feat(factor): 评估结果存储 factor_eval.db——runs/results两表,metrics按周期JSON,SANGUO_FACTOR_EVAL_DB可覆盖 [vps]

2026-08-25 00:17:47 +08:00
parent 89a8dd1487
commit afe969e307
2 changed files with 208 additions and 0 deletions
@@ -0,0 +1,57 @@
+# tests/factor/test_eval_store.py
+"""eval_store:建库/建run/UPSERT落盘/查询过滤/finish."""
+import sys, os
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
+
+from sanguo_factor import eval_store
+
+
+def _rows():
+    return [
+        {"factor": "alpha2", "category": "alpha101", "expression": "(-1)*ts_corr(...)",
+         "metrics": {"1": {"ic_mean": 0.05}, "turnover": 0.3}},
+        {"factor": "kmid", "category": "alpha158", "expression": "(close-open)/open",
+         "metrics": {"1": {"ic_mean": -0.02}, "turnover": 0.6}},
+    ]
+
+
+def test_roundtrip(tmp_path):
+    db = str(tmp_path / "factor_eval.db")
+    eval_store.init_db(db)
+    run_id = eval_store.create_run(db, label="冒烟", universe="custom", symbols_count=50,
+                                   factors_total=2, start="2024-01-01", end="2024-12-31",
+                                   params={"periods": [1, 5, 10]})
+    eval_store.save_results(db, run_id, _rows())
+    eval_store.finish_run(db, run_id, "done", factors_done=2)
+
+    runs = eval_store.list_runs(db)
+    assert len(runs) == 1 and runs[0]["run_id"] == run_id and runs[0]["status"] == "done"
+
+    rows = eval_store.get_rows(db, run_id)
+    assert len(rows) == 2
+    assert rows[0]["metrics"]["1"]["ic_mean"] == 0.05
+
+    assert eval_store.get_detail(db, run_id, "kmid")["category"] == "alpha158"
+    assert eval_store.get_detail(db, run_id, "nope") is None
+
+
+def test_filter_by_category_and_search(tmp_path):
+    db = str(tmp_path / "factor_eval.db")
+    eval_store.init_db(db)
+    run_id = eval_store.create_run(db, label="x", universe="all_a", symbols_count=1,
+                                   factors_total=2, start="", end="", params={})
+    eval_store.save_results(db, run_id, _rows())
+    assert len(eval_store.get_rows(db, run_id, category="alpha101")) == 1
+    assert len(eval_store.get_rows(db, run_id, search="corr")) == 1   # 搜表达式
+    assert len(eval_store.get_rows(db, run_id, search="kmid")) == 1   # 搜因子名
+
+
+def test_upsert_same_run(tmp_path):
+    db = str(tmp_path / "factor_eval.db")
+    eval_store.init_db(db)
+    run_id = eval_store.create_run(db, label="x", universe="all_a", symbols_count=1,
+                                   factors_total=1, start="", end="", params={})
+    eval_store.save_results(db, run_id, [_rows()[0]])
+    eval_store.save_results(db, run_id, [{**_rows()[0], "metrics": {"1": {"ic_mean": 0.09}}}] * 1)
+    rows = eval_store.get_rows(db, run_id)
+    assert len(rows) == 1 and rows[0]["metrics"]["1"]["ic_mean"] == 0.09