# -*- coding: utf-8 -*- import babel.dates from datetime import datetime, timedelta, time from odoo import fields, http, _ from odoo.addons.website.controllers.backend import WebsiteBackend from odoo.http import request from odoo.tools.misc import get_lang class WebsiteSaleBackend(WebsiteBackend): @http.route() def fetch_dashboard_data(self, website_id, date_from, date_to): Website = request.env['website'] current_website = website_id and Website.browse(website_id) or Website.get_current_website() results = super(WebsiteSaleBackend, self).fetch_dashboard_data(website_id, date_from, date_to) date_date_from = fields.Date.from_string(date_from) date_date_to = fields.Date.from_string(date_to) date_diff_days = (date_date_to - date_date_from).days datetime_from = datetime.combine(date_date_from, time.min) datetime_to = datetime.combine(date_date_to, time.max) sales_values = dict( graph=[], best_sellers=[], summary=dict( order_count=0, order_carts_count=0, order_unpaid_count=0, order_to_invoice_count=0, order_carts_abandoned_count=0, payment_to_capture_count=0, total_sold=0, order_per_day_ratio=0, order_sold_ratio=0, order_convertion_pctg=0, ) ) results['dashboards']['sales'] = sales_values results['groups']['sale_salesman'] = request.env['res.users'].has_group('sales_team.group_sale_salesman') if not results['groups']['sale_salesman']: return results results['dashboards']['sales']['utm_graph'] = self.fetch_utm_data(datetime_from, datetime_to) # Product-based computation sale_report_domain = [ ('website_id', '=', current_website.id), ('state', 'in', ['sale', 'done']), ('date', '>=', datetime_from), ('date', '<=', fields.Datetime.now()) ] report_product_lines = request.env['sale.report'].read_group( domain=sale_report_domain, fields=['product_tmpl_id', 'product_uom_qty', 'price_subtotal'], groupby='product_tmpl_id', orderby='product_uom_qty desc', limit=5) for product_line in report_product_lines: product_tmpl_id = request.env['product.template'].browse(product_line['product_tmpl_id'][0]) sales_values['best_sellers'].append({ 'id': product_tmpl_id.id, 'name': product_tmpl_id.name, 'qty': product_line['product_uom_qty'], 'sales': product_line['price_subtotal'], }) # Sale-based results computation sale_order_domain = [ ('website_id', '=', current_website.id), ('date_order', '>=', fields.Datetime.to_string(datetime_from)), ('date_order', '<=', fields.Datetime.to_string(datetime_to))] so_group_data = request.env['sale.order'].read_group(sale_order_domain, fields=['state'], groupby='state') for res in so_group_data: if res.get('state') == 'sent': sales_values['summary']['order_unpaid_count'] += res['state_count'] elif res.get('state') in ['sale', 'done']: sales_values['summary']['order_count'] += res['state_count'] sales_values['summary']['order_carts_count'] += res['state_count'] report_price_lines = request.env['sale.report'].read_group( domain=[ ('website_id', '=', current_website.id), ('state', 'in', ['sale', 'done']), ('date', '>=', datetime_from), ('date', '<=', datetime_to)], fields=['team_id', 'price_subtotal'], groupby=['team_id'], ) sales_values['summary'].update( order_to_invoice_count=request.env['sale.order'].search_count(sale_order_domain + [ ('state', 'in', ['sale', 'done']), ('order_line', '!=', False), ('partner_id', '!=', request.env.ref('base.public_partner').id), ('invoice_status', '=', 'to invoice'), ]), order_carts_abandoned_count=request.env['sale.order'].search_count(sale_order_domain + [ ('is_abandoned_cart', '=', True), ('cart_recovery_email_sent', '=', False) ]), payment_to_capture_count=request.env['payment.transaction'].search_count([ ('state', '=', 'authorized'), # that part perform a search on sale.order in order to comply with access rights as tx do not have any ('sale_order_ids', 'in', request.env['sale.order'].search(sale_order_domain + [('state', '!=', 'cancel')]).ids), ]), total_sold=sum(price_line['price_subtotal'] for price_line in report_price_lines) ) # Ratio computation sales_values['summary']['order_per_day_ratio'] = round(float(sales_values['summary']['order_count']) / date_diff_days, 2) sales_values['summary']['order_sold_ratio'] = round(float(sales_values['summary']['total_sold']) / sales_values['summary']['order_count'], 2) if sales_values['summary']['order_count'] else 0 sales_values['summary']['order_convertion_pctg'] = 100.0 * sales_values['summary']['order_count'] / sales_values['summary']['order_carts_count'] if sales_values['summary']['order_carts_count'] else 0 # Graphes computation if date_diff_days == 7: previous_sale_label = _('Previous Week') elif date_diff_days > 7 and date_diff_days <= 31: previous_sale_label = _('Previous Month') else: previous_sale_label = _('Previous Year') sales_values['graph'] += [{ 'values': self._compute_sale_graph(date_date_from, date_date_to, sale_report_domain), 'key': 'Untaxed Total', }, { 'values': self._compute_sale_graph(date_date_from - timedelta(days=date_diff_days), date_date_from, sale_report_domain, previous=True), 'key': previous_sale_label, }] return results def fetch_utm_data(self, date_from, date_to): sale_utm_domain = [ ('website_id', '!=', False), ('state', 'in', ['sale', 'done']), ('date_order', '>=', date_from), ('date_order', '<=', date_to) ] orders_data_groupby_campaign_id = request.env['sale.order']._read_group( domain=sale_utm_domain + [('campaign_id', '!=', False)], fields=['amount_total', 'id', 'campaign_id'], groupby='campaign_id') orders_data_groupby_medium_id = request.env['sale.order']._read_group( domain=sale_utm_domain + [('medium_id', '!=', False)], fields=['amount_total', 'id', 'medium_id'], groupby='medium_id') orders_data_groupby_source_id = request.env['sale.order']._read_group( domain=sale_utm_domain + [('source_id', '!=', False)], fields=['amount_total', 'id', 'source_id'], groupby='source_id') return { 'campaign_id': self.compute_utm_graph_data('campaign_id', orders_data_groupby_campaign_id), 'medium_id': self.compute_utm_graph_data('medium_id', orders_data_groupby_medium_id), 'source_id': self.compute_utm_graph_data('source_id', orders_data_groupby_source_id), } def compute_utm_graph_data(self, utm_type, utm_graph_data): return [{ 'utm_type': data[utm_type][1], 'amount_total': data['amount_total'] } for data in utm_graph_data] def _compute_sale_graph(self, date_from, date_to, sales_domain, previous=False): days_between = (date_to - date_from).days date_list = [(date_from + timedelta(days=x)) for x in range(0, days_between + 1)] daily_sales = request.env['sale.report'].read_group( domain=sales_domain, fields=['date', 'price_subtotal'], groupby='date:day') daily_sales_dict = {p['date:day']: p['price_subtotal'] for p in daily_sales} sales_graph = [{ '0': fields.Date.to_string(d) if not previous else fields.Date.to_string(d + timedelta(days=days_between)), # Respect read_group format in models.py '1': daily_sales_dict.get(babel.dates.format_date(d, format='dd MMM yyyy', locale=get_lang(request.env).code), 0) } for d in date_list] return sales_graph