gawa-odoo
8bf6bee153
* = {account, sale, purchase, hr_expense}
When a plan is mandatory for SOL, POL or expenses, the flow should still be blocked when pressing the button, and not only when creating analytic lines.
We add the info in the context of the button, so automatic flows are still not blocked.
When the applicability rule requires a mandatory analytic distribution, raise an error upon :
- confirming PO,
- sending or confirming SO
- approving Expense Report by manager.
t-3040929
closes odoo/odoo#107166
X-original-commit: 8623a7850288828759db125b1054b0fed6b6b135
Signed-off-by: William André (wan) <wan@odoo.com>
71 lines
3.5 KiB
Python
71 lines
3.5 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 models, fields, api, _
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from odoo.tools.float_utils import float_round, float_compare
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from odoo.exceptions import ValidationError
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class AnalyticMixin(models.AbstractModel):
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_name = 'analytic.mixin'
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_description = 'Analytic Mixin'
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analytic_distribution = fields.Json(
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'Analytic Distribution',
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compute="_compute_analytic_distribution", store=True, copy=True, readonly=False,
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precompute=True
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)
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analytic_precision = fields.Integer(
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store=False,
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default=lambda self: self.env['decimal.precision'].precision_get("Percentage Analytic"),
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)
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def init(self):
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# Add a gin index for json search on the keys, on the models that actually have a table
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query = ''' SELECT table_name
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FROM information_schema.tables
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WHERE table_name=%s '''
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self.env.cr.execute(query, [self._table])
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if self.env.cr.dictfetchone():
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query = f"""
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CREATE INDEX IF NOT EXISTS {self._table}_analytic_distribution_gin_index
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ON {self._table} USING gin(analytic_distribution);
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"""
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self.env.cr.execute(query)
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def _compute_analytic_distribution(self):
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pass
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def write(self, vals):
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""" Format the analytic_distribution float value, so equality on analytic_distribution can be done """
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decimal_precision = self.env['decimal.precision'].precision_get('Percentage Analytic')
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vals = self._sanitize_values(vals, decimal_precision)
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return super().write(vals)
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@api.model_create_multi
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def create(self, vals_list):
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""" Format the analytic_distribution float value, so equality on analytic_distribution can be done """
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decimal_precision = self.env['decimal.precision'].precision_get('Percentage Analytic')
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vals_list = [self._sanitize_values(vals, decimal_precision) for vals in vals_list]
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return super().create(vals_list)
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def _validate_distribution(self, **kwargs):
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if self.env.context.get('validate_analytic', False):
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mandatory_plans_ids = [plan['id'] for plan in self.env['account.analytic.plan'].sudo().get_relevant_plans(**kwargs) if plan['applicability'] == 'mandatory']
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if not mandatory_plans_ids:
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return
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decimal_precision = self.env['decimal.precision'].precision_get('Percentage Analytic')
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distribution_by_root_plan = {}
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for analytic_account_id, percentage in (self.analytic_distribution or {}).items():
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root_plan = self.env['account.analytic.account'].browse(int(analytic_account_id)).root_plan_id
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distribution_by_root_plan[root_plan.id] = distribution_by_root_plan.get(root_plan.id, 0) + percentage
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for plan_id in mandatory_plans_ids:
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if float_compare(distribution_by_root_plan.get(plan_id, 0), 100, precision_digits=decimal_precision) != 0:
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raise ValidationError(_("One or more lines require a 100% analytic distribution."))
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def _sanitize_values(self, vals, decimal_precision):
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""" Normalize the float of the distribution """
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if 'analytic_distribution' in vals:
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vals['analytic_distribution'] = vals.get('analytic_distribution') and {
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account_id: float_round(distribution, decimal_precision) for account_id, distribution in vals['analytic_distribution'].items()}
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return vals
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