비기계적 매도전략(가치보존) + 위성종목 추천 엔진 추가

매크로·실적·펀더멘털·공매도수급·호가미시구조·대내외 변수 5개 독립 팩터군의 confluence(최소 3/5 합의) 없이는 매도 트리거를 금지하는 정성적 매도판단 엔진과, 보유종목 제외 위성후보 추천 로직을 추가한다. - 단일 팩터 임계값 돌파만으로는 매도 신호를 생성하지 않음 (mechanical_sell_prohibited=true) - 데이터 결측 시 항상 DATA_MISSING/INSUFFICIENT_DATA_NO_ACTION — 추정값으로 채우지 않음 - KIS 호가10단계·공매도거래비중 + Naver 시세/수급 스크래핑 입력 연동 - SQLite 시계열 저장 + 사후 적중률 자체평가 (evaluate_qualitative_sell_strategy_accuracy_v1) - Gitea 일일 스케줄(장마감 후) + 파이프라인 계약 검증 게이트
2026-06-21 20:05:55 +09:00
parent 4cb206a269
commit da0e1b0f7e
15 changed files with 2321 additions and 0 deletions
@@ -0,0 +1,70 @@
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[2]
+if str(ROOT) not in sys.path:
+    sys.path.insert(0, str(ROOT))
+
+from src.quant_engine.qualitative_sell_strategy_store_v1 import (
+    QualitativeSellStoreSpec,
+    fetch_recent_sell_strategy_results,
+    insert_satellite_recommendation,
+    insert_sell_strategy_result,
+    resolve_store_path,
+)
+
+
+def test_insert_and_fetch_sell_strategy_result(tmp_path):
+    db_path = tmp_path / "test.db"
+    result = {
+        "code": "005930",
+        "generated_at": "2026-06-21T12:00:00+09:00",
+        "decision": {
+            "action": "TRIM_REVIEW_PARTIAL",
+            "conviction": "MEDIUM",
+            "market_regime": "TECHNICAL_MARKET",
+            "composite_score": 0.42,
+            "rationale": "test rationale",
+        },
+    }
+    insert_sell_strategy_result(db_path, result)
+    rows = fetch_recent_sell_strategy_results(db_path, "005930")
+    assert len(rows) == 1
+    assert rows[0]["action"] == "TRIM_REVIEW_PARTIAL"
+    assert rows[0]["composite_score"] == 0.42
+
+
+def test_fetch_returns_empty_list_when_db_missing(tmp_path):
+    rows = fetch_recent_sell_strategy_results(tmp_path / "nonexistent.db", "005930")
+    assert rows == []
+
+
+def test_multiple_inserts_ordered_by_generated_at_desc(tmp_path):
+    db_path = tmp_path / "test.db"
+    for ts in ("2026-06-19T12:00:00", "2026-06-21T12:00:00", "2026-06-20T12:00:00"):
+        insert_sell_strategy_result(db_path, {
+            "code": "005930", "generated_at": ts,
+            "decision": {"action": "HOLD_NO_CONFLUENCE"},
+        })
+    rows = fetch_recent_sell_strategy_results(db_path, "005930")
+    assert [r["generated_at"] for r in rows] == ["2026-06-21T12:00:00", "2026-06-20T12:00:00", "2026-06-19T12:00:00"]
+
+
+def test_insert_satellite_recommendation(tmp_path):
+    db_path = tmp_path / "test.db"
+    insert_satellite_recommendation(db_path, "2026-06-21T12:00:00+09:00", {
+        "ticker": "042700",
+        "score": {"satellite_action": "BUY_CANDIDATE", "attractiveness_score": 0.6, "market_regime": "PERFORMANCE_MARKET"},
+    })
+    import sqlite3
+    conn = sqlite3.connect(db_path)
+    row = conn.execute("SELECT ticker, satellite_action, attractiveness_score FROM satellite_recommendations").fetchone()
+    conn.close()
+    assert row == ("042700", "BUY_CANDIDATE", 0.6)
+
+
+def test_resolve_store_path_supports_sqlite(tmp_path):
+    db_path = resolve_store_path(QualitativeSellStoreSpec(location=tmp_path / "qualitative.db"), ROOT)
+    assert str(db_path).endswith("qualitative.db")