024, 9, 30), announce_date=date(2025, 3, 30),
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roe=Decimal("99.0"), source="tushare",
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),
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# C：roe 低于阈值
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FinancialIndicator(
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symbol=_SYMS[2], report_date=date(2024, 6, 30), announce_date=date(2024, 8, 20),
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roe=Decimal("5.0"), source="tushare",
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),
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]
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def test_roe_filter_no_future_leak(self) -> None:
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df = synthetic_daily({s: 0.002 for s in _SYMS}, n=320)
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svc = _svc(df, fin_rows=self._fin_rows())
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res = svc.select(
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_cond_query(
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[{"field": "fundamental.roe", "op": "gte", "value": 15}],
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universe=UniverseSpec(min_listing_days=0),
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),
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# 上面 helper 已带 as_of
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)
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got = {c.symbol for c in res.candidates}
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# A 可见且 roe=20 → 入选；B 公告在未来（防未来函数）→ 不入选；C roe=5 → 不入选
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assert got == {_SYMS[0]}
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def test_missing_financial_repo_raises(self) -> None:
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df = synthetic_daily({s: 0.002 for s in _SYMS}, n=320)
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svc = SelectionService(_MemStockRepo(_stocks()), _MemDailyRepo(df)) # 无财务 repo
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with pytest.raises(ValueError):
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svc.select(
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_cond_query(
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[{"field": "fundamental.roe", "op": "gte", "value": 15}],
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universe=UniverseSpec(min_listing_days=0),
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)
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)
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def test_as_of_earlier_excludes_announced_after(self) -> None:
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"""更早 as_of：A 的 roe=20 若在 as_of 之后才公告也不可见。"""
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df = synthetic_daily({s: 0.002 for s in _SYMS}, n=320)
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rows = [
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FinancialIndicator(
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symbol=_SYMS[0], report_date=date(2024, 6, 30),
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announce_date=date(2024, 10, 1), roe=Decimal("99.0"), source="tushare",
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)
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]
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svc = _svc(df, fin_rows=rows)
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res = svc.select(
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SelectionQuery(
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method="condition",
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conditions=[{"field": "fundamental.roe", "op": "gte", "value": 50}],
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as_of=date(2024, 9, 1), # announce(10-01) 尚未来
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universe=UniverseSpec(min_listing_days=0),
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)
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)
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assert {c.symbol for c in res.candidates} == set() # 无人可见 roe → 全部不通过
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