fix: numpy float → Python native 변환 — DB INSERT 시 np.float64 직렬화 오류 수정

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

prediction/models/result.py

@@ -56,29 +56,41 @@ class AnalysisResult:
 
     def to_db_tuple(self) -> tuple:
         import json
+
+        def _f(v: object) -> float:
+            """numpy float → Python float 변환."""
+            return float(v) if v is not None else 0.0
+
+        def _i(v: object) -> int:
+            """numpy int → Python int 변환."""
+            return int(v) if v is not None else 0
+
+        # features dict 내부 numpy 값도 변환
+        safe_features = {k: float(v) for k, v in self.features.items()} if self.features else {}
+
         return (
-            self.mmsi,
+            str(self.mmsi),
             self.timestamp,
-            self.vessel_type,
-            self.confidence,
-            self.fishing_pct,
-            self.cluster_id,
-            self.season,
-            self.zone,
-            self.dist_to_baseline_nm,
-            self.activity_state,
-            self.ucaf_score,
-            self.ucft_score,
-            self.is_dark,
-            self.gap_duration_min,
-            self.spoofing_score,
-            self.bd09_offset_m,
-            self.speed_jump_count,
-            self.cluster_size,
-            self.is_leader,
-            self.fleet_role,
-            self.risk_score,
-            self.risk_level,
-            json.dumps(self.features),
+            str(self.vessel_type),
+            _f(self.confidence),
+            _f(self.fishing_pct),
+            _i(self.cluster_id),
+            str(self.season),
+            str(self.zone),
+            _f(self.dist_to_baseline_nm),
+            str(self.activity_state),
+            _f(self.ucaf_score),
+            _f(self.ucft_score),
+            bool(self.is_dark),
+            _i(self.gap_duration_min),
+            _f(self.spoofing_score),
+            _f(self.bd09_offset_m),
+            _i(self.speed_jump_count),
+            _i(self.cluster_size),
+            bool(self.is_leader),
+            str(self.fleet_role),
+            _i(self.risk_score),
+            str(self.risk_level),
+            json.dumps(safe_features),
             self.analyzed_at,
         )