feat: Add equipment remaining life count API, refine actual data insertion logging, and enhance prediction data fetching.

src/equipment/router.py

@@ -12,6 +12,7 @@ from src.equipment.schema import (
     EquipmentTop10,
     EquipmentTop10Pagination,
     EquipmentUpdate,
+    CountRemainingLifeResponse,
 )
 from src.equipment.service import (
     get_master_by_assetnum,
@@ -20,6 +21,7 @@ from src.equipment.service import (
     get_all,
     create,
     get_top_10_replacement_priorities,
+    get_count_remaining_life,
     update,
     delete,
     generate_all_transaction,
@@ -113,6 +115,16 @@ async def simulate_equipment(db_session: DbSession, assetnum: str):
 
     return StreamingResponse(event_generator(), media_type='text/event-stream')
 
+@router.get(
+    "/count-remaining-life",
+    response_model=StandardResponse[CountRemainingLifeResponse],
+)
+async def get_count_remaining_life(db_session: DbSession, common: CommonParameters):
+    count = await get_count_remaining_life(db_session=db_session, common=common)
+    return StandardResponse(
+        data=count,
+        message="Count remaining life retrieved successfully",
+    )
 
 @router.get(
     "/top-10-replacement-priorities",

src/equipment/schema.py

@@ -145,3 +145,8 @@ class EquipmentDataMaster(EquipmentBase):
 
 class EquipmentPagination(Pagination):
     items: List[EquipmentDataMaster] = []
+
+class CountRemainingLifeResponse(DefaultBase):
+    safe: int
+    warning: int
+    critical: int

src/equipment/service.py

@@ -411,6 +411,39 @@ async def get_top_10_economic_life(*, db_session: DbSession, common) -> list[Equ
     result = await search_filter_sort_paginate(model=query, **common)
     return result
 
+async def get_count_remaining_life(*, db_session: DbSession, common) -> dict[str, int]:
+    """Count remaining life based on the category"""
+    current_year = datetime.datetime.now().year
+
+    remaining_life = case(
+        (
+            (Equipment.minimum_eac_year - current_year) >= 0,
+            (Equipment.minimum_eac_year - current_year),
+        ),
+        else_=0,
+    )
+
+    query = (
+        Select(
+            func.sum(case((remaining_life <= 1, 1), else_=0)).label("red"),
+            func.sum(case(((remaining_life > 1) & (remaining_life < 5), 1), else_=0)).label("orange"),
+            func.sum(case((remaining_life >= 5, 1), else_=0)).label("green"),
+        )
+        .select_from(Equipment)
+        .join(EquipmentMaster, Equipment.assetnum == EquipmentMaster.assetnum)
+        .filter(Equipment.minimum_eac_year != None)
+        .filter((Equipment.minimum_eac != None) & (Equipment.minimum_eac != 0))
+    )
+
+    result = await db_session.execute(query)
+    row = result.mappings().one()
+
+    return {
+        "safe": int(row["red"] or 0),
+        "warning": int(row["orange"] or 0),
+        "critical": int(row["green"] or 0),
+    }
+
 async def get_top_10_replacement_priorities(*, db_session: DbSession, common) -> list[Equipment]:
     """Returns top 10 replacement priorities."""
     query = (

src/modules/equipment/Eac.py

@@ -352,7 +352,7 @@ def main(assetnum=None):
                 print("Skipping None assetnum")
                 continue
 
-            print(f"Processing asset: {row_assetnum}")
+            print(f"EAC Calculation asset: {row_assetnum}")
             eac.hitung_eac_equipment(row_assetnum)
             processed.append(row_assetnum)
 

src/modules/equipment/Prediksi.py

@@ -126,35 +126,35 @@ class Prediksi:
         return fv_values
 
     # Fungsi untuk menghapus data proyeksi pada tahun tertentu
-    def __delete_predictions_from_db(self, equipment_id):
-        try:
-            connections = get_connection()
-            connection = (
-                connections[0] if isinstance(connections, tuple) else connections
-            )
-            if connection is None:
-                print("Database connection failed.")
-                return None
+    # def __delete_predictions_from_db(self, equipment_id):
+    #     try:
+    #         connections = get_connection()
+    #         connection = (
+    #             connections[0] if isinstance(connections, tuple) else connections
+    #         )
+    #         if connection is None:
+    #             print("Database connection failed.")
+    #             return None
 
-            cursor = connection.cursor()
+    #         cursor = connection.cursor()
 
-            # Query untuk menghapus data berdasarkan tahun proyeksi
-            delete_query = """
-            DELETE FROM lcc_equipment_tr_data
-            WHERE assetnum = %s AND is_actual = 0;
-            """  # Asumsikan kolom is_actual digunakan untuk membedakan data proyeksi dan data aktual
+    #         # Query untuk menghapus data berdasarkan tahun proyeksi
+    #         delete_query = """
+    #         DELETE FROM lcc_equipment_tr_data
+    #         WHERE assetnum = %s AND is_actual = 0;
+    #         """  # Asumsikan kolom is_actual digunakan untuk membedakan data proyeksi dan data aktual
 
-            # Eksekusi query delete
-            cursor.execute(delete_query, (equipment_id,))
-            connection.commit()
-            # print(f"Data proyeksi untuk tahun {equipment_id} berhasil dihapus.")
+    #         # Eksekusi query delete
+    #         cursor.execute(delete_query, (equipment_id,))
+    #         connection.commit()
+    #         # print(f"Data proyeksi untuk tahun {equipment_id} berhasil dihapus.")
 
-        except Exception as e:
-            print(f"Error saat menghapus data proyeksi dari database: {e}")
+    #     except Exception as e:
+    #         print(f"Error saat menghapus data proyeksi dari database: {e}")
 
-        finally:
-            if connection:
-                connection.close()
+    #     finally:
+    #         if connection:
+    #             connection.close()
 
     # Fungsi untuk menyimpan data proyeksi ke database
     async def __insert_predictions_to_db(self, data, equipment_id, token):
@@ -707,6 +707,75 @@ class Prediksi:
 
     # ======================================================================================================================================================
 
+    async def _fetch_api_data(self, assetnum: str, year: int) -> dict:
+        url = self.RELIABILITY_APP_URL
+        endpoint = f"{url}/main/number-of-failures/{assetnum}/{int(year)}/{int(year)}"
+        async with httpx.AsyncClient() as client:
+            try:
+                current_token = getattr(self, "access_token", None)
+                response = await client.get(
+                    endpoint,
+                    timeout=30.0,
+                    headers={"Authorization": f"Bearer {current_token}"} if current_token else {},
+                )
+                response.raise_for_status()
+                return response.json()
+            except httpx.HTTPStatusError as e:
+                status = getattr(e.response, "status_code", None)
+                # If we get a 401 or 403, try to refresh the access token and retry once
+                if status in (401, 403):
+                    print(f"Received {status} from reliability API, attempting to refresh/re-login...")
+                    # Try refreshing token first
+                    new_access = await self.refresh_access_token()
+                    # If refresh failed (e.g. refresh token expired), try full sign-in
+                    if not new_access:
+                        print("Refresh failed, attempting full sign-in...")
+                        await self.sign_in()
+                        new_access = getattr(self, "access_token", None)
+
+                    if new_access:
+                        try:
+                            response = await client.get(
+                                endpoint,
+                                timeout=30.0,
+                                headers={"Authorization": f"Bearer {new_access}"},
+                            )
+                            response.raise_for_status()
+                            return response.json()
+                        except httpx.HTTPError as e2:
+                            print(f"HTTP error occurred after retry: {e2}")
+                            return {}
+                print(f"HTTP error occurred: {e}")
+                return {}
+            except httpx.HTTPError as e:
+                print(f"HTTP error occurred: {e}")
+                return {}
+
+    def __get_man_hour_rate(self, staff_level: str = "junior"):
+        connection = None
+        try:
+            connections = get_connection()
+            connection = (
+                connections[0] if isinstance(connections, tuple) else connections
+            )
+            if connection is None:
+                return 0.0
+
+            cursor = connection.cursor()
+            # Takes from salary_per_hour_idr on specific staff_job_level
+            query = "SELECT salary_per_hour_idr FROM lcc_manpower_cost WHERE staff_job_level = %s LIMIT 1"
+            cursor.execute(query, (staff_level,))
+            result = cursor.fetchone()
+            if result:
+                return float(result[0])
+            return 0.0
+        except Exception as e:
+            print(f"Error getting man hour rate for {staff_level}: {e}")
+            return 0.0
+        finally:
+            if connection:
+                connection.close()
+
     async def predict_equipment_data(self, assetnum, token):
         try:
             # Mengambil data dari database
@@ -759,6 +828,7 @@ class Prediksi:
 
             # Mendapatkan rate dan tahun maksimal
             rate, max_year = self.__get_rate_and_max_year(assetnum)
+            man_hour_rate = self.__get_man_hour_rate() # Defaults to 'junior'
             pmt = 0
 
             # Prediksi untuk setiap kolom
@@ -788,8 +858,28 @@ class Prediksi:
                             recent_vals = df[column].dropna()
 
                         # Jika masih kosong, pakai default (interval minimal 1, lainnya 0)
-                        if recent_vals.empty:
+                        if "labor" in col_lower:
+                            preds_list = []
+                            for yr in future_years:
+                                failures_data = await self._fetch_api_data(assetnum, yr)
+                                # Interval from number of failures
+                                interval = 0.0
+                                if isinstance(failures_data, dict):
+                                    val = failures_data.get("data")
+                                    if val is not None:
+                                        try:
+                                            interval = float(val)
+                                        except Exception:
+                                            interval = 0.0
+                                
+                                # interval * labor_time(3) * labor_human(1) * man_hour_rate
+                                cost = rc_labor_cost(interval, 3.0, 1.0, man_hour_rate)
+                                preds_list.append(cost)
+                            preds = np.array(preds_list, dtype=float)
+
+                        elif recent_vals.empty:
                             avg = 0.0
+                            preds = np.repeat(float(avg), n_future)
                         else:
                             avg = pd.to_numeric(recent_vals, errors="coerce").fillna(0).mean()
                             avg = 0.0 if pd.isna(avg) else float(avg)
@@ -957,22 +1047,22 @@ async def main(RELIABILITY_APP_URL=RELIABILITY_APP_URL, assetnum=None, token=Non
         prediksi = Prediksi(RELIABILITY_APP_URL)
 
         # If token not provided, sign in to obtain access_token/refresh_token
-        # if token is None:
-        #     signin_res = await prediksi.sign_in()
-        #     if not getattr(prediksi, "access_token", None):
-        #         print("Failed to obtain access token; aborting.")
-        #         return
-        # else:
-        #     # Use provided token as access token
-        #     prediksi.access_token = token
+        if token is None:
+            signin_res = await prediksi.sign_in()
+            if not getattr(prediksi, "access_token", None):
+                print("Failed to obtain access token; aborting.")
+                return
+        else:
+            # Use provided token as access token
+            prediksi.access_token = token
 
         # If an assetnum was provided, run only for that assetnum
         if assetnum:
-            print(f"Processing single assetnum: {assetnum}")
+            print(f"Predicting single assetnum: {assetnum}")
             try:
                 await prediksi.predict_equipment_data(assetnum, prediksi.access_token)
             except Exception as e:
-                print(f"Error processing {assetnum}: {e}")
+                print(f"Error Predicting {assetnum}: {e}")
             print("Selesai.")
             return
 
@@ -993,11 +1083,11 @@ async def main(RELIABILITY_APP_URL=RELIABILITY_APP_URL, assetnum=None, token=Non
             if not current_asset or str(current_asset).strip() == "":
                 print(f"[{idx}/{len(results)}] Skipping empty assetnum")
                 continue
-            print(f"[{idx}/{len(results)}] Processing assetnum: {current_asset}")
+            print(f"[{idx}/{len(results)}] Predicting assetnum: {current_asset}")
             try:
                 await prediksi.predict_equipment_data(current_asset, prediksi.access_token)
             except Exception as e:
-                print(f"Error processing {current_asset}: {e}")
+                print(f"Error Predicting {current_asset}: {e}")
 
         print("Selesai.")
     except Exception as e:

src/modules/equipment/insert_actual_data.py

@@ -954,6 +954,7 @@ async def query_data(target_assetnum: str = None):
         total_assets = len(results)
         processed_assets = 0
         total_inserted = 0
+        total_updated = 0
         overall_start = datetime.now()
         print(f"Starting processing {total_assets} assets at {overall_start.isoformat()}")
 
@@ -970,6 +971,7 @@ async def query_data(target_assetnum: str = None):
             processed_assets += 1
             years_processed = 0
             inserted_this_asset = 0
+            updated_this_asset = 0
 
             # CM
             data_cm = get_recursive_query(cursor_wo, assetnum, worktype="CM")
@@ -1108,8 +1110,8 @@ async def query_data(target_assetnum: str = None):
                             year,
                         ),
                     )
-                    inserted_this_asset += 1
-                    total_inserted += 1
+                    updated_this_asset += 1
+                    total_updated += 1
                 seq = seq + 1
 
             # commit per asset to persist progress and free transaction
@@ -1127,16 +1129,16 @@ async def query_data(target_assetnum: str = None):
             # progress per asset
             print(
                 f"[{idx}/{total_assets}] Asset {assetnum} processed. "
-                f"Inserted this asset: {inserted_this_asset}. "
+                f"Inserted: {inserted_this_asset}, Updated: {updated_this_asset}. "
                 f"Asset time: {asset_elapsed.total_seconds():.2f}s. "
-                f"Total inserted: {total_inserted}. "
+                f"Total Ins: {total_inserted}, Upd: {total_updated}. "
                 f"Overall elapsed: {total_elapsed.total_seconds():.2f}s. "
                 f"Progress: {pct_assets:.1f}%"
             )
 
             # periodic summary every 10 assets
             if idx % 10 == 0 or idx == total_assets:
-                print(f"SUMMARY: {idx}/{total_assets} assets processed, {total_inserted} rows inserted, elapsed {total_elapsed.total_seconds():.1f}s")
+                print(f"SUMMARY: {idx}/{total_assets} assets processed, {total_inserted} inserted, {total_updated} updated, elapsed {total_elapsed.total_seconds():.1f}s")
 
         # Commit perubahan
         try:
@@ -1147,7 +1149,7 @@ async def query_data(target_assetnum: str = None):
             except Exception:
                 pass
 
-        print(f"Finished processing all assets. Total assets: {total_assets}, total inserted: {total_inserted}, total time: {(datetime.now()-overall_start).total_seconds():.2f}s")
+        print(f"Finished processing all assets. Total assets: {total_assets}, Total Inserted: {total_inserted}, Total Updated: {total_updated}, Total time: {(datetime.now()-overall_start).total_seconds():.2f}s")
 
     except Exception as e:
         print("Error saat menjalankan query:", e)