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# -*- coding: utf-8 -*-
from odoo import http, _
from odoo.http import request
from datetime import datetime, timedelta
import babel
from odoo.addons.website.controllers.backend import WebsiteBackend
from odoo.tools import DEFAULT_SERVER_DATE_FORMAT
class WebsiteSaleBackend(WebsiteBackend):
@http.route()
def fetch_dashboard_data(self, date_from, date_to):
results = super(WebsiteSaleBackend, self).fetch_dashboard_data(date_from, date_to)
results['groups']['sale_salesman'] = request.env['res.users'].has_group('sales_team.group_sale_salesman')
if not results['groups']['sale_salesman']:
return results
date_from = datetime.strptime(date_from, DEFAULT_SERVER_DATE_FORMAT)
date_to = datetime.strptime(date_to, DEFAULT_SERVER_DATE_FORMAT)
# Best seller products
product_lines = request.env['sale.order.line'].read_group(
domain=[
('product_id.website_published', '=', True),
('order_id.state', 'in', ['sent', 'sale', 'done']),
('order_id.team_id.website_ids', '!=', False),
('order_id.date_order', '>=', date_from.strftime(DEFAULT_SERVER_DATE_FORMAT)),
('order_id.date_order', '<=', date_to.strftime(DEFAULT_SERVER_DATE_FORMAT))],
fields=['product_id', 'product_uom_qty', 'price_total'],
groupby='product_id', orderby='product_uom_qty desc', limit=5)
best_sellers = []
for product_line in product_lines:
product_id = request.env['product.product'].browse(product_line['product_id'][0])
best_sellers.append({
'id': product_id.id,
'name': product_id.name,
'qty': product_line['product_uom_qty'],
'sales': product_line['price_total'],
})
# Graphes computation
sales_domain = [
('team_id.website_ids', '!=', False),
('state', 'in', ['sent', 'sale', 'done']),
]
sales_graph = self._compute_sale_graph(date_from, date_to, sales_domain)
previous_sales_graph = self._compute_sale_graph(date_from - timedelta(days=(date_to - date_from).days), date_from, sales_domain, previous=True)
results['dashboards']['sales'] = {
'graph': [
{
'values': sales_graph,
'key': _('Sales'),
},
{
'values': previous_sales_graph,
'key': _('Previous Sales'),
},
],
'best_sellers': best_sellers,
}
return results
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.order'].read_group(
domain=sales_domain + [
('date_order', '>=', date_from.strftime(DEFAULT_SERVER_DATE_FORMAT)),
('date_order', '<=', date_to.strftime(DEFAULT_SERVER_DATE_FORMAT))],
fields=['date_order', 'amount_total'],
groupby='date_order:day')
daily_sales_dict = {p['date_order:day']: p['amount_total'] for p in daily_sales}
sales_graph = [{
'0': d.strftime(DEFAULT_SERVER_DATE_FORMAT) if not previous else (d + timedelta(days=days_between)).strftime(DEFAULT_SERVER_DATE_FORMAT),
# Respect read_group format in models.py
'1': daily_sales_dict.get(babel.dates.format_date(d, format='dd MMM yyyy', locale=request.env.context.get('lang') or 'en_US'), 0)
} for d in date_list]
return sales_graph