@ -38,10 +38,7 @@ class Prediksi:
def __get_param ( self , equipment_id ) :
try :
# Mendapatkan koneksi dari config.py
connections = get_connection ( )
connection = (
connections [ 0 ] if isinstance ( connections , tuple ) else connections
)
connection , connection_wo_db = get_connection ( )
if connection is None :
print ( " Database connection failed. " )
return None
@ -69,10 +66,7 @@ class Prediksi:
def __fetch_data_from_db ( self , equipment_id ) :
try :
# Get connection from config.py (using only the first connection)
connections = get_connection ( )
connection = (
connections [ 0 ] if isinstance ( connections , tuple ) else connections
)
connection , connection_wo_db = get_connection ( )
if connection is None :
print ( " Database connection failed. " )
return None
@ -159,10 +153,7 @@ class Prediksi:
# Fungsi untuk menyimpan data proyeksi ke database
async def __insert_predictions_to_db ( self , data , equipment_id , token ) :
try :
connections = get_connection ( )
connection = (
connections [ 0 ] if isinstance ( connections , tuple ) else connections
)
connection , connection_wo_db = get_connection ( )
if connection is None :
print ( " Database connection failed. " )
return None
@ -320,11 +311,8 @@ class Prediksi:
def __get_asset_criticality_params ( self , equipment_id ) :
try :
connection s = get_connection ( )
connection , connection_wo_db = get_connection ( )
efdh_foh_sum = None
connection = (
connections [ 0 ] if isinstance ( connections , tuple ) else connections
)
if connection is None :
print ( " Database connection failed. " )
return None
@ -418,28 +406,42 @@ class Prediksi:
# Fungsi untuk menghapus data proyeksi pada tahun tertentu
def __update_data_lcc ( self , equipment_id ) :
try :
connection s = get_connection ( )
connection , connection_wo_db = get_connection ( )
production_connection = get_production_connection ( )
connection = (
connections [ 0 ] if isinstance ( connections , tuple ) else connections
)
production_connection = (
production_connection [ 0 ] if isinstance ( production_connection , tuple ) else production_connection
)
if connection is None or production_connection is None :
print ( " Database connection failed. " )
return None
cursor = connection . cursor ( cursor_factory = DictCursor )
# --- OPTIMIZATION START: Fetch static data ONCE ---
# Fetch man_hour_rate (constant for all years currently based on code logic)
man_hour_rate = 0.0
try :
prod_cur = production_connection . cursor ( )
prod_cur . execute ( """ SELECT value_num FROM lcc_ms_master WHERE name= ' manhours_rate ' """ )
r2 = prod_cur . fetchone ( )
if r2 and r2 [ 0 ] is not None :
man_hour_rate = float ( r2 [ 0 ] )
prod_cur . close ( )
except Exception :
pass
# Fetch Asset Criticality (constant for the asset)
asset_criticality_data = self . __get_asset_criticality_params ( equipment_id )
ac = asset_criticality_data if isinstance ( asset_criticality_data , dict ) else { }
asset_criticality_value = float ( ac . get ( " asset_criticality " , 0.0 ) )
# --- OPTIMIZATION END ---
# Ambil semua baris untuk assetnum
select_q = '''
SELECT id , seq , tahun ,
raw_cm_interval , raw_cm_material_cost , rc_cm_labor_cost ,
raw_pm_interval , raw_pm_material_cost , rc_pm_labor_cost ,
raw_predictive_interval , raw_predictive_material_cost , rc_predictive_labor_cost ,
raw_oh_interval , raw_oh_material_cost , rc_oh_labor_cost ,
raw_predictive_interval , raw_predictive_material_cost , rc_predictive_labor_cost ,
raw_cm_interval , raw_cm_material_cost , rc_cm_labor_cost , rc_cm_material_cost ,
raw_pm_interval , raw_pm_material_cost , rc_pm_labor_cost , rc_pm_material_cost ,
raw_predictive_interval , raw_predictive_material_cost , rc_predictive_labor_cost , rc_predictive_material_cost ,
raw_oh_interval , raw_oh_material_cost , rc_oh_labor_cost , rc_oh_material_cost ,
efdh_equivalent_forced_derated_hours , foh_forced_outage_hours
FROM lcc_equipment_tr_data
WHERE assetnum = % s ;
@ -447,24 +449,6 @@ class Prediksi:
cursor . execute ( select_q , ( equipment_id , ) )
rows = cursor . fetchall ( )
# Helper to get man_hour for a year (fallback to master 'manhours_rate')
def _get_man_hour_for_year ( year ) :
try :
# cur = connection.cursor()
prod_cur = production_connection . cursor ( )
# cur.execute("SELECT man_hour FROM lcc_ms_year_data WHERE year = %s", (year,))
# r = cur.fetchone()
# if r and r[0] is not None:
# return float(r[0])
# cur.execute("SELECT value_num FROM lcc_ms_master WHERE name='manhours_rate'")
prod_cur . execute ( """ SELECT value_num FROM lcc_ms_master WHERE name= ' manhours_rate ' """ )
r2 = prod_cur . fetchone ( )
if r2 and r2 [ 0 ] is not None :
return float ( r2 [ 0 ] )
except Exception :
pass
return 0.0
update_q = '''
UPDATE lcc_equipment_tr_data
SET rc_cm_material_cost = % s ,
@ -480,14 +464,14 @@ class Prediksi:
WHERE id = % s ;
'''
batch_params = [ ]
for r in rows :
try :
yr = r . get ( " tahun " ) if isinstance ( r , dict ) else r [ 2 ]
man_hour = _get_man_hour_for_year ( yr )
seq = int ( r . get ( " seq " ) or 0 ) if isinstance ( r , dict ) else int ( r [ 1 ] or 0 )
# yr = r.get("tahun") if isinstance(r, dict) else r[2]
# man_hour = man_hour_rate # Used pre-fetched value
# seq = int(r.get("seq") or 0) if isinstance(r, dict) else int(r[1] or 0)
raw_pm_material_cost = float ( r . get ( " raw_pm_material_cost " ) or 0.0 )
raw_predictive_material_cost = float ( r . get ( " raw_predictive_material_cost " ) or 0.0 )
@ -506,38 +490,20 @@ class Prediksi:
rc_oh_labor = float ( r . get ( " rc_oh_labor_cost " ) or 0.0 )
try :
# if np.isfinite(raw_pm_interval) and raw_pm_interval != 0:
# rc_pm_material = raw_pm_material_cost * raw_pm_interval
# else:
rc_pm_material = raw_pm_material_cost
rc_pm_material = raw_pm_material_cost if raw_pm_material_cost > 0 else float ( r . get ( " rc_pm_material_cost " ) or 0.0 )
except Exception :
rc_pm_material = 0.0
try :
# if np.isfinite(raw_predictive_interval) and raw_predictive_interval != 0:
# rc_predictive_material = raw_predictive_material_cost * raw_predictive_interval
# else:
rc_predictive_material = raw_predictive_material_cost
rc_predictive_material = raw_predictive_material_cost if raw_predictive_material_cost > 0 else float ( r . get ( " rc_predictive_material_cost " ) or 0.0 )
except Exception :
rc_predictive_material = 0.0
rc_oh_material = raw_oh_material_cost
rc_oh_material = raw_oh_material_cost if raw_oh_material_cost > 0 else float ( r . get ( " rc_oh_material_cost " ) or 0.0 )
asset_criticality_data = self . __get_asset_criticality_params ( equipment_id )
asset_criticality_value = 0.0
# Simplify extraction and avoid repeating the multiplication
ac = asset_criticality_data if isinstance ( asset_criticality_data , dict ) else { }
efdh_foh_sum = efdh_equivalent_forced_derated_hours + foh_forced_outage_hours if efdh_equivalent_forced_derated_hours and foh_forced_outage_hours else 0.0
# try:
# efdh_foh_sum = float(ac.get("efdh_foh_sum", 0.0))
# except Exception:
# efdh_foh_sum = 0.0
try :
asset_criticality_value = float ( ac . get ( " asset_criticality " , 0.0 ) )
except Exception :
asset_criticality_value = 0.0
# single multiplier used for all RC groups
ac_multiplier = efdh_foh_sum * asset_criticality_value
@ -551,9 +517,7 @@ class Prediksi:
id_val = r . get ( " id " ) if isinstance ( r , dict ) else r [ 0 ]
cursor . execute (
update_q ,
(
batch_params . append ( (
rc_cm_material ,
rc_cm_labor ,
rc_pm_material ,
@ -563,13 +527,17 @@ class Prediksi:
rc_oh_material ,
rc_oh_labor ,
total ,
id_val ,
) ,
)
id_val
) )
except Exception :
# ignore row-specific errors and continue
continue
# Execute Batch Update
if batch_params :
cursor . executemany ( update_q , batch_params )
# For seq=0 rows, set rc_total_cost to acquisition_cost
cursor . execute (
" update lcc_equipment_tr_data set rc_total_cost = (select acquisition_cost from lcc_ms_equipment_data where assetnum=lcc_equipment_tr_data.assetnum) where assetnum = %s and seq=0; " ,
@ -584,14 +552,16 @@ class Prediksi:
finally :
if connection :
connection . close ( )
if ' production_connection ' in locals ( ) and production_connection :
try :
production_connection . close ( )
except Exception :
pass
# Fungsi untuk mengambil parameter dari database
def __get_rate_and_max_year ( self , equipment_id ) :
try :
connections = get_connection ( )
connection = (
connections [ 0 ] if isinstance ( connections , tuple ) else connections
)
connection , connection_wo_db = get_connection ( )
if connection is None :
print ( " Database connection failed. " )
return None
@ -751,13 +721,10 @@ class Prediksi:
print ( f " HTTP error occurred: { e } " )
return { }
def __get_man_hour_rate ( self , staff_level : str = " j unior" ) :
def __get_man_hour_rate ( self , staff_level : str = " J unior" ) :
connection = None
try :
connections = get_connection ( )
connection = (
connections [ 0 ] if isinstance ( connections , tuple ) else connections
)
connection , connection_wo_db = get_connection ( )
if connection is None :
return 0.0
@ -829,6 +796,7 @@ 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
@ -841,7 +809,6 @@ class Prediksi:
try :
# Case untuk kolom yang terkait dengan corrective maintenance (cm)
if " cm " in col_lower :
recent_df = df
recent_n = df . shape [ 0 ]
@ -852,7 +819,7 @@ class Prediksi:
. head ( recent_n ) [ column ]
. dropna ( )
)
# print(f"Recent Vals: {recent_vals}")
# Fallback ke semua nilai non-na jika tidak ada recent_vals
if recent_vals . empty :
recent_vals = df [ column ] . dropna ( )
@ -865,10 +832,16 @@ class Prediksi:
# Interval from number of failures
interval = 0.0
if isinstance ( failures_data , dict ) :
val = failures_data . get ( " data " )
if val is not None :
data_list = failures_data . get ( " data " )
# data is a list of objects, extract num_fail from first item
if isinstance ( data_list , list ) and len ( data_list ) > 0 :
first_item = data_list [ 0 ]
if isinstance ( first_item , dict ) :
num_fail = first_item . get ( " num_fail " )
if num_fail is not None :
try :
interval = float ( val )
interval = float ( num_fail )
print ( f " interval for year { yr } : { interval } " )
except Exception :
interval = 0.0
@ -883,11 +856,10 @@ class Prediksi:
else :
avg = pd . to_numeric ( recent_vals , errors = " coerce " ) . fillna ( 0 ) . mean ( )
avg = 0.0 if pd . isna ( avg ) else float ( avg )
preds = np . repeat ( float ( avg ) , n_future )
# print(preds)
else :
# Untuk kolom non-cm, gunakan nilai dari last actual year bila ada,
# Для kolom non-cm, gunakan nilai dari last actual year bila ada,
# jika tidak ada gunakan last available non-NA value, jika tidak ada pakai 0.0
if " is_actual " in df . columns and not df [ df [ " is_actual " ] == 1 ] . empty :
last_actual_year_series = df [ df [ " is_actual " ] == 1 ] [ " year " ]
@ -900,6 +872,7 @@ class Prediksi:
last_actual_year = int ( df [ " year " ] . max ( ) )
row_vals = df [ df [ " year " ] == last_actual_year ]
value = None
if not row_vals . empty :
@ -1067,8 +1040,7 @@ async def main(RELIABILITY_APP_URL=RELIABILITY_APP_URL, assetnum=None, token=Non
return
# Otherwise fetch all assetnums from DB and loop
connections = get_connection ( )
connection = connections [ 0 ] if isinstance ( connections , tuple ) else connections
connection , connection_wo_db = get_connection ( )
if connection is None :
print ( " Database connection failed. " )
return
@ -1078,16 +1050,36 @@ async def main(RELIABILITY_APP_URL=RELIABILITY_APP_URL, assetnum=None, token=Non
cursor . execute ( query_main )
results = cursor . fetchall ( )
for idx , row in enumerate ( results , start = 1 ) :
current_asset = row . get ( " assetnum " ) if hasattr ( row , " get " ) else row [ 0 ]
if not current_asset or str ( current_asset ) . strip ( ) == " " :
print ( f " [ { idx } / { len ( results ) } ] Skipping empty assetnum " )
continue
print ( f " [ { idx } / { len ( results ) } ] Predicting assetnum: { current_asset } " )
# Close connection early as we have the data and don't need it for the async loop
if connection :
connection . close ( )
connection = None
# Concurrency limit to prevent overwhelming DB/API
MAX_CONCURRENT_TASKS = 10
sem = asyncio . Semaphore ( MAX_CONCURRENT_TASKS )
total_assets = len ( results )
print ( f " Starting prediction for { total_assets } assets with { MAX_CONCURRENT_TASKS } concurrent tasks. " )
async def bound_predict ( idx , asset ) :
async with sem :
try :
await prediksi . predict_equipment_data ( current_asset , prediksi . access_token )
if not asset or str ( asset ) . strip ( ) == " " :
print ( f " [ { idx } / { total_assets } ] Skipping empty assetnum " )
return
print ( f " [ { idx } / { total_assets } ] Predicting assetnum: { asset } " )
await prediksi . predict_equipment_data ( asset , prediksi . access_token )
except Exception as e :
print ( f " Error Predicting { current_asset } : { e } " )
print ( f " Error Predicting { asset } : { e } " )
tasks = [ ]
for idx , row in enumerate ( results , start = 1 ) :
current_asset = row . get ( " assetnum " ) if hasattr ( row , " get " ) else row [ 0 ]
tasks . append ( bound_predict ( idx , current_asset ) )
await asyncio . gather ( * tasks )
print ( " Selesai. " )
except Exception as e :
@ -1098,7 +1090,17 @@ async def main(RELIABILITY_APP_URL=RELIABILITY_APP_URL, assetnum=None, token=Non
connection . close ( )
if __name__ == " __main__ " :
asyncio . run (
main ( )
import argparse
parser = argparse . ArgumentParser ( description = " Run equipment prediction " )
parser . add_argument (
" --assetnum " , " -a " ,
type = str ,
default = None ,
help = " Specific assetnum to predict. If not provided, predicts all assets. "
)
args = parser . parse_args ( )
asyncio . run (
main ( assetnum = args . assetnum )
)
