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134 lines
4.7 KiB
Python
134 lines
4.7 KiB
Python
import random
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from typing import Optional
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from sqlalchemy import Delete, Select
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from src.auth.service import CurrentUser
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from src.database.core import DbSession
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from src.scope_equipment.model import ScopeEquipment
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from src.scope_equipment.service import get_by_scope_name
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from src.overhaul_activity.service import get_all_by_session_id
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# async def get_all_budget_constrains(
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# *, db_session: DbSession, session_id: str, cost_threshold: float = 100000000
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# ):
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# At the module level, add this dictionary to store persistent EAF values
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_equipment_eaf_cache = {}
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import random
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async def get_all_budget_constrains(
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*, db_session: DbSession, session_id: str, cost_threshold: float = 100000000
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):
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"""Get all overhaul overview with EAF values that sum to 100%."""
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equipments = await get_all_by_session_id(db_session=db_session, overhaul_session_id=session_id)
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# If no equipments found, return empty list
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if not equipments:
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return [], []
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# Create or retrieve persistent EAF values
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global _equipment_eaf_cache
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# Generate EAF values for new equipment IDs
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equipment_ids = [equipment.id for equipment in equipments]
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# Generate new random EAF values if they don't exist
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if not _equipment_eaf_cache or set(equipment_ids) != set(_equipment_eaf_cache.keys()):
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total_eaf = 100.0
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remaining_items = len(equipment_ids)
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_equipment_eaf_cache.clear()
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# Ensure minimum EAF value for each equipment
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min_eaf = 1.0 # Minimum 1% for each equipment
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reserved_eaf = min_eaf * remaining_items
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distributable_eaf = total_eaf - reserved_eaf
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for eq_id in equipment_ids[:-1]: # All except last item
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if remaining_items > 1:
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# Generate a random value between min_eaf and the remaining distributable EAF
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max_allowed = distributable_eaf / (remaining_items - 1)
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eaf = round(min_eaf + random.uniform(0, max_allowed), 2)
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_equipment_eaf_cache[eq_id] = eaf
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distributable_eaf -= (eaf - min_eaf)
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remaining_items -= 1
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# Assign remaining EAF to last item, ensuring it's at least min_eaf
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_equipment_eaf_cache[equipment_ids[-1]] = round(distributable_eaf + min_eaf, 2)
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# Create result array of dictionaries
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result = [
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{
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"id": equipment.id,
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"assetnum": equipment.assetnum,
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"location_tag": equipment.equipment.location_tag,
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"name": equipment.equipment.name,
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"total_cost": equipment.material_cost + equipment.service_cost,
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"eaf_contribution": _equipment_eaf_cache[equipment.id]
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}
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for equipment in equipments
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]
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# Sort by EAF contribution (highest to lowest)
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result.sort(key=lambda x: x["eaf_contribution"], reverse=True)
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# Filter equipment up to threshold
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cumulative_cost = 0
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included_results = []
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for equipment in result:
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cumulative_cost += equipment["total_cost"]
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if cumulative_cost >= cost_threshold:
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break
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included_results.append(equipment)
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# Rest equipment is consequence list
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consequence_results = result[len(included_results):]
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#Sort
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consequence_results.sort(key=lambda x: x["eaf_contribution"], reverse=True)
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included_results.sort(key=lambda x: x["eaf_contribution"], reverse=True)
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return included_results, consequence_results
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# """Get all overhaul overview with EAF values that sum to 100%."""
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# # equipments = await get_by_scope_name(db_session=db_session, scope_name=scope_name)
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# equipments = await get_all_by_session_id(db_session=db_session, overhaul_session_id=session_id)
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# # If no equipments found, return empty list
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# if not equipments:
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# return []
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# # Create result array of dictionaries
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# result = [
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# {
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# "id": equipment.id,
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# "assetnum": equipment.assetnum,
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# "location_tag": equipment.equipment.location_tag,
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# "name": equipment.equipment.name,
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# "total_cost": equipment.material_cost + equipment.service_cost
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# "eaf_contribution": ## Create Dummy % number, each equipment has different value
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# }
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# for equipment in equipments
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# ]
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# result.sort(key=lambda x: x["eaf_contribution"], reverse=True) #Sort from biggest contribution
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# # Filter equipment up to threshold
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# cumulative_cost = 0
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# included_results = []
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# for equipment in result:
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# cumulative_cost += equipment["total_cost"]
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# if cumulative_cost >= cost_threshold:
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# break
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# included_results.append(equipment)
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# # rest equipemnt is consequence list
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# consequence_results = result[len(included_results):]
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# return included_results ,consequence_results
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