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
107 lines
4.1 KiB
Python
107 lines
4.1 KiB
Python
"""M7.3 行情口径测试：Repository 读路径按 adjust 过滤（不复权主口径），spec 记录口径。
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混合行场景：同 symbol/date 存在 tushare/none 与 sina/qfq 行时，研究读取
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（get_range_many / stream）默认只取 adjust=none —— 消除「混合口径污染因子」风险。
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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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from app.domain.entities.market import DailyBar
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from app.domain.entities.research import ResearchSpec
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from app.domain.entities.selection import SelectionQuery
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from app.infrastructure.persistence.sqlalchemy.base import Base
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from app.infrastructure.persistence.sqlalchemy.repositories.market_impl import (
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SqlAlchemyDailyBarRepository,
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)
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from sqlalchemy import create_engine
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from sqlalchemy.orm import Session
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_D = date(2024, 6, 3)
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_D2 = date(2024, 6, 4)
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_D3 = date(2024, 6, 5)
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def _bar(adjust: str, close: str, source: str = "tushare", day=None) -> DailyBar:
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return DailyBar(
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symbol="600519.SH",
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trade_date=day or _D,
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source=source,
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adjust=adjust,
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open=Decimal("100"), high=Decimal("101"), low=Decimal("99"),
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close=Decimal(close), volume=Decimal("1000"), amount=Decimal("100000"),
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)
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class TestAdjustFilter:
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def _session(self, tmp_path) -> Session:
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engine = create_engine(f"sqlite:///{tmp_path / 'adj.db'}", future=True)
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Base.metadata.create_all(engine)
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return Session(engine)
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def test_get_range_many_filters_adjust(self, tmp_path) -> None:
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with self._session(tmp_path) as session:
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repo = SqlAlchemyDailyBarRepository(session)
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# 唯一键 (symbol, trade_date)：同键共存不可能 —— 用连续三天模拟
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# none 主口径两天 + sina/qfq 兜底一天
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repo.upsert_many(
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[
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_bar("none", "1700", day=_D),
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_bar("none", "1710", day=_D2),
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_bar("qfq", "1680", source="sina", day=_D3),
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]
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)
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session.commit()
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none_rows = repo.get_range_many(["600519.SH"], _D, _D3, adjust="none")
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assert len(none_rows) == 2 and {float(r.close) for r in none_rows} == {1700, 1710}
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qfq_rows = repo.get_range_many(["600519.SH"], _D, _D3, adjust="qfq")
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assert len(qfq_rows) == 1 and float(qfq_rows[0].close) == 1680
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def test_stream_filters_adjust(self, tmp_path) -> None:
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with self._session(tmp_path) as session:
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repo = SqlAlchemyDailyBarRepository(session)
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repo.upsert_many(
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[
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_bar("none", "1700", day=_D),
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_bar("none", "1710", day=_D2),
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_bar("qfq", "1680", source="sina", day=_D3),
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]
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)
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session.commit()
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rows = list(
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repo.stream_range_many_columns(
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["600519.SH"], _D, _D3, ["close"], adjust="none"
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)
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)
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assert len(rows) == 2 and {float(r[-1]) for r in rows} == {1700, 1710}
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qrows = list(
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repo.stream_range_many_columns(
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["600519.SH"], _D, _D3, ["close"], adjust="qfq"
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)
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)
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assert len(qrows) == 1 and float(qrows[0][-1]) == 1680
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class TestSpecRecordsAdjustment:
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def test_research_spec_default_and_field(self) -> None:
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spec = ResearchSpec(
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type="backtest",
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factors=[{"name": "momentum_60", "weight": 1}],
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period=(date(2024, 1, 1), date(2024, 6, 1)),
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)
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assert spec.price_adjustment == "none"
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snap = spec.model_dump(mode="json")
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assert snap["price_adjustment"] == "none" # 结果 config_snapshot 可溯源
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def test_selection_query_adjustment_in_snapshot(self) -> None:
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q = SelectionQuery(factors=[{"name": "momentum_60", "weight": 1}], top_n=5)
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assert q.price_adjustment == "none"
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assert q.model_dump()["price_adjustment"] == "none"
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q2 = SelectionQuery(
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factors=[{"name": "momentum_60", "weight": 1}], top_n=5, price_adjustment="qfq"
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)
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assert q2.price_adjustment == "qfq"
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