feat(lotto-signals): signal_runner orchestrator + service_proxy GET helpers

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

agent-office/tests/test_lotto_signal_runner.py

@@ -0,0 +1,114 @@
+import gc
+import os
+import sys
+import tempfile
+
+_fd, _TMP = tempfile.mkstemp(suffix=".db")
+os.close(_fd)
+os.unlink(_TMP)
+os.environ["AGENT_OFFICE_DB_PATH"] = _TMP
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+import pytest
+
+from app.curator import signal_runner
+from app import db
+
+
+@pytest.fixture(autouse=True)
+def fresh_db():
+    gc.collect()
+    if os.path.exists(_TMP):
+        os.remove(_TMP)
+    db.init_db()
+    yield
+    gc.collect()
+    if os.path.exists(_TMP):
+        try:
+            os.remove(_TMP)
+        except PermissionError:
+            pass  # Windows: WAL-mode file locked; DB is ephemeral anyway
+
+
+def test_evaluate_and_persist_cold_start():
+    """첫 호출은 warmup으로 기록되고 baseline에 값이 들어간다."""
+    result = signal_runner.evaluate_metric_and_persist(
+        source="light",
+        metric="sim_signal",
+        value=1.5,
+        draw_no=None,
+        z_normal=1.5,
+        z_urgent=2.5,
+        push_to_window=True,
+    )
+    assert result["fire_level"] == "warmup"
+    assert result["z_score"] is None
+
+    bl = db.get_baseline("sim_signal")
+    assert bl is not None
+    assert bl["window_values"] == [1.5]
+
+
+def test_evaluate_after_window_filled_normal_fire():
+    """8회 push 후 정상 운영, 평균 대비 z≥1.5면 normal."""
+    for v in [1.0, 1.1, 0.9, 1.0, 1.0, 1.1, 0.9, 1.0]:
+        signal_runner.evaluate_metric_and_persist(
+            source="sim",
+            metric="sim_signal",
+            value=v,
+            draw_no=None,
+            z_normal=1.5,
+            z_urgent=2.5,
+            push_to_window=True,
+        )
+
+    result = signal_runner.evaluate_metric_and_persist(
+        source="sim",
+        metric="sim_signal",
+        value=1.12,
+        draw_no=None,
+        z_normal=1.5,
+        z_urgent=2.5,
+        push_to_window=True,
+    )
+    assert result["fire_level"] in ("normal", "urgent")
+    assert result["z_score"] is not None and result["z_score"] >= 1.5
+
+
+def test_evaluate_drift_skips_same_draw_push():
+    """drift는 회차 단위. 같은 회차에서 두 번 호출하면 두 번째는 window push X."""
+    signal_runner.evaluate_metric_and_persist(
+        source="sim", metric="drift", value=0.05, draw_no=1100,
+        z_normal=1.5, z_urgent=2.5, push_to_window=True,
+    )
+    bl_before = db.get_baseline("drift")
+    assert bl_before["window_values"] == [0.05]
+    assert bl_before["last_pushed_draw_no"] == 1100
+
+    signal_runner.evaluate_metric_and_persist(
+        source="sim", metric="drift", value=0.08, draw_no=1100,
+        z_normal=1.5, z_urgent=2.5, push_to_window=True,
+    )
+    bl_after = db.get_baseline("drift")
+    assert bl_after["window_values"] == [0.05]
+
+
+@pytest.mark.asyncio
+async def test_run_signal_check_aggregates_three_metrics(monkeypatch):
+    """run_signal_check이 3종 메트릭 모두 평가하고 overall fire를 반환."""
+    async def fake_lotto_best():
+        return [{"numbers": [1,2,3,4,5,6], "scores": [10,10,10,10,10]}] * 20
+
+    async def fake_lotto_strategy_weights():
+        return {"gap_focus": 0.4, "hot_focus": 0.3, "pair_bias": 0.3}
+
+    monkeypatch.setattr(signal_runner, "_fetch_best_picks", fake_lotto_best)
+    monkeypatch.setattr(signal_runner, "_fetch_strategy_weights", fake_lotto_strategy_weights)
+
+    out = await signal_runner.run_signal_check(source="light", curate_result=None, current_draw_no=1101)
+    assert "overall_fire" in out
+    assert "results" in out
+    assert any(r["metric"] == "sim_signal" for r in out["results"])
+    # light_check는 confidence 평가 안 함
+    assert not any(r["metric"] == "confidence" for r in out["results"])