Simon
5bde8f9f5f
- ChartService qfq 基准改为该股最新因子（截至今天）归一：历史区间随最新除权 平移正确（v3 §20.5 Chart Display vs Execution basis 分离） - 显示口径与执行 basis 不一致时，成交/信号 marker 价格按当日因子换算到 K 线坐标系 （fill 早段价格在 qfq 下折算验证 100→50） - tests：qfq 回测 marker 折算 + selection 标记保留；全量 pytest 通过
300 lines
12 KiB
Python
300 lines
12 KiB
Python
"""M9-1 Chart Service/API 测试：K线/量/指标、复权显示折算、按股历史信号与选股、
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回测个股图（fills）、API 集成。使用 tmp SQLite + 真实 SQLAlchemy repo。
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"""
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from __future__ import annotations
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from datetime import date, datetime
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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.api import deps
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from app.application.services.chart_service import ChartService
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from app.domain.entities.market import AdjustFactor, Stock
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from app.domain.entities.research import (
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ExperimentRecord,
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ResearchSpec,
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)
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from app.infrastructure.persistence.sqlalchemy.base import Base
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from app.infrastructure.persistence.sqlalchemy.repositories.jobs_impl import (
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SqlAlchemyExperimentRepository,
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)
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from app.infrastructure.persistence.sqlalchemy.repositories.market_impl import (
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SqlAlchemyAdjustFactorRepository,
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SqlAlchemyDailyBarRepository,
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SqlAlchemyStockRepository,
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)
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from app.main import app
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from app.quant.engine import LocalEngine
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from fastapi.testclient import TestClient
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from sqlalchemy import create_engine
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from sqlalchemy.orm import sessionmaker
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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", "600003.SH"]
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def _daily_df(n=320) -> pd.DataFrame:
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return synthetic_daily({s: 0.004 - 0.001 * i for i, s in enumerate(_SYMS)}, n=n)
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@pytest.fixture()
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def seeded(tmp_path):
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engine = create_engine(f"sqlite:///{tmp_path / 'chart.db'}", future=True)
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Base.metadata.create_all(engine)
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Session = sessionmaker(bind=engine, expire_on_commit=False)
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df = _daily_df()
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with Session() as session:
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SqlAlchemyStockRepository(session).upsert_many(
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[Stock(symbol=s, name=f"测试股份{i}", list_date=date(1999, 1, 1))
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for i, s in enumerate(_SYMS)]
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)
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SqlAlchemyDailyBarRepository(session).upsert_many(bars_dataframe_to_daily_bars(df))
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session.commit()
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return engine, Session, df
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class TestChartServiceUnit:
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def test_stock_chart_ohlc_and_indicators(self, seeded) -> None:
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engine, Session, _df = seeded
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with Session() as session:
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svc = ChartService(
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SqlAlchemyStockRepository(session),
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SqlAlchemyDailyBarRepository(session),
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SqlAlchemyAdjustFactorRepository(session),
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)
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res = svc.stock_chart(_SYMS[0], date(2024, 1, 1), date(2024, 12, 31), "none")
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assert res.metadata.symbol == _SYMS[0]
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assert res.metadata.bar_count > 200
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assert res.bars[0].close and res.bars[-1].close
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assert "ma20" in res.indicators and "ma60" in res.indicators
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assert res.metadata.adjust_mode == "none"
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def test_qfq_display_conversion(self, seeded, tmp_path) -> None:
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"""前段因子 1.0 / 后段 2.0：qfq 显示把前段折半、hfq 前段不变后段翻倍。"""
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engine, Session, df = _seeded_with_factors(tmp_path)
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dates = sorted(df["trade_date"].unique())
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split = dates[len(dates) // 2]
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with Session() as session:
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repo = SqlAlchemyAdjustFactorRepository(session)
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rows = [
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AdjustFactor(symbol=_SYMS[0], trade_date=d,
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factor=Decimal("1.0") if d < split else Decimal("2.0"))
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for d in dates
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]
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repo.upsert_many(rows)
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session.commit()
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svc = ChartService(
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SqlAlchemyStockRepository(session),
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SqlAlchemyDailyBarRepository(session),
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SqlAlchemyAdjustFactorRepository(session),
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)
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none_chart = svc.stock_chart(_SYMS[0], dates[0], dates[-1], "none")
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none_c = none_chart.bars[0].close
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none_last = none_chart.bars[-1].close
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qfq_c = svc.stock_chart(_SYMS[0], dates[0], dates[-1], "qfq").bars[0].close
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hfq_c = svc.stock_chart(_SYMS[0], dates[0], dates[-1], "hfq").bars[0].close
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last_qfq = svc.stock_chart(_SYMS[0], dates[0], dates[-1], "qfq").bars[-1].close
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assert none_c is not None and qfq_c is not None and none_last is not None
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assert abs(none_c - qfq_c * 2) < 1e-3 # qfq 前段折半
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assert abs(none_c - hfq_c) < 1e-3 # hfq 前段不变
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assert abs(none_last - last_qfq) < 1e-3 # 最新段 qfq 基准=原价
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def test_backtest_chart_fills(self, seeded) -> None:
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engine, Session, df = seeded
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spec = ResearchSpec(
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type="backtest",
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universe={"exclude_st": False, "min_listing_days": 0,
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"symbols": [_SYMS[0], _SYMS[1], _SYMS[2]]},
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factors=[{"name": "momentum_60", "weight": 1.0}],
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selection={"top_n": 2},
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rebalance="monthly",
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period=(date(2024, 5, 1), date(2024, 12, 31)),
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)
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result = LocalEngine().run_backtest(df, spec)
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with Session() as session:
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svc = ChartService(
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SqlAlchemyStockRepository(session),
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SqlAlchemyDailyBarRepository(session),
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SqlAlchemyAdjustFactorRepository(session),
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)
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chart = svc.backtest_stock_chart(result, _SYMS[0], date(2024, 1, 1), date(2024, 12, 31))
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assert chart.metadata.execution_price_basis == "none"
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assert chart.bars and chart.metadata.bar_count > 100
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kinds = {f.kind for f in chart.fills}
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assert kinds <= {"fill_buy", "fill_sell"}
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# 有成交则有 fill 标记
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if result.trades:
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assert len(chart.fills) >= 2
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def _seeded_with_factors(tmp_path):
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engine = create_engine(f"sqlite:///{tmp_path / 'chart2.db'}", future=True)
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Base.metadata.create_all(engine)
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Session = sessionmaker(bind=engine, expire_on_commit=False)
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df = _daily_df()
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with Session() as session:
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SqlAlchemyStockRepository(session).upsert_many(
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[Stock(symbol=s, name=f"测试{i}", list_date=date(1999, 1, 1))
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for i, s in enumerate(_SYMS)]
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)
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SqlAlchemyDailyBarRepository(session).upsert_many(bars_dataframe_to_daily_bars(df))
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session.commit()
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return engine, Session, df
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@pytest.fixture()
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def client(tmp_path):
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engine, Session, df = _seeded_with_factors(tmp_path)
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def _session_override():
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with Session() as s:
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yield s
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app.dependency_overrides[deps.get_session] = _session_override
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# 预置一只实验（backtest），供 backtest chart API
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spec = ResearchSpec(
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type="backtest",
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universe={"exclude_st": False, "min_listing_days": 0, "symbols": _SYMS[:3]},
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factors=[{"name": "momentum_60", "weight": 1.0}],
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selection={"top_n": 2},
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rebalance="monthly",
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period=(date(2024, 5, 1), date(2024, 12, 31)),
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)
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result = LocalEngine().run_backtest(df, spec)
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with Session() as session:
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repo = SqlAlchemyExperimentRepository(session)
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repo.save(
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ExperimentRecord(
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id="EXP-CHART-1",
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kind="backtest",
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spec_json=spec.model_dump_json(),
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result_json=result.model_dump_json(),
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summary_text="chart-test",
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created_at=datetime.now(),
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)
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)
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session.commit()
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with TestClient(app) as c:
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yield c
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app.dependency_overrides.clear()
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class TestChartApi:
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def test_stock_chart_200(self, client) -> None:
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resp = client.get(
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f"/api/stocks/{_SYMS[0]}/chart?start=2024-01-01&end=2024-12-31&adjust=none"
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)
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assert resp.status_code == 200
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body = resp.json()
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assert body["metadata"]["adjust_mode"] == "none"
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assert len(body["bars"]) > 200
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assert "ma20" in body["indicators"]
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def test_signals_selections_by_symbol(self, client) -> None:
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# 生成一次信号 + 一次选股，再按 symbol 查询
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body = {
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"query": {
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"universe": {"exclude_st": False, "min_listing_days": 0, "symbols": _SYMS},
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"factors": [{"name": "momentum_60", "weight": 1}],
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"top_n": 10,
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"as_of": "2024-12-31",
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}
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}
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assert client.post("/api/signals", json={**body, "rules": {"buy_rank_threshold": 1, "max_output_rank": 4}}).status_code == 200
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assert client.post("/api/selections", json={
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"universe": {"exclude_st": False, "min_listing_days": 0, "symbols": _SYMS},
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"method": "score", "factors": [{"name": "momentum_60", "weight": 1}],
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"top_n": 2, "as_of": "2024-12-31",
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}).status_code == 200
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markers = client.get(f"/api/stocks/{_SYMS[0]}/signals").json()
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assert isinstance(markers, list) and len(markers) >= 1
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assert markers[0]["kind"].startswith("signal_")
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assert markers[0]["text"]
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hits = client.get(f"/api/stocks/{_SYMS[0]}/selections").json()
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assert isinstance(hits, list)
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assert all(m["kind"] == "selection" for m in hits)
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def test_backtest_chart_and_trades(self, client) -> None:
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chart = client.get(
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f"/api/backtests/EXP-CHART-1/stocks/{_SYMS[0]}/chart?start=2024-01-01&end=2024-12-31"
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)
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assert chart.status_code == 200
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c = chart.json()
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assert c["metadata"]["execution_price_basis"] == "none"
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assert c["bars"] and c["metadata"]["bar_count"] > 100
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trades = client.get("/api/backtests/EXP-CHART-1/trades").json()
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positions = client.get("/api/backtests/EXP-CHART-1/positions").json()
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assert isinstance(trades, list) and isinstance(positions, list)
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assert client.get("/api/backtests/EXP-NOPE/stocks/x/chart").status_code == 404
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class TestAdjustCoordinate:
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def test_qfq_backtest_marker_converted(self, seeded, tmp_path) -> None:
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"""显示前复权时，早期成交 marker 价格按因子折算贴图（v3 §20.5 坐标）。"""
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from app.domain.entities.research import (
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ActionRecord,
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BacktestResult,
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BacktestSummary,
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CurvePoint,
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RankedPick,
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Trade,
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)
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engine, Session, df = _seeded_with_factors(tmp_path)
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dates = sorted(df["trade_date"].unique())
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split = dates[len(dates) // 2]
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with Session() as session:
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SqlAlchemyAdjustFactorRepository(session).upsert_many(
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[
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AdjustFactor(symbol=_SYMS[0], trade_date=d,
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factor=Decimal("1.0") if d < split else Decimal("2.0"))
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for d in dates
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]
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)
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session.commit()
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svc = ChartService(
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SqlAlchemyStockRepository(session),
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SqlAlchemyDailyBarRepository(session),
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SqlAlchemyAdjustFactorRepository(session),
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)
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# 早期（factor=1.0 段）一笔买入成交价 100
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result = BacktestResult(
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summary=BacktestSummary(
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start=dates[0], end=dates[-1], initial_capital=1e6, final_equity=1e6,
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total_return_pct=0, annual_return_pct=0, sharpe=0, max_drawdown_pct=0,
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volatility_pct=0, win_rate_pct=0, total_trades=1, avg_turnover_pct=0,
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),
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equity_curve=[CurvePoint(date=dates[0], value=1e6)],
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drawdown=[], monthly_returns=[], yearly_returns=[],
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positions=[], trades=[
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Trade(entry_date=dates[5], exit_date=dates[-1], symbol=_SYMS[0],
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entry_price=100.0, exit_price=200.0, return_pct=100),
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],
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selection_history=[
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RankedPick(date=dates[5], symbol=_SYMS[0], rank=1, score=1.0)
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],
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signal_history=[
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ActionRecord(date=dates[5], symbol=_SYMS[0], signal="BUY", filled=True, price=100.0),
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],
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fills=[
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ActionRecord(date=dates[5], symbol=_SYMS[0], signal="BUY", filled=True, price=100.0),
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],
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turnover_pct=0,
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config_snapshot={"price_adjustment": "none"},
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)
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chart_none = svc.backtest_stock_chart(result, _SYMS[0], dates[0], dates[-1], "none")
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chart_qfq = svc.backtest_stock_chart(result, _SYMS[0], dates[0], dates[-1], "qfq")
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# none：fill 价 100；qfq 显示：早期因子 1.0 / 最新 2.0 → 折算 50
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none_fill = chart_none.fills[0]
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qfq_fill = chart_qfq.fills[0]
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assert none_fill.price == 100.0
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assert qfq_fill.price is not None and abs(qfq_fill.price - 50.0) < 1e-3
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# 选股意图标记保留
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assert any(m.kind == "selection" for m in chart_qfq.selections)
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