Public release from ruodoo-project: 19.0 - 2026-05-10 21:19:01 UTC
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mklab_forecast_mrp/models/forecast.py
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236
mklab_forecast_mrp/models/forecast.py
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# -*- coding: utf-8 -*-
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from odoo import models, fields, api, exceptions
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from datetime import timedelta, datetime
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from collections import defaultdict
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import logging
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_logger = logging.getLogger(__name__)
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class MklabForecast(models.Model):
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_name = 'mklab.forecast'
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name = fields.Char(string='Название', compute='_compute_name')
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start_date = fields.Date(string='Дата прогноза', required=True)
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forecast_line_ids = fields.One2many(
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comodel_name='mklab.forecastline',
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inverse_name='forecast_id',
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string='Строки',
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)
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partner_ids = fields.Many2many(
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comodel_name='res.partner',
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string='Ограничить контрагентами',
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)
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expected_growth = fields.Float(
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string='Ожидаемый рост продаж при акции, %',
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required=True,
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default=20,
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)
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is_promo = fields.Boolean(string='Запланирована акция', compute='_compute_is_promo')
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is_ready_to_calc = fields.Boolean(string='Отправить на расчет')
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total_amount = fields.Float(string='Итого', compute='_compute_total_amount')
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state = fields.Selection(
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selection=[('draft', 'Черновик'), ('active', 'Утвержден')],
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string='Статус',
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default='draft',
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)
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def _compute_name(self):
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for s in self:
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s.name = str(s.start_date) if s.start_date else ''
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def _compute_total_amount(self):
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for s in self:
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s.total_amount = sum(s.forecast_line_ids.mapped(lambda r: r.total_amount))
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def _compute_is_promo(self):
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for s in self:
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promos = self.env['mklab.marketaction'].search([
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('start_date', '<=', s.start_date),
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('end_date', '>=', s.start_date),
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])
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s.is_promo = bool(promos)
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@api.constrains('is_ready_to_calc')
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def _reset_calculated(self):
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for s in self:
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s.forecast_line_ids.write({'is_calculated': False})
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def action_validate(self):
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self.state = 'active'
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def action_cancel(self):
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self.state = 'draft'
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def fill_lines(self):
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for s in self:
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if s.forecast_line_ids:
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raise exceptions.UserError(
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'Для автоматического заполнения нужно сначала очистить все строки')
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line_obj = self.env['mklab.forecastline']
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products = self.env['product.product'].search([('is_forecast_ok', '=', True)])
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for prod in products:
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line_obj.create({
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'forecast_id': s.id,
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'product_id': prod.id,
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'price': prod.list_price,
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})
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def create_mrp(self):
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for s in self:
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lines = s.forecast_line_ids.filtered(
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lambda r: r.forecast_value > 0 and not r.mrp_order_id)
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for line in lines:
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bom = line.bom_id
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if not bom:
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raise exceptions.UserError(
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'Для продукта ' + line.product_id.name + ' не найдена ведомость материалов')
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new_order = self.env['mrp.production'].create({
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'product_id': line.product_id.id,
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'product_qty': line.forecast_value,
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'bom_id': bom.id,
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'product_uom_id': line.product_id.uom_id.id,
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'origin': s.name,
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'company_id': self.env.user.company_id.id,
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'date_start': s.start_date,
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})
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line.mrp_order_id = new_order
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class MklabForecastLine(models.Model):
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_name = 'mklab.forecastline'
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product_id = fields.Many2one(
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comodel_name='product.product',
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string='Товар',
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required=True,
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)
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forecast_value = fields.Float(string='Прогноз/план')
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order_value = fields.Float(string='В заказах факт')
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invoice_value = fields.Float(string='Отгружено факт')
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forecast_id = fields.Many2one(
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comodel_name='mklab.forecast',
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string='Прогноз',
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)
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is_calculated = fields.Boolean(string='Пересчитано автоматом')
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price = fields.Float(string='Цена')
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total_amount = fields.Float(string='Итого', compute='_compute_total_amount')
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mrp_order_id = fields.Many2one(
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comodel_name='mrp.production',
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string='Заказ на производство',
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)
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notes = fields.Text(string='Комментарий')
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bom_id = fields.Many2one(
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comodel_name='mrp.bom',
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string='Ведомость материалов',
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)
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def _compute_total_amount(self):
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for s in self:
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s.total_amount = s.price * s.forecast_value
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def calc_bom(self):
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for s in self:
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s.bom_id, s.notes = s.product_id.start_planning(s.forecast_value)
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def get_fact_values(self):
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for s in self:
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for_start = datetime.combine(s.forecast_id.start_date, datetime.min.time())
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for_end = for_start + timedelta(hours=23)
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if s.forecast_id.partner_ids:
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orders = self.env['sale.order'].search([
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('date_order', '<=', for_end),
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('date_order', '>=', for_start),
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('partner_id', 'in', s.forecast_id.partner_ids.ids),
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])
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else:
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orders = self.env['sale.order'].search([
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('date_order', '<=', for_end),
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('date_order', '>=', for_start),
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])
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ord_value = 0
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inv_value = 0
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for order in orders:
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for line in order.order_line.filtered(lambda r: r.product_id == s.product_id):
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ord_value += line.product_uom_qty
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for inv in order.invoice_ids:
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for line in inv.invoice_line_ids.filtered(lambda r: r.product_id == s.product_id):
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inv_value += line.quantity
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s.invoice_value = inv_value
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s.order_value = ord_value
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def get_forecast_values(self):
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for s in self:
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start_date_forforecast = s.forecast_id.start_date - timedelta(days=84)
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weekday = s.forecast_id.start_date.weekday()
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if s.forecast_id.partner_ids:
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orders = self.env['sale.order'].search([
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('date_order', '<', s.forecast_id.start_date),
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('date_order', '>=', start_date_forforecast),
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('dayofweek', '=', weekday),
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('partner_id', 'in', s.forecast_id.partner_ids.ids),
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])
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else:
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orders = self.env['sale.order'].search([
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('date_order', '<', s.forecast_id.start_date),
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('date_order', '>=', start_date_forforecast),
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('dayofweek', '=', weekday),
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])
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f_value = 0
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promos_forecast = self.env['mklab.marketaction'].search([
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('start_date', '<=', s.forecast_id.start_date),
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('end_date', '>=', s.forecast_id.start_date),
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])
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for order in orders:
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promos = self.env['mklab.marketaction'].search([
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('start_date', '<=', order.date_order),
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('end_date', '>=', order.date_order),
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])
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koeff = 0
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if promos:
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mark_lines = self.env['mklab.productline'].search([
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('action_id', '=', promos[0].id),
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('product_id', '=', s.product_id.id),
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])
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pids = self.env['mklab.partnerline'].search([
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('action_id', '=', promos[0].id),
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('partner_id', '=', order.partner_id.id),
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])
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if mark_lines and (pids or not promos[0].partner_line_ids):
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koeff = mark_lines[0].expected_growth
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is_promo = False
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if promos_forecast:
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mark_lines_f = self.env['mklab.productline'].search([
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('action_id', '=', promos_forecast[0].id),
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('product_id', '=', s.product_id.id),
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])
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pids_f = self.env['mklab.partnerline'].search([
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('action_id', '=', promos_forecast[0].id),
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('partner_id', '=', order.partner_id.id),
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])
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if mark_lines_f and (pids_f or not promos_forecast[0].partner_line_ids):
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is_promo = True
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order_qty = 0
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for line in order.order_line.filtered(lambda r: r.product_id == s.product_id):
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line_qty = (line.product_uom_qty * (1 + koeff / 100) * (1 + s.forecast_id.expected_growth / 100)
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if is_promo else line.product_uom_qty * (1 + koeff / 100))
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f_value += line_qty
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order_qty += line_qty
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s.forecast_value = round(f_value / 12, 0)
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@api.model
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def recalc_all(self):
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"""Cron: пересчитывает по 5 строк за раз."""
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lines = self.env['mklab.forecastline'].search(
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[('forecast_id.is_ready_to_calc', '=', True), ('is_calculated', '=', False)],
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limit=5,
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)
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for line in lines:
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line.get_forecast_values()
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line.get_fact_values()
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line.is_calculated = True
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