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80 lines
3.7 KiB
Python
80 lines
3.7 KiB
Python
from datetime import datetime
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from sqlalchemy import select, func, cast, Numeric
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from sqlalchemy.orm import Session
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from sqlalchemy import and_
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from sqlalchemy.sql import not_
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from src.maximo.model import WorkOrderData # Assuming this is where your model is
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from src.database.core import CollectorDbSession
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async def get_cm_cost_summary(collector_db: CollectorDbSession, last_oh_date:datetime, upcoming_oh_date:datetime):
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query = select(
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WorkOrderData.location,
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(func.sum(WorkOrderData.total_cost_max).cast(Numeric) / func.count(WorkOrderData.wonum)).label('avg_cost')
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).where(
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and_(
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# WorkOrderData.wo_start >= last_oh_date,
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# WorkOrderData.wo_start <= upcoming_oh_date,
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WorkOrderData.worktype.in_(['CM', 'EM', 'PROACTIVE']),
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WorkOrderData.system_tag.in_(['HPB', 'AH', 'APC', 'SCR', 'CL', 'DM', 'CRH', 'ASH', 'BAD', 'DS', 'WTP',
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'MT', 'SUP', 'DCS', 'FF', 'EG', 'AI', 'SPS', 'EVM', 'SCW', 'KLH', 'CH',
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'TUR', 'LOT', 'HRH', 'ESP', 'CAE', 'GMC', 'BFT', 'LSH', 'CHB', 'BSS',
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'LOS', 'LPB', 'SAC', 'CP', 'EHS', 'RO', 'GG', 'MS', 'CW', 'SO', 'ATT',
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'AFG', 'EHB', 'RP', 'FO', 'PC', 'APE', 'AF', 'DMW', 'BRS', 'GEN', 'ABS',
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'CHA', 'TR', 'H2', 'BDW', 'LOM', 'ACR', 'AL', 'FW', 'COND', 'CCCW', 'IA',
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'GSS', 'BOL', 'SSB', 'CO', 'OA', 'CTH-UPD', 'AS', 'DP']),
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WorkOrderData.reportdate.is_not(None),
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WorkOrderData.actstart.is_not(None),
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WorkOrderData.actfinish.is_not(None),
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WorkOrderData.unit.in_([3, 0]),
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WorkOrderData.reportdate >= datetime.strptime('2015-01-01', '%Y-%m-%d'),
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not_(WorkOrderData.wonum.like('T%'))
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)
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).group_by(
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WorkOrderData.location
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).order_by(
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func.count(WorkOrderData.wonum).desc()
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)
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result = await collector_db.execute(query)
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data = result.all()
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return {
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data.location: data.avg_cost for data in data
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}
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async def get_oh_cost_summary(collector_db: CollectorDbSession, last_oh_date:datetime, upcoming_oh_date:datetime):
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query = select(
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WorkOrderData.location,
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(func.sum(WorkOrderData.total_cost_max).cast(Numeric) / func.count(WorkOrderData.wonum)).label('avg_cost')
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).where(
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and_(
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# WorkOrderData.wo_start >= last_oh_date,
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# WorkOrderData.wo_start <= upcoming_oh_date,
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WorkOrderData.worktype.in_(['OH']),
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WorkOrderData.system_tag.in_(['HPB', 'AH', 'APC', 'SCR', 'CL', 'DM', 'CRH', 'ASH', 'BAD', 'DS', 'WTP',
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'MT', 'SUP', 'DCS', 'FF', 'EG', 'AI', 'SPS', 'EVM', 'SCW', 'KLH', 'CH',
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'TUR', 'LOT', 'HRH', 'ESP', 'CAE', 'GMC', 'BFT', 'LSH', 'CHB', 'BSS',
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'LOS', 'LPB', 'SAC', 'CP', 'EHS', 'RO', 'GG', 'MS', 'CW', 'SO', 'ATT',
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'AFG', 'EHB', 'RP', 'FO', 'PC', 'APE', 'AF', 'DMW', 'BRS', 'GEN', 'ABS',
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'CHA', 'TR', 'H2', 'BDW', 'LOM', 'ACR', 'AL', 'FW', 'COND', 'CCCW', 'IA',
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'GSS', 'BOL', 'SSB', 'CO', 'OA', 'CTH-UPD', 'AS', 'DP']),
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WorkOrderData.reportdate.is_not(None),
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WorkOrderData.actstart.is_not(None),
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WorkOrderData.actfinish.is_not(None),
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WorkOrderData.unit.in_([3, 0]),
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WorkOrderData.reportdate >= datetime.strptime('2015-01-01', '%Y-%m-%d'),
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not_(WorkOrderData.wonum.like('T%'))
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)
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).group_by(
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WorkOrderData.location
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).order_by(
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func.count(WorkOrderData.wonum).desc()
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)
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result = await collector_db.execute(query)
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data = result.all()
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return {
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data.location: data.avg_cost for data in data
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}
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