184 lines
7.0 KiB
Python
184 lines
7.0 KiB
Python
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"""采购需求自动推导服务
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销售订单确认 → 按 BOM 展开物料需求 → 对比当前库存 → 自动生成采购建议（缺多少、建议供应商、预计金额）
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"""
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from math import ceil
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from decimal import Decimal
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from typing import List
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from fastapi import HTTPException
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select, func
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from shared.models.database import (
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Product,
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ProductMaterial,
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SalesOrder,
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SalesOrderItem,
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Inventory,
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MaterialSupplier,
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Supplier,
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)
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from ..schemas.purchase_demand_schemas import (
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PurchaseDemandItemResponse,
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PurchaseDemandResponse,
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)
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class PurchaseDemandService:
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"""采购需求推导服务"""
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@staticmethod
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async def calculate_demands(
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db_session: AsyncSession,
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sales_order_ids: List[int],
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) -> PurchaseDemandResponse:
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"""
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核心算法：
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1. 批量查询销售订单 + 明细项
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2. 按 BOM 展开所有成品所需的物料（含损耗率）
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3. 聚合跨订单的同一物料需求量
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4. 对比当前库存，计算缺口
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5. 查询 MaterialSupplier 推荐主供应商
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"""
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# ── 1. 查询销售订单 ──
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order_result = await db_session.execute(
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select(SalesOrder).where(SalesOrder.id.in_(sales_order_ids))
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)
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orders = order_result.scalars().all()
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if not orders:
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raise HTTPException(status_code=404, detail="未找到有效的销售订单")
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order_ids_found = [o.id for o in orders]
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order_nos = [o.order_no for o in orders]
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# ── 2. 查询订单明细（成品列表） ──
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item_result = await db_session.execute(
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select(SalesOrderItem).where(SalesOrderItem.order_id.in_(order_ids_found))
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)
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order_items = item_result.scalars().all()
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if not order_items:
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return PurchaseDemandResponse(
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source_order_ids=order_ids_found,
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source_order_nos=order_nos,
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)
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# ── 3. 按 BOM 展开物料需求 ──
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finished_ids = list({int(i.product_id) for i in order_items})
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bom_result = await db_session.execute(
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select(ProductMaterial, Product)
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.join(Product, ProductMaterial.material_product_id == Product.id)
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.where(ProductMaterial.finished_product_id.in_(finished_ids))
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.where(Product.is_active == True)
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.where(Product.item_type == "material")
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)
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bom_rows = bom_result.all()
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if not bom_rows:
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return PurchaseDemandResponse(
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source_order_ids=order_ids_found,
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source_order_nos=order_nos,
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)
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# 按 finished_product_id 分组 BOM
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bom_by_finished: dict = {}
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for bom, material in bom_rows:
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bom_by_finished.setdefault(int(bom.finished_product_id), []).append((bom, material))
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# 聚合需求量：material_id → { material, required_qty }
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required_qty_map: dict = {}
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for order_item in order_items:
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bom_items = bom_by_finished.get(int(order_item.product_id)) or []
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for bom, material in bom_items:
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qty = (
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Decimal(str(order_item.quantity))
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* Decimal(str(bom.quantity or 0))
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* (1 + Decimal(str(bom.loss_rate or 0)))
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)
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entry = required_qty_map.setdefault(
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material.id,
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{"material": material, "required_qty": Decimal("0")},
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)
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entry["required_qty"] += qty
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if not required_qty_map:
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return PurchaseDemandResponse(
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source_order_ids=order_ids_found,
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source_order_nos=order_nos,
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)
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# ── 4. 对比当前库存 ──
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material_ids = list(required_qty_map.keys())
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stock_result = await db_session.execute(
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select(Inventory.product_id, func.coalesce(func.sum(Inventory.quantity), 0))
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.where(Inventory.product_id.in_(material_ids))
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.group_by(Inventory.product_id)
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)
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stock_map = {row[0]: Decimal(str(row[1] or 0)) for row in stock_result.all()}
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# ── 5. 查询物料-供应商关联（推荐主供应商） ──
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ms_result = await db_session.execute(
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select(MaterialSupplier, Supplier)
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.join(Supplier, MaterialSupplier.supplier_id == Supplier.id)
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.where(MaterialSupplier.product_id.in_(material_ids))
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.where(Supplier.is_active == True)
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.order_by(MaterialSupplier.is_primary.desc(), MaterialSupplier.id.asc())
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)
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ms_rows = ms_result.all()
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# 每个物料取第一个（优先 is_primary=True）
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supplier_map: dict = {}
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for ms, supplier in ms_rows:
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if ms.product_id not in supplier_map:
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supplier_map[ms.product_id] = {
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"supplier_id": supplier.id,
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"supplier_name": supplier.name,
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"lead_time": ms.lead_time,
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}
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# ── 6. 组装响应 ──
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items: List[PurchaseDemandItemResponse] = []
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total_estimated_cost = Decimal("0")
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shortage_count = 0
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for material_id, entry in required_qty_map.items():
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material = entry["material"]
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required_qty = int(ceil(entry["required_qty"]))
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available_qty = stock_map.get(material_id, Decimal("0"))
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shortage_qty = max(required_qty - int(available_qty), 0)
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unit_cost = Decimal(str(material.cost_price or 0))
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estimated_cost = Decimal(str(shortage_qty)) * unit_cost
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total_estimated_cost += estimated_cost
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if shortage_qty > 0:
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shortage_count += 1
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suggested = supplier_map.get(material_id)
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items.append(
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PurchaseDemandItemResponse(
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material_id=material.id,
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material_sku=material.sku,
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material_name=material.name,
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required_quantity=Decimal(str(required_qty)),
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available_quantity=available_qty,
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shortage_quantity=Decimal(str(shortage_qty)),
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unit_cost=unit_cost,
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estimated_cost=estimated_cost,
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suggested_supplier_id=suggested["supplier_id"] if suggested else None,
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suggested_supplier_name=suggested["supplier_name"] if suggested else None,
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supplier_lead_time=suggested["lead_time"] if suggested else None,
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)
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)
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# 按缺口数量降序排列（最缺的排最前）
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items.sort(key=lambda x: (x.shortage_quantity, x.estimated_cost), reverse=True)
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return PurchaseDemandResponse(
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items=items,
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total_estimated_cost=total_estimated_cost,
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shortage_count=shortage_count,
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source_order_ids=order_ids_found,
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source_order_nos=order_nos,
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)
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purchase_demand_service = PurchaseDemandService()
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