gawa-odoo
4d7a9eea13
If an aml has no product, it should not trigger a model that has a product. So, we now define the fields that have to be checked on the model, instead of just being the ones given as parameters. The way the field `company_id` impacts the model has also been changed. The idea is that a model with a company specified should be better than a model without one. But we also want that a model with 1 valid rule and no company is better than one with only a good selected company. closes odoo/odoo#107165 X-original-commit: feff1a8a056f1fbbc852f7cf164e73abf83c4cc9 Signed-off-by: William André (wan) <wan@odoo.com>
105 lines
4.2 KiB
Python
105 lines
4.2 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 import api, fields, models, _
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from odoo.exceptions import UserError
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class NonMatchingDistribution(Exception):
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pass
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class AccountAnalyticDistributionModel(models.Model):
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_name = 'account.analytic.distribution.model'
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_inherit = 'analytic.mixin'
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_description = 'Analytic Distribution Model'
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_rec_name = 'create_date'
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_order = 'id desc'
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partner_id = fields.Many2one(
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'res.partner',
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string='Partner',
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ondelete='cascade',
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help="Select a partner for which the analytic distribution will be used (e.g. create new customer invoice or Sales order if we select this partner, it will automatically take this as an analytic account)",
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)
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partner_category_id = fields.Many2one(
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'res.partner.category',
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string='Partner Category',
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ondelete='cascade',
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help="Select a partner category for which the analytic distribution will be used (e.g. create new customer invoice or Sales order if we select this partner, it will automatically take this as an analytic account)",
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)
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company_id = fields.Many2one(
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'res.company',
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string='Company',
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default=lambda self: self.env.company,
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ondelete='cascade',
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help="Select a company for which the analytic distribution will be used (e.g. create new customer invoice or Sales order if we select this company, it will automatically take this as an analytic account)",
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)
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@api.constrains('company_id')
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def _check_company_accounts(self):
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query = """
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SELECT model.id
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FROM account_analytic_distribution_model model
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JOIN account_analytic_account account
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ON model.analytic_distribution ? CAST(account.id AS VARCHAR)
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WHERE account.company_id IS NOT NULL
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AND (model.company_id IS NULL
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OR model.company_id != account.company_id)
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"""
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self.flush_model(['company_id', 'analytic_distribution'])
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self.env.cr.execute(query)
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if self.env.cr.dictfetchone():
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raise UserError(_('You defined a distribution with analytic account(s) belonging to a specific company but a model shared between companies or with a different company'))
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@api.model
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def _get_distribution(self, vals):
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""" Returns the distribution model that has the most fields that corresponds to the vals given
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This method should be called to prefill analytic distribution field on several models """
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domain = []
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for fname, value in vals.items():
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domain += self._create_domain(fname, value) or []
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best_score = 0
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res = {}
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fnames = set(self._get_fields_to_check())
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for rec in self.search(domain):
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try:
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score = sum(rec._check_score(key, vals.get(key)) for key in fnames)
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if score > best_score:
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res = rec.analytic_distribution
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best_score = score
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except NonMatchingDistribution:
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continue
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return res
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def _get_fields_to_check(self):
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return (
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set(self.env['account.analytic.distribution.model']._fields)
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- set(self.env['analytic.mixin']._fields)
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- set(models.MAGIC_COLUMNS) - {'display_name', '__last_update'}
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)
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def _check_score(self, key, value):
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self.ensure_one()
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if key == 'company_id':
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if not self.company_id or value == self.company_id.id:
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return 1 if self.company_id else 0.5
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raise NonMatchingDistribution
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if not self[key]:
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return 0
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if value and ((self[key].id in value) if isinstance(value, (list, tuple))
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else (value.startswith(self[key])) if key.endswith('_prefix')
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else (value == self[key].id)
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):
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return 1
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raise NonMatchingDistribution
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def _create_domain(self, fname, value):
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if not value:
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return False
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if fname == 'partner_category_id':
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value += [False]
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return [(fname, 'in', value)]
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else:
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return [(fname, 'in', [value, False])]
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