fix prediksi script

src/modules/equipment/Prediksi.py

@@ -195,7 +195,7 @@ class Prediksi:
                 "raw_loss_output_MW", raw_loss_output_price
                 , created_by, created_at
             ) VALUES (
-                %s, %s, 0, 1, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, 'Sys', NOW()
+                %s, %s, 0, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, 'Sys', NOW()
             )
             """
 
@@ -226,40 +226,44 @@ class Prediksi:
                 max_seq = max_seq + 1
                 # Update values from API
                 api_data = await fetch_api_data(equipment_id, row["year"])
-                if api_data:
-                    # # Get current num_fail
-                    cm_interval_prediction = api_data["data"][0]["num_fail"]
+                if api_data and "data" in api_data and isinstance(api_data["data"], list) and len(api_data["data"]) > 0:
+                    # Get current num_fail (ensure numeric)
+                    try:
+                        cm_interval_prediction = float(api_data["data"][0].get("num_fail", row.get("cm_interval", 1)))
+                    except Exception:
+                        cm_interval_prediction = float(row.get("cm_interval", 1)) if not pd.isna(row.get("cm_interval", None)) else 1
                 else:
-                    cm_interval_prediction = (
-                        (
-                            float(row["cm_interval"])
-                            if float(row["cm_interval"]) >= 1
-                            else 1
-                        ),
-                    )
+                    # Fallback: ensure numeric scalar, not a tuple
+                    try:
+                        val = float(row.get("cm_interval", 1))
+                        cm_interval_prediction = val if val >= 1 else 1.0
+                    except Exception:
+                        cm_interval_prediction = 1.0
+
                 records_to_insert.append(
                     (
                         str(uuid4()),
                         int(max_seq),
-                        float(row["year"]),
+                        float(row["pm_interval"]) if not pd.isna(row.get("pm_interval", None)) else 0.0,
+                        float(row["year"]) if not pd.isna(row.get("year", None)) else 0.0,
                         equipment_id,
                         cm_interval_prediction,
-                        float(row["cm_cost"]),
-                        float(row["cm_labor_time"]),
-                        float(row["cm_labor_human"]),
-                        float(row["pm_cost"]),
-                        float(row["pm_labor_time"]),
-                        float(row["pm_labor_human"]),
-                        float(row["oh_interval"]),
-                        float(row["oh_cost"]),
-                        float(row["oh_labor_time"]),
-                        float(row["oh_labor_human"]),
-                        float(row["predictive_interval"]),
-                        float(row["predictive_material_cost"]),
-                        float(row["predictive_labor_time"]),
-                        float(row["predictive_labor_human"]),
-                        float(row["loss_output_mw"]),
-                        float(row["loss_price"]),
+                        float(row["cm_cost"]) if not pd.isna(row.get("cm_cost", None)) else 0.0,
+                        float(row["cm_labor_time"]) if not pd.isna(row.get("cm_labor_time", None)) else 0.0,
+                        float(row["cm_labor_human"]) if not pd.isna(row.get("cm_labor_human", None)) else 0.0,
+                        float(row["pm_cost"]) if not pd.isna(row.get("pm_cost", None)) else 0.0,
+                        float(row["pm_labor_time"]) if not pd.isna(row.get("pm_labor_time", None)) else 0.0,
+                        float(row["pm_labor_human"]) if not pd.isna(row.get("pm_labor_human", None)) else 0.0,
+                        float(row["oh_interval"]) if not pd.isna(row.get("oh_interval", None)) else 0.0,
+                        float(row["oh_cost"]) if not pd.isna(row.get("oh_cost", None)) else 0.0,
+                        float(row["oh_labor_time"]) if not pd.isna(row.get("oh_labor_time", None)) else 0.0,
+                        float(row["oh_labor_human"]) if not pd.isna(row.get("oh_labor_human", None)) else 0.0,
+                        float(row["predictive_interval"]) if not pd.isna(row.get("predictive_interval", None)) else 0.0,
+                        float(row["predictive_material_cost"]) if not pd.isna(row.get("predictive_material_cost", None)) else 0.0,
+                        float(row["predictive_labor_time"]) if not pd.isna(row.get("predictive_labor_time", None)) else 0.0,
+                        float(row["predictive_labor_human"]) if not pd.isna(row.get("predictive_labor_human", None)) else 0.0,
+                        float(row["loss_output_mw"]) if not pd.isna(row.get("loss_output_mw", None)) else 0.0,
+                        float(row["loss_price"]) if not pd.isna(row.get("loss_price", None)) else 0.0,
                     )
                 )
 
@@ -522,4 +526,8 @@ async def main(RELIABILITY_APP_URL=RELIABILITY_APP_URL):
         return
         
 
-asyncio.run(main())
+if __name__ == "__main__":
+    asyncio.run(
+        main()
+    )
+

src/modules/equipment/run.py

@@ -4,12 +4,12 @@ import time
 # prefer package-relative imports, but allow running this file directly as a script
 try:
     from .insert_actual_data import query_data, insert_lcca_maximo_corrective_data, insert_ms_equipment_data
-    from .Prediksi import Prediksi
+    from .Prediksi import Prediksi, main as predict_run
     from .Eac import Eac
 except ImportError:
     # fallback when there's no parent package (e.g., python run.py)
     from insert_actual_data import query_data, insert_lcca_maximo_corrective_data, insert_ms_equipment_data
-    from Prediksi import Prediksi
+    from Prediksi import Prediksi, main as predict_run
     from Eac import Eac
 
 
@@ -17,15 +17,14 @@ except ImportError:
 async def main():
     start_time = time.time()
 
-    try:
-        await query_data()
-    except Exception as e:
-        print(f"Error in query_data: {str(e)}")
-        return
+    # try:
+    #     await query_data()
+    # except Exception as e:
+    #     print(f"Error in query_data: {str(e)}")
+    #     return
 
     try:
-        prediksi = Prediksi()
-        await prediksi.main()
+        await predict_run()
     except Exception as e:
         print(f"Error in predict_equipment_data: {str(e)}")
         return