58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
"""Verify BacktestEngine consumes persisted factor fields."""
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from __future__ import annotations
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from datetime import date
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import pytest
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from app.backtest.engine import BacktestEngine, BtConfig
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@pytest.fixture()
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def engine(monkeypatch):
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cfg = BtConfig(
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id="test",
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name="factor",
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start_date=date(2025, 1, 10),
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end_date=date(2025, 1, 10),
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universe=["000001.SZ"],
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params={},
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)
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engine = BacktestEngine(cfg)
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def fake_fetch_latest(ts_code, trade_date, fields): # noqa: D401
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assert "factors.mom_20" in fields
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return {
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"daily.close": 10.0,
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"daily.pct_chg": 0.02,
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"daily_basic.turnover_rate": 5.0,
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"daily_basic.volume_ratio": 15.0,
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"factors.mom_20": 0.12,
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"factors.mom_60": 0.25,
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"factors.volat_20": 0.05,
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"factors.turn_20": 3.0,
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"news.sentiment_index": 0.3,
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"news.heat_score": 0.4,
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"macro.industry_heat": 0.6,
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"macro.relative_strength": 0.7,
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}
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monkeypatch.setattr(engine.data_broker, "fetch_latest", fake_fetch_latest)
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monkeypatch.setattr(engine.data_broker, "fetch_series", lambda *args, **kwargs: [])
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monkeypatch.setattr(engine.data_broker, "fetch_flags", lambda *args, **kwargs: False)
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return engine
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def test_load_market_data_prefers_factors(engine):
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data = engine.load_market_data(date(2025, 1, 10))
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record = data["000001.SZ"]
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features = record["features"]
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assert features["mom_20"] == pytest.approx(0.12)
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assert features["mom_60"] == pytest.approx(0.25)
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assert features["volat_20"] == pytest.approx(0.05)
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assert features["turn_20"] == pytest.approx(3.0)
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assert features["news_sentiment"] == pytest.approx(0.3)
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assert features["news_heat"] == pytest.approx(0.4)
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assert features["risk_penalty"] == pytest.approx(min(1.0, 0.05 * 5.0))
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