mirror of
https://ghfast.top/https://github.com/aeroxw/easy-tdx.git
synced 2026-09-12 16:54:17 +08:00
Justin Gu
5fc398255d
mypy (13 errors → 0): - portfolio/optimizer: register_optimizer 返回类型改为 Callable 装饰器签名 (原标注 type[WeightOptimizer] 导致 4 个子类 Too many arguments) - factor/engine: _datetime_to_int 用 isinstance 收窄替代 object→int 强转 - factor/analysis: 删多余 type:ignore（改由 mypy override 统一处理 scipy） - backtest/orders, execution: np.sqrt 表达式用 float() 包裹消除 no-any-return - MyTT.pyi: MACD 签名删除错误的 LOW/HIGH 参数（与 MyTT.py 实际签名对齐） - pyproject: 新增 scipy mypy override (ignore_missing_imports) ruff format: 8 个 test 文件格式化 验证: 564 passed, mypy 192 文件零错误, ruff check/format 全绿
77 lines
2.6 KiB
Python
77 lines
2.6 KiB
Python
"""Test RebalanceEngine."""
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from __future__ import annotations
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import numpy as np
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import pandas as pd
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from easy_tdx.portfolio.optimizer import EqualWeightOptimizer, FactorWeightedOptimizer
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from easy_tdx.portfolio.rebalance import RebalanceEngine
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def _make_market(n_stocks: int = 10, n_days: int = 120, seed: int = 42) -> dict[str, pd.DataFrame]:
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rng = np.random.default_rng(seed)
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data = {}
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for i in range(n_stocks):
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close = 10.0 + np.cumsum(rng.normal(0.01, 0.5, n_days))
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close = np.maximum(close, 1.0)
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data[f"{i:06d}"] = pd.DataFrame(
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{
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"datetime": pd.date_range("2024-01-01", periods=n_days, freq="D"),
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"open": close,
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"high": close + 0.3,
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"low": close - 0.3,
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"close": close,
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"vol": rng.integers(1e5, 1e7, n_days).astype(float),
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"amount": close * 1e6,
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}
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)
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return data
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class TestRebalanceEngine:
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def test_basic_run(self):
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engine = RebalanceEngine(
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optimizer=EqualWeightOptimizer(),
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factor_name="momentum_20d",
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n_stocks=5,
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rebalance_freq="M",
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cash=1_000_000,
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)
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result = engine.run(_make_market(), start_date=20240101, end_date=20240430)
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assert len(result.states) > 0
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assert len(result.rebalance_dates) > 0
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assert len(result.equity_curve) > 0
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assert "total_return" in result.performance
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def test_with_factor_weighted(self):
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engine = RebalanceEngine(
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optimizer=FactorWeightedOptimizer(),
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factor_name="momentum_20d",
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n_stocks=5,
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)
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result = engine.run(_make_market(), start_date=20240101, end_date=20240430)
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assert len(result.states) > 0
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def test_empty_data(self):
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result = RebalanceEngine(optimizer=EqualWeightOptimizer()).run({})
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assert result.performance["total_return"] == 0.0
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def test_equity_curve_dates_sorted(self):
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result = RebalanceEngine(
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optimizer=EqualWeightOptimizer(),
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rebalance_freq="M",
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).run(_make_market(), start_date=20240101, end_date=20240430)
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dates = result.equity_curve["datetime"].tolist()
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assert dates == sorted(dates)
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def test_trades_recorded(self):
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engine = RebalanceEngine(
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optimizer=EqualWeightOptimizer(),
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n_stocks=3,
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rebalance_freq="M",
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)
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result = engine.run(_make_market(), start_date=20240101, end_date=20240430)
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assert len(result.trades) > 0
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assert "BUY" in result.trades["direction"].values
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