feat: instrument analysis

backend/routers/causal_lab.py

@@ -1391,21 +1391,47 @@ Règles : coef intermédiaire ∈ [-5,5] ; coef output en pips, |val| ∈ [30,20
 def refresh_auto_analyses():
     """
     Re-run _run_auto_analysis for all causal_event_analyses rows with empty actual_json.
-    Fills in real price data so comprehension scores can be computed.
+    Returns detailed per-event debug info.
     """
     try:
         from services.database import get_conn
         conn = get_conn()
-        rows = conn.execute("""
+
+        # Also return a DB state summary for all analyses (not just empty ones)
+        all_rows = conn.execute("""
             SELECT a.id AS cea_id, a.market_event_id, a.template_id,
-                   a.actual_json
+                   a.actual_json, a.prediction_json,
+                   e.name AS event_name, e.start_date
             FROM causal_event_analyses a
-            WHERE a.actual_json IS NULL OR a.actual_json = '{}' OR a.actual_json = 'null'
+            LEFT JOIN market_events e ON e.id = a.market_event_id
+            ORDER BY a.id DESC
         """).fetchall()
+
+        db_state = []
+        for r in all_rows:
+            actual = r["actual_json"] or ""
+            pred   = r["prediction_json"] or ""
+            db_state.append({
+                "cea_id":       r["cea_id"],
+                "event_id":     r["market_event_id"],
+                "event_name":   r["event_name"],
+                "start_date":   r["start_date"],
+                "template_id":  r["template_id"],
+                "actual_empty": actual in (None, "", "{}", "null"),
+                "pred_empty":   pred   in (None, "", "{}", "null"),
+                "actual_keys":  list(json.loads(actual).keys()) if actual not in (None, "", "{}", "null") else [],
+                "pred_keys":    list(json.loads(pred).keys())   if pred   not in (None, "", "{}", "null") else [],
+            })
+
+        rows = [r for r in all_rows if (r["actual_json"] or "") in (None, "", "{}", "null")]
+        print(f"[refresh] {len(rows)} analyses with empty actual_json out of {len(all_rows)} total", flush=True)
         conn.close()
 
+        details = []
         refreshed, failed = 0, 0
         for row in rows:
+            detail: dict = {"cea_id": row["cea_id"], "event_id": row["market_event_id"],
+                            "event_name": row["event_name"], "template_id": row["template_id"]}
             try:
                 conn2 = get_conn()
                 ev_row = conn2.execute(
@@ -1413,18 +1439,33 @@ def refresh_auto_analyses():
                 ).fetchone()
                 conn2.close()
                 if not ev_row:
+                    detail["result"] = "event_not_found"
+                    details.append(detail)
                     continue
-                ok = _run_auto_analysis(dict(ev_row), row["template_id"])
+                ev = dict(ev_row)
+                detail["surprise_pct"] = ev.get("surprise_pct")
+                detail["start_date"]   = ev.get("start_date")
+                ok = _run_auto_analysis(ev, row["template_id"])
+                detail["result"] = "ok" if ok else "failed"
                 if ok:
                     refreshed += 1
                 else:
                     failed += 1
+                    detail["result"] = "run_returned_false"
             except Exception as _e:
                 logger.warning(f"[refresh_auto_analyses] cea#{row['cea_id']}: {_e}")
+                detail["result"] = f"exception: {_e}"
                 failed += 1
+            details.append(detail)
 
-        logger.info(f"[refresh_auto_analyses] done: {refreshed} refreshed, {failed} failed")
-        return {"refreshed": refreshed, "failed": failed, "total": len(rows)}
+        print(f"[refresh] done: {refreshed} refreshed, {failed} failed", flush=True)
+        return {
+            "refreshed":  refreshed,
+            "failed":     failed,
+            "total":      len(rows),
+            "db_state":   db_state,
+            "details":    details,
+        }
     except Exception as e:
         logger.error(f"[refresh_auto_analyses] {e}")
         raise HTTPException(500, str(e))