# This file is part of Tryton. The COPYRIGHT file at the top level of # this repository contains the full copyright notices and license terms. import datetime import operator from collections import defaultdict from trytond.model import ModelSQL, ValueMixin, fields from trytond.transaction import Transaction from trytond.pool import Pool, PoolMeta from trytond.tools import grouped_slice supply_period = fields.TimeDelta("Supply Period") class PurchaseConfiguration(metaclass=PoolMeta): __name__ = 'purchase.configuration' supply_period = fields.MultiValue(supply_period) class PurchaseConfigurationSupplyPeriod(ModelSQL, ValueMixin): "Purchase Configuration Supply Period" __name__ = 'purchase.configuration.supply_period' supply_period = supply_period class PurchaseRequest(metaclass=PoolMeta): 'Purchase Request' __name__ = 'purchase.request' @classmethod def _get_origin(cls): origins = super(PurchaseRequest, cls)._get_origin() return origins | {'stock.order_point'} @classmethod def generate_requests(cls, products=None, warehouses=None): """ For each product compute the purchase request that must be created today to meet product outputs. If products is specified it will compute the purchase requests for the selected products. If warehouses is specified it will compute the purchase request necessary for the selected warehouses. """ pool = Pool() OrderPoint = pool.get('stock.order_point') Product = pool.get('product.product') Location = pool.get('stock.location') User = pool.get('res.user') company = User(Transaction().user).company if warehouses is None: # fetch warehouses: warehouses = Location.search([ ('type', '=', 'warehouse'), ]) warehouse_ids = [w.id for w in warehouses] # fetch order points order_points = OrderPoint.search([ ('warehouse_location', '!=', None), ('company', '=', company.id if company else None), ]) # index them by product product2ops = {} product2ops_other = {} for order_point in order_points: if order_point.type == 'purchase': dict_ = product2ops else: dict_ = product2ops_other dict_[ (order_point.warehouse_location.id, order_point.product.id) ] = order_point if products is None: # fetch goods and assets # ordered by ids to speedup reduce_ids in products_by_location products = Product.search([ ('type', 'in', ['goods', 'assets']), ('consumable', '=', False), ('purchasable', '=', True), ], order=[('id', 'ASC')]) product_ids = [p.id for p in products] # aggregate product by minimum supply date date2products = {} for product in products: min_date, max_date = cls.get_supply_dates( product, company=company.id) date2products.setdefault((min_date, max_date), []).append(product) # compute requests new_requests = [] for dates, dates_products in date2products.items(): min_date, max_date = dates for sub_products in grouped_slice(dates_products): sub_products = list(sub_products) product_ids = [p.id for p in sub_products] with Transaction().set_context(forecast=True, stock_date_end=min_date or datetime.date.max): pbl = Product.products_by_location(warehouse_ids, with_childs=True, grouping_filter=(product_ids,)) for warehouse_id in warehouse_ids: min_date_qties = defaultdict(int, ((x, pbl.pop((warehouse_id, x), 0)) for x in product_ids)) # Do not compute shortage for product # with different order point product_ids = [ p.id for p in sub_products if (warehouse_id, p.id) not in product2ops_other] # Search for shortage between min-max shortages = cls.get_shortage(warehouse_id, product_ids, min_date, max_date, min_date_qties=min_date_qties, order_points=product2ops) for product in sub_products: if product.id not in shortages: continue shortage_date, product_quantity = shortages[product.id] if shortage_date is None or product_quantity is None: continue order_point = product2ops.get( (warehouse_id, product.id)) # generate request values request = cls.compute_request(product, warehouse_id, shortage_date, product_quantity, company, order_point) new_requests.append(request) # delete purchase requests without a purchase line products = set(products) reqs = cls.search([ ('purchase_line', '=', None), ('origin', 'like', 'stock.order_point,%'), ]) reqs = [r for r in reqs if r.product in products] cls.delete(reqs) new_requests = cls.compare_requests(new_requests) cls.create_requests(new_requests) @classmethod def create_requests(cls, new_requests): to_save = [] for new_req in new_requests: if new_req.supply_date == datetime.date.max: new_req.supply_date = None if new_req.computed_quantity > 0: to_save.append(new_req) cls.save(to_save) @classmethod def compare_requests(cls, new_requests): """ Compare new_requests with already existing request to avoid to re-create existing requests. """ pool = Pool() Uom = pool.get('product.uom') Request = pool.get('purchase.request') requests = Request.search([ ('purchase_line.moves', '=', None), ('purchase_line.purchase.state', '!=', 'cancel'), ('origin', 'like', 'stock.order_point,%'), ]) # Fetch data from existing requests existing_req = {} for request in requests: pline = request.purchase_line # Skip incoherent request if (request.product != pline.product or request.warehouse != pline.purchase.warehouse): continue # Take smallest amount between request and purchase line pline_qty = Uom.compute_qty(pline.unit, pline.quantity, pline.product.default_uom, round=False) quantity = min(request.computed_quantity, pline_qty) existing_req.setdefault( (request.product.id, request.warehouse.id), []).append({ 'supply_date': ( request.supply_date or datetime.date.max), 'quantity': quantity, }) for i in existing_req.values(): i.sort(key=lambda r: r['supply_date']) # Update new requests to take existing requests into account new_requests.sort(key=operator.attrgetter('supply_date')) for new_req in new_requests: for old_req in existing_req.get( (new_req.product.id, new_req.warehouse.id), []): if old_req['supply_date'] <= new_req.supply_date: new_req.computed_quantity = max(0.0, new_req.computed_quantity - old_req['quantity']) new_req.quantity = Uom.compute_qty( new_req.product.default_uom, new_req.computed_quantity, new_req.uom, round=False) new_req.quantity = new_req.uom.ceil(new_req.quantity) old_req['quantity'] = max(0.0, old_req['quantity'] - new_req.computed_quantity) else: break return new_requests @classmethod def get_supply_dates(cls, product, **pattern): """ Return the minimal interval of earliest supply dates for a product. """ Date = Pool().get('ir.date') min_date = None max_date = None today = Date.today() for product_supplier in product.product_suppliers_used(**pattern): supply_date = product_supplier.compute_supply_date(date=today) next_day = today + product_supplier.get_supply_period() next_supply_date = product_supplier.compute_supply_date( date=next_day) if (not min_date) or supply_date < min_date: min_date = supply_date if (not max_date): max_date = next_supply_date if supply_date > min_date and supply_date < max_date: max_date = supply_date if next_supply_date < max_date: max_date = next_supply_date if not min_date: min_date = datetime.date.max max_date = datetime.date.max return (min_date, max_date) @classmethod def compute_request(cls, product, location_id, shortage_date, product_quantity, company, order_point=None, supplier_pattern=None): """ Return the value of the purchase request which will answer to the needed quantity at the given date. I.e: the latest purchase date, the expected supply date and the prefered supplier. """ pool = Pool() Uom = pool.get('product.uom') Request = pool.get('purchase.request') if supplier_pattern is None: supplier_pattern = {} else: supplier_pattern = supplier_pattern.copy() supplier_pattern['company'] = company.id supplier, purchase_date = cls.find_best_supplier(product, shortage_date) uom = product.purchase_uom or product.default_uom target_quantity = order_point.target_quantity if order_point else 0.0 computed_quantity = target_quantity - product_quantity product_quantity = uom.ceil(product_quantity) quantity = Uom.compute_qty( product.default_uom, computed_quantity, uom, round=False) quantity = uom.ceil(quantity) if order_point: origin = 'stock.order_point,%s' % order_point.id else: origin = 'stock.order_point,-1' return Request(product=product, party=supplier and supplier or None, quantity=quantity, uom=uom, computed_quantity=computed_quantity, computed_uom=product.default_uom, purchase_date=purchase_date, supply_date=shortage_date, stock_level=product_quantity, company=company, warehouse=location_id, origin=origin, ) @classmethod def get_shortage(cls, location_id, product_ids, min_date, max_date, min_date_qties, order_points): """ Return for each product the first date between min_date and max_date where the stock quantity is less than the minimal quantity and the smallest stock quantity in the interval or None if there is no date where stock quantity is less than the minimal quantity. The minimal quantity comes from the order point or is zero. min_date_qty is the quantities for each products at the min_date. order_points is a dictionary that links products to order point. """ Product = Pool().get('product.product') res_dates = {} res_qties = {} min_quantities = {} for product_id in product_ids: order_point = order_points.get((location_id, product_id)) if order_point: min_quantities[product_id] = order_point.min_quantity else: min_quantities[product_id] = 0.0 current_date = min_date current_qties = min_date_qties.copy() while (current_date < max_date) or (current_date == min_date): for product_id in product_ids: current_qty = current_qties[product_id] min_quantity = min_quantities[product_id] res_qty = res_qties.get(product_id) res_date = res_dates.get(product_id) if min_quantity is not None and current_qty < min_quantity: if not res_date: res_dates[product_id] = current_date if (not res_qty) or (current_qty < res_qty): res_qties[product_id] = current_qty if current_date == datetime.date.max: break current_date += datetime.timedelta(1) # Update current quantities with next moves with Transaction().set_context(forecast=True, stock_date_start=current_date, stock_date_end=current_date): pbl = Product.products_by_location([location_id], with_childs=True, grouping_filter=(product_ids,)) for key, qty in pbl.items(): _, product_id = key current_qties[product_id] += qty return dict((x, (res_dates.get(x), res_qties.get(x))) for x in product_ids)