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ProStock/tests/test_compute_factors.py

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"""compute_factors 入口脚本的单元测试(使用 mock 隔离外部依赖)。"""
from unittest.mock import MagicMock, patch
import polars as pl
import pytest
from src.data.compute_factors import run
@pytest.fixture
def mock_manager():
"""提供一个 mock 的 FactorManager。"""
manager = MagicMock()
manager.get_all_factors.return_value = pl.DataFrame(
{
"factor_id": ["F_001", "F_002"],
"name": ["ma_5", "ma_20"],
"dsl": ["ts_mean(close, 5)", "ts_mean(close, 20)"],
}
)
manager.get_factors_by_name.side_effect = lambda name: pl.DataFrame(
{"name": [name], "dsl": [f"dsl_of_{name}"]}
)
return manager
@pytest.fixture
def mock_engine():
"""提供一个 mock 的 FactorEngine。"""
engine = MagicMock()
engine.compute.side_effect = lambda cols, start, end: pl.DataFrame(
{
"trade_date": ["20240101", "20240101"],
"ts_code": ["000001.SZ", "000002.SZ"],
cols[0]: [1.0, 2.0],
}
)
return engine
@pytest.fixture
def mock_storage(tmp_path):
"""提供一个 mock 的 FactorStorage全部校验通过。"""
storage = MagicMock()
storage.validate.return_value = (
True,
{"max_abs_diff": 0.0, "mean_abs_diff": 0.0, "matched_rows": 2},
)
storage.save.return_value = None
return storage
def test_run_auto_discover_factors(mock_manager, mock_engine, mock_storage):
"""未传入 factor_names 时自动读取 metadata 中全部因子。"""
with (
patch("src.data.compute_factors.FactorEngine", return_value=mock_engine),
patch("src.data.compute_factors.FactorStorage", return_value=mock_storage),
patch("src.data.compute_factors.FactorManager", return_value=mock_manager),
):
result = run(
factor_names=[],
metadata="dummy.jsonl",
start_date="20240101",
end_date="20240131",
)
assert result["success"] == ["ma_5", "ma_20"]
assert len(result["failed"]) == 0
assert mock_manager.get_all_factors.called
def test_run_validate_fail_skip(mock_manager, mock_engine, mock_storage):
"""校验失败且无 force 时跳过写入。"""
mock_storage.validate.return_value = (
False,
{"max_abs_diff": 1.0, "mean_abs_diff": 0.5, "matched_rows": 2},
)
with (
patch("src.data.compute_factors.FactorEngine", return_value=mock_engine),
patch("src.data.compute_factors.FactorStorage", return_value=mock_storage),
patch("src.data.compute_factors.FactorManager", return_value=mock_manager),
):
result = run(
factor_names=["ma_5"],
metadata="dummy.jsonl",
start_date="20240101",
end_date="20240131",
force=False,
)
assert result["success"] == []
assert len(result["failed"]) == 1
assert result["failed"][0]["name"] == "ma_5"
assert result["failed"][0]["reason"] == "校验失败"
mock_storage.save.assert_not_called()
def test_run_validate_fail_force(mock_manager, mock_engine, mock_storage):
"""校验失败但 force=True 时强制写入。"""
mock_storage.validate.return_value = (
False,
{"max_abs_diff": 1.0, "mean_abs_diff": 0.5, "matched_rows": 2},
)
with (
patch("src.data.compute_factors.FactorEngine", return_value=mock_engine),
patch("src.data.compute_factors.FactorStorage", return_value=mock_storage),
patch("src.data.compute_factors.FactorManager", return_value=mock_manager),
):
result = run(
factor_names=["ma_5"],
metadata="dummy.jsonl",
start_date="20240101",
end_date="20240131",
force=True,
)
assert result["success"] == ["ma_5"]
assert len(result["failed"]) == 0
mock_storage.save.assert_called_once()
def test_run_missing_metadata_entry(mock_manager, mock_engine, mock_storage):
"""metadata 中找不到因子时标记失败。"""
mock_manager.get_factors_by_name.side_effect = None
mock_manager.get_factors_by_name.return_value = pl.DataFrame(
{"name": [], "dsl": []}
)
with (
patch("src.data.compute_factors.FactorEngine", return_value=mock_engine),
patch("src.data.compute_factors.FactorStorage", return_value=mock_storage),
patch("src.data.compute_factors.FactorManager", return_value=mock_manager),
):
result = run(
factor_names=["unknown"],
metadata="dummy.jsonl",
start_date="20240101",
end_date="20240131",
)
assert result["success"] == []
assert len(result["failed"]) == 1
assert "未找到" in result["failed"][0]["reason"]
def test_run_engine_exception(mock_manager, mock_engine, mock_storage):
"""engine.compute 抛出异常时标记失败。"""
mock_engine.compute.side_effect = ValueError("compute error")
with (
patch("src.data.compute_factors.FactorEngine", return_value=mock_engine),
patch("src.data.compute_factors.FactorStorage", return_value=mock_storage),
patch("src.data.compute_factors.FactorManager", return_value=mock_manager),
):
result = run(
factor_names=["ma_5"],
metadata="dummy.jsonl",
start_date="20240101",
end_date="20240131",
)
assert result["success"] == []
assert len(result["failed"]) == 1
assert "compute error" in result["failed"][0]["reason"]
def test_run_missing_result_column(mock_engine, mock_storage, mock_manager):
"""计算结果缺少对应因子列时标记失败。"""
mock_engine.compute.side_effect = lambda cols, start, end: pl.DataFrame(
{
"trade_date": ["20240101"],
"ts_code": ["000001.SZ"],
"wrong_col": [1.0],
}
)
with (
patch("src.data.compute_factors.FactorEngine", return_value=mock_engine),
patch("src.data.compute_factors.FactorStorage", return_value=mock_storage),
patch("src.data.compute_factors.FactorManager", return_value=mock_manager),
):
result = run(
factor_names=["ma_5"],
metadata="dummy.jsonl",
start_date="20240101",
end_date="20240131",
)
assert result["success"] == []
assert len(result["failed"]) == 1
assert "缺少列" in result["failed"][0]["reason"]