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# -*- 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
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