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refactor: externalize SQL WHERE clause generation and update cost data column names.

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main
MrWaradana 3 weeks ago
parent 84bc9ec06e
commit 052b94d8e0
9 changed files with 183 additions and 246 deletions
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src/equipment/__pycache__/service.cpython-311.pyc
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106
src/equipment/service.py
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@ -23,6 +23,7 @@ import httpx
from src.modules.equipment.run import main
from src.modules.equipment.Prediksi import main as predict_main
from src.modules.equipment.Eac import main as eac_main
from src.modules.equipment.where_query_sql import get_where_query_sql_all_worktype
import datetime
import math
@ -120,99 +121,26 @@ CATEGORY_ROLLUP_CHILDREN = _build_category_rollup_children()
logger = logging.getLogger(__name__)
MAXIMO_SQL = text(
"""
SELECT
*
FROM public.wo_maximo AS a
WHERE a.asset_unit = '3'
AND a.asset_assetnum = :assetnum
AND a.wonum NOT LIKE 'T%'
AND (
(a.worktype = 'CM' AND a.wojp8 != 'S1')
OR (a.worktype <> 'CM')
);
"""
)
JOINED_MAXIMO_SQL = text(
"""
SELECT *
FROM public.wo_maximo a
LEFT JOIN public.wo_maximo_labtrans b
ON b.wonum = a.wonum
LEFT JOIN lcc_ms_manpower emp
ON UPPER(TRIM(emp."ID Number")) = UPPER(TRIM(b.laborcode))
WHERE
a.asset_unit = '3'
AND a.wonum NOT LIKE 'T%'
AND a.asset_assetnum = :assetnum
AND (
a.actfinish IS NULL
OR a.actstart IS NULL
OR (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0) <= 730
)
AND (
(a.worktype = 'CM' AND a.wojp8 != 'S1')
OR (a.worktype <> 'CM')
)
AND (
a.description NOT ILIKE '%U4%'
OR (
a.description ILIKE '%U3%'
AND a.description ILIKE '%U4%'
)
);
"""
)
async def _fetch_maximo_records(
*, session: AsyncSession, assetnum: str
) -> list[dict[str, Any]]:
"""Fetch Maximo rows with a retry to mask transient collector failures."""
query = MAXIMO_SQL.bindparams(assetnum=assetnum)
try:
result = await session.execute(query)
return result.mappings().all()
except AsyncpgInterfaceError as exc:
logger.warning(
"Collector session closed while fetching Maximo data for %s. Retrying once.",
assetnum,
)
try:
async with collector_async_session() as retry_session:
retry_result = await retry_session.execute(query)
return retry_result.mappings().all()
except Exception as retry_exc:
logger.error(
"Retrying Maximo query failed for %s: %s",
assetnum,
retry_exc,
exc_info=True,
)
except SQLAlchemyError as exc:
logger.error(
"Failed to fetch Maximo data for %s: %s", assetnum, exc, exc_info=True
)
except Exception as exc:
logger.exception(
"Unexpected error while fetching Maximo data for %s", assetnum
)
return []
async def _fetch_joined_maximo_records(
*, session: AsyncSession, assetnum: str
) -> list[dict[str, Any]]:
"""Fetch Joined Maximo rows with a retry to mask transient collector failures."""
query = JOINED_MAXIMO_SQL.bindparams(assetnum=assetnum)
where_query = get_where_query_sql_all_worktype(assetnum)
JOINED_MAXIMO_SQL = text(
f"""
SELECT *
FROM public.wo_maximo a
LEFT JOIN public.wo_maximo_labtrans b
ON b.wonum = a.wonum
LEFT JOIN lcc_ms_manpower emp
ON UPPER(TRIM(emp."ID Number")) = UPPER(TRIM(b.laborcode))
{where_query}
"""
)
try:
result = await session.execute(query)
result = await session.execute(JOINED_MAXIMO_SQL)
return result.mappings().all()
except AsyncpgInterfaceError as exc:
logger.warning(
@ -221,7 +149,7 @@ async def _fetch_joined_maximo_records(
)
try:
async with collector_async_session() as retry_session:
retry_result = await retry_session.execute(query)
retry_result = await retry_session.execute(JOINED_MAXIMO_SQL)
return retry_result.mappings().all()
except Exception as retry_exc:
logger.error(
@ -358,7 +286,7 @@ async def get_master_by_assetnum(
min_seq = equipment_record.minimum_eac_seq if equipment_record else None
min_eac_year = equipment_record.minimum_eac_year if equipment_record else None
maximo_record = await _fetch_maximo_records(
maximo_record = await _fetch_joined_maximo_records(
session=collector_db_session, assetnum=assetnum
)
joined_maximo_record = await _fetch_joined_maximo_records(

239
src/modules/equipment/Prediksi.py
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@ -86,22 +86,14 @@ class Prediksi:
query = """
SELECT
tahun AS year,
raw_cm_interval AS cm_interval,
raw_cm_material_cost AS cm_cost,
raw_cm_labor_time AS cm_labor_time,
raw_cm_labor_human AS cm_labor_human,
raw_pm_interval AS pm_interval,
raw_pm_material_cost AS pm_cost,
raw_pm_labor_time AS pm_labor_time,
raw_pm_labor_human AS pm_labor_human,
raw_oh_interval AS oh_interval,
raw_oh_material_cost AS oh_cost,
raw_oh_labor_time AS oh_labor_time,
raw_oh_labor_human AS oh_labor_human,
raw_predictive_material_cost AS predictive_material_cost,
raw_predictive_labor_time AS predictive_labor_time,
raw_predictive_labor_human AS predictive_labor_human,
raw_predictive_interval AS predictive_interval
rc_cm_material_cost,
rc_cm_labor_cost,
rc_pm_material_cost,
rc_pm_labor_cost,
rc_oh_material_cost,
rc_oh_labor_cost,
rc_predictive_material_cost,
rc_predictive_labor_cost
FROM lcc_equipment_tr_data
WHERE assetnum = %s
and is_actual=1
@ -188,62 +180,65 @@ class Prediksi:
# Query untuk insert data
insert_query = """
INSERT INTO lcc_equipment_tr_data (
id,
id,
seq,
is_actual,
raw_pm_interval,
tahun, assetnum,
raw_cm_interval, raw_cm_material_cost, raw_cm_labor_time, raw_cm_labor_human,
raw_pm_material_cost, raw_pm_labor_time, raw_pm_labor_human,
raw_oh_interval, raw_oh_material_cost, raw_oh_labor_time, raw_oh_labor_human,
raw_predictive_interval, raw_predictive_material_cost, raw_predictive_labor_time, raw_predictive_labor_human,
created_by, created_at
tahun, assetnum,
rc_cm_material_cost,
rc_cm_labor_cost,
rc_pm_material_cost,
rc_pm_labor_cost,
rc_oh_material_cost,
rc_oh_labor_cost,
rc_predictive_material_cost,
rc_predictive_labor_cost,
created_by, created_at
) VALUES (
%s, %s, 0, %s, %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, 'Sys', NOW()
)
"""
# If a token was provided, store locally so fetch_api_data can use/refresh it
if token:
self.access_token = token
# Fetch data from external API (uses instance access_token and will try refresh on 403)
async def fetch_api_data(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 403, try to refresh the access token and retry once
if status == 403:
print("Received 403 from reliability API, attempting to refresh access token...")
new_access = await self.refresh_access_token()
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 refresh: {e2}")
return {}
print(f"HTTP error occurred: {e}")
return {}
except httpx.HTTPError as e:
print(f"HTTP error occurred: {e}")
return {}
# if token:
# self.access_token = token
# # Fetch data from external API (uses instance access_token and will try refresh on 403)
# async def fetch_api_data(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 403, try to refresh the access token and retry once
# if status == 403:
# print("Received 403 from reliability API, attempting to refresh access token...")
# new_access = await self.refresh_access_token()
# 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 refresh: {e2}")
# return {}
# print(f"HTTP error occurred: {e}")
# return {}
# except httpx.HTTPError as e:
# print(f"HTTP error occurred: {e}")
# return {}
# Menyiapkan data untuk batch insert
# print(f"Data to be inserted: {data}")
@ -252,71 +247,63 @@ class Prediksi:
max_seq = max_seq + 1
# (token already stored before defining fetch_api_data)
# maintain previous cm_interval between iterations using attribute on fetch_api_data
if not hasattr(fetch_api_data, "prev_cm"):
fetch_api_data.prev_cm = None
# if not hasattr(fetch_api_data, "prev_cm"):
# fetch_api_data.prev_cm = None
# Update values from API (current year)
api_data = await fetch_api_data(equipment_id, row["year"])
if api_data and "data" in api_data and isinstance(api_data["data"], list) and len(api_data["data"]) > 0:
try:
cur_cm = float(api_data["data"][0].get("num_fail", row.get("cm_interval", 1)))
except Exception:
cur_cm = float(row.get("cm_interval", 1)) if not pd.isna(row.get("cm_interval", None)) else 1.0
else:
try:
val = float(row.get("cm_interval", 1))
cur_cm = val if val >= 1 else 1.0
except Exception:
cur_cm = 1.0
# api_data = await fetch_api_data(equipment_id, row["year"])
# if api_data and "data" in api_data and isinstance(api_data["data"], list) and len(api_data["data"]) > 0:
# try:
# cur_cm = float(api_data["data"][0].get("num_fail", row.get("cm_interval", 1)))
# except Exception:
# cur_cm = float(row.get("cm_interval", 1)) if not pd.isna(row.get("cm_interval", None)) else 1.0
# else:
# try:
# val = float(row.get("cm_interval", 1))
# cur_cm = val if val >= 1 else 1.0
# except Exception:
# cur_cm = 1.0
# Determine previous cm_interval: prefer stored prev_cm, otherwise try API for previous year, else fallback to cur_cm
if fetch_api_data.prev_cm is not None:
prev_cm = float(fetch_api_data.prev_cm)
else:
try:
api_prev = await fetch_api_data(equipment_id, int(row["year"]) - 1)
if api_prev and "data" in api_prev and isinstance(api_prev["data"], list) and len(api_prev["data"]) > 0:
prev_cm = float(api_prev["data"][0].get("num_fail", cur_cm))
else:
# attempt to use any available previous value from the row if present, otherwise fallback to current
prev_cm = float(row.get("cm_interval", cur_cm)) if not pd.isna(row.get("cm_interval", None)) else cur_cm
except Exception:
prev_cm = cur_cm
# if fetch_api_data.prev_cm is not None:
# prev_cm = float(fetch_api_data.prev_cm)
# else:
# try:
# api_prev = await fetch_api_data(equipment_id, int(row["year"]) - 1)
# if api_prev and "data" in api_prev and isinstance(api_prev["data"], list) and len(api_prev["data"]) > 0:
# prev_cm = float(api_prev["data"][0].get("num_fail", cur_cm))
# else:
# # attempt to use any available previous value from the row if present, otherwise fallback to current
# prev_cm = float(row.get("cm_interval", cur_cm)) if not pd.isna(row.get("cm_interval", None)) else cur_cm
# except Exception:
# prev_cm = cur_cm
# compute difference: current year interval minus previous year interval
try:
cm_interval_diff = float(cur_cm) - float(prev_cm)
except Exception:
cm_interval_diff = 0.0
# try:
# cm_interval_diff = float(cur_cm) - float(prev_cm)
# except Exception:
# cm_interval_diff = 0.0
# append record using the difference for raw_cm_interval
records_to_insert.append(
(
str(uuid4()), # id
int(max_seq), # seq
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,
int(row["year"]),
equipment_id,
cm_interval_diff,
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.get("rc_cm_material_cost", 0)) if not pd.isna(row.get("rc_cm_material_cost", 0)) else 0.0,
float(row.get("rc_cm_labor_cost", 0)) if not pd.isna(row.get("rc_cm_labor_cost", 0)) else 0.0,
float(row.get("rc_pm_material_cost", 0)) if not pd.isna(row.get("rc_pm_material_cost", 0)) else 0.0,
float(row.get("rc_pm_labor_cost", 0)) if not pd.isna(row.get("rc_pm_labor_cost", 0)) else 0.0,
float(row.get("rc_oh_material_cost", 0)) if not pd.isna(row.get("rc_oh_material_cost", 0)) else 0.0,
float(row.get("rc_oh_labor_cost", 0)) if not pd.isna(row.get("rc_oh_labor_cost", 0)) else 0.0,
float(row.get("rc_predictive_material_cost", 0)) if not pd.isna(row.get("rc_predictive_material_cost", 0)) else 0.0,
float(row.get("rc_predictive_labor_cost", 0)) if not pd.isna(row.get("rc_predictive_labor_cost", 0)) else 0.0,
)
)
# store current cm for next iteration
fetch_api_data.prev_cm = cur_cm
# fetch_api_data.prev_cm = cur_cm
# Eksekusi batch insert
cursor.executemany(insert_query, records_to_insert)
@ -788,24 +775,26 @@ class Prediksi:
if "is_actual" in df.columns:
recent_df = df[df["is_actual"] == 1]
recent_n = recent_df.shape[0]
avg_recent = recent_df[column].mean()
print(f"avg_recent: {avg_recent}")
else:
recent_df = df
recent_n = df.shape[0]
recent_n = max(1, recent_n)
recent_vals = (
recent_df.sort_values("year", ascending=False)
recent_df.sort_values("year", ascending=True)
.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()
# Jika masih kosong, pakai default (interval minimal 1, lainnya 0)
if recent_vals.empty:
avg = 0.0
avg = 0.0
else:
# Pastikan numeric; jika gagal, pakai mean dari yang bisa dikonversi
try:
@ -818,7 +807,7 @@ class Prediksi:
avg = max(0.0, avg)
preds = np.repeat(float(avg), n_future)
print(preds)
else:
# Untuk 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
@ -980,14 +969,14 @@ 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:

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src/modules/equipment/insert_actual_data.py
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@ -8,7 +8,7 @@ from datetime import datetime
import sys
import os
import httpx
from src.modules.equipment.where_query_sql import get_where_query_sql
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from config import get_connection, get_production_connection
@ -106,6 +106,7 @@ def get_recursive_query(cursor, assetnum, worktype="CM"):
# ) as d group by d.tahun
# ;
# """
where_query = get_where_query_sql(assetnum, worktype)
query = f"""
select
@ -122,14 +123,8 @@ def get_recursive_query(cursor, assetnum, worktype="CM"):
from public.wo_maximo as a
LEFT JOIN public.wo_maximo_labtrans AS b
ON b.wonum = a.wonum
where
a.asset_unit = '3'
{f"AND a.worktype = '{worktype}'" if worktype != 'CM' else "AND a.worktype in ('CM', 'PROACTIVE', 'WA')"}
AND a.asset_assetnum = '{assetnum}'
and a.wonum not like 'T%'
{f"AND a.wojp8 != 'S1'" if worktype == 'CM' else ""}
group by DATE_PART('year', a.reportdate)
having ROUND(SUM(EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600), 2) <= 730;
{where_query}
group by DATE_PART('year', a.reportdate);
"""
# Eksekusi query dan fetch hasil
cursor.execute(query)
@ -149,7 +144,7 @@ def get_labour_cost_totals(cursor, assetnum: str, worktype: str) -> dict:
"""Return yearly labor cost totals for a worktype using the standardized query."""
if not assetnum or not worktype:
return {}
where_query = get_where_query_sql(assetnum, worktype)
query = f"""
SELECT
EXTRACT(YEAR FROM x.reportdate)::int AS tahun,
@ -173,25 +168,12 @@ FROM (
a.wonum,
a.reportdate,
CASE
WHEN (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0) = 0
THEN 1
ELSE (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0)
WHEN EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0 = 0 THEN 1
WHEN EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0 > 730 THEN 1
ELSE EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0
END AS jumlah_jam_kerja
FROM public.wo_maximo a
WHERE
a.asset_unit = '3'
AND a.wonum NOT LIKE 'T%'
AND a.asset_assetnum = '{assetnum}'
AND (EXTRACT(EPOCH FROM (a.actfinish - a.actstart)) / 3600.0) <= 730
AND a.worktype = '{worktype}'
AND (
a.description NOT ILIKE '%U4%'
OR (
a.description ILIKE '%U3%'
AND a.description ILIKE '%U4%'
)
)
{where_query}
) bw
LEFT JOIN public.wo_maximo_labtrans b
ON b.wonum = bw.wonum

10
src/modules/equipment/run.py
Unescape Escape View File

@ -17,11 +17,11 @@ 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:
prediction_result = await predict_run()

38
src/modules/equipment/where_query_sql.py
Unescape Escape View File

@ -0,0 +1,38 @@
def get_where_query_sql(assetnum, worktype):
where_query = f"""
where
a.asset_unit = '3'
and a.wonum not like 'T%'
AND a.asset_assetnum = '{assetnum}'
{f"AND a.worktype = '{worktype}'" if worktype != 'CM' else "AND a.worktype in ('CM', 'PROACTIVE', 'EM')"}
{f"AND a.wojp8 != 'S1'" if worktype == 'CM' else ""}
AND (
a.description NOT ILIKE '%U4%'
OR (
a.description ILIKE '%U3%'
AND a.description ILIKE '%U4%'
)
)
"""
return where_query
def get_where_query_sql_all_worktype(assetnum):
where_query = f"""
where
a.asset_unit = '3'
and a.wonum not like 'T%'
AND a.asset_assetnum = '{assetnum}'
AND (
(a.worktype = 'CM' AND a.wojp8 != 'S1')
OR (a.worktype <> 'CM')
)
AND (
a.description NOT ILIKE '%U4%'
OR (
a.description ILIKE '%U3%'
AND a.description ILIKE '%U4%'
)
)
"""
return where_query
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