Julien Castiaux
4f03a5f136
PEP-594 is deprecating a bunch of modules. As part of the cleanup, we are also dealing with long deprecated modules, functions and aliases. * `assert_` -> `assertTrue` * `assertEquals` -> `assertEqual` * `assertNotEquals` -> `assertNotEqual` * `assertAlmostEquals` -> `assertAlmostEqual` * `assertRaisesRegexp` -> `assertRaisesRegex` * `assertRegexpMatches` -> `assertRegex` * `base64.encodestring` -> `base64.encodebytes` * `base64.decodestring` -> `base64.decodebytes` * `inspect.getargspec` -> `inspect.signature` * `inspect.formatargspec` -> `inspect.signature` * `logging.warn` -> `logging.warning` closes odoo/odoo#36863 Task: 2003936 Signed-off-by: Raphael Collet (rco) <rco@openerp.com>
83 lines
4.1 KiB
Python
83 lines
4.1 KiB
Python
# -*- coding: utf-8 -*-
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# Part of Odoo. See LICENSE file for full copyright and licensing details.
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from odoo.tests.common import TransactionCase
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from odoo import tools
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class TestCRMPLS(TransactionCase):
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def _get_lead_values(self, team_id, name_suffix, country_id, state_id, email_state, phone_state, source_id, stage_id):
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return {
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'name': 'lead_' + name_suffix,
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'type': 'opportunity',
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'state_id': state_id,
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'email_state': email_state,
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'phone_state': phone_state,
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'source_id': source_id,
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'stage_id': stage_id,
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'country_id': country_id,
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'team_id': team_id
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}
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def test_predictive_lead_scoring(self):
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""" We test here computation of lead probability based on PLS Bayes.
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We will use 3 different values for each possible variables:
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country_id : 1,2,3
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state_id: 1,2,3
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email_state: correct, incorrect, None
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phone_state: correct, incorrect, None
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source_id: 1,2,3
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stage_id: 1,2,3 + the won stage
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And we will compute all of this for 2 different team_id
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Note : We assume here that original bayes computation is correct
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as we don't compute manually the probabilities."""
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Lead = self.env['crm.lead']
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state_values = ['correct', 'incorrect', None]
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source_ids = self.env['utm.source'].search([], limit=3).ids
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state_ids = self.env['res.country.state'].search([], limit=3).ids
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country_ids = self.env['res.country'].search([], limit=3).ids
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stage_ids = self.env['crm.stage'].search([], limit=3).ids
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team_ids = self.env['crm.team'].create([{'name': 'Team Test 1'}, {'name': 'Team Test 2'}]).ids
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# create bunch of lost and won crm_lead
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leads_to_create = []
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# for team 1
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for i in range(3):
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leads_to_create.append(self._get_lead_values(team_ids[0], 'team_1_%s' % str(i), country_ids[i], state_ids[i], state_values[i], state_values[i], source_ids[i], stage_ids[i]))
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leads_to_create.append(
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self._get_lead_values(team_ids[0], 'team_1_%s' % str(3), country_ids[0], state_ids[1], state_values[2], state_values[0], source_ids[2], stage_ids[1]))
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# for team 2
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leads_to_create.append(
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self._get_lead_values(team_ids[1], 'team_2_%s' % str(0), country_ids[0], state_ids[1], state_values[2], state_values[0], source_ids[1], stage_ids[2]))
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leads_to_create.append(
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self._get_lead_values(team_ids[1], 'team_2_%s' % str(1), country_ids[0], state_ids[1], state_values[0], state_values[1], source_ids[2], stage_ids[1]))
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leads_to_create.append(
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self._get_lead_values(team_ids[1], 'team_2_%s' % str(2), country_ids[0], state_ids[2], state_values[0], state_values[1], source_ids[2], stage_ids[0]))
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leads_to_create.append(
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self._get_lead_values(team_ids[1], 'team_2_%s' % str(3), country_ids[0], state_ids[1], state_values[2], state_values[0], source_ids[2], stage_ids[1]))
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leads = Lead.create(leads_to_create)
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# Set the PLS config
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self.env['ir.config_parameter'].sudo().set_param("crm.pls_start_date", "2000-01-01")
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self.env['ir.config_parameter'].sudo().set_param("crm.pls_fields", "country_id,state_id,email_state,phone_state,source_id")
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# set leads as won and lost
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# for Team 1
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leads[0].action_set_lost()
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leads[1].action_set_lost()
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leads[2].action_set_won()
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# for Team 2
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leads[4].action_set_lost()
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leads[5].action_set_lost()
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leads[6].action_set_won()
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# rebuild frequencies table and recompute automated_probability for all leads.
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Lead._cron_update_automated_probabilities()
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# As the cron is computing and writing in SQL queries, we need to invalidate the cache
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leads.invalidate_cache()
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self.assertEqual(tools.float_compare(leads[3].automated_probability, 33.49, 2), 0)
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self.assertEqual(tools.float_compare(leads[7].automated_probability, 7.74, 2), 0)
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