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Odoo-Modules/fusion_plating/fusion_plating/models/fp_bath_log_line.py
gsinghpal 13e300d90e changes
2026-04-28 19:39:37 -04:00

182 lines
6.5 KiB
Python

# -*- coding: utf-8 -*-
# Copyright 2026 Nexa Systems Inc.
# License OPL-1 (Odoo Proprietary License v1.0)
# Part of the Fusion Plating product family.
from odoo import api, fields, models
class FpBathLogLine(models.Model):
"""A single parameter reading on a bath log.
Each line = one titration result or one sensor reading. Target ranges
are pulled from the bath's per-bath overrides if present, otherwise
from the parameter's defaults on fusion.plating.bath.parameter.
Status is computed per line (ok / warning / out_of_spec) and rolled
up to the parent log.
"""
_name = 'fusion.plating.bath.log.line'
_description = 'Fusion Plating — Bath Log Reading'
_order = 'log_id, sequence, id'
log_id = fields.Many2one(
'fusion.plating.bath.log',
string='Log',
required=True,
ondelete='cascade',
index=True,
)
bath_id = fields.Many2one(
related='log_id.bath_id',
store=True,
readonly=True,
)
sequence = fields.Integer(
string='Sequence',
default=10,
)
parameter_id = fields.Many2one(
'fusion.plating.bath.parameter',
string='Parameter',
required=True,
ondelete='restrict',
)
parameter_code = fields.Char(
related='parameter_id.code',
store=True,
readonly=True,
)
uom = fields.Char(
related='parameter_id.uom_display',
readonly=True,
string='Unit',
)
value = fields.Float(
string='Value',
required=True,
)
target_min = fields.Float(
string='Target Min',
compute='_compute_targets',
store=True,
)
target_max = fields.Float(
string='Target Max',
compute='_compute_targets',
store=True,
)
status = fields.Selection(
[
('ok', 'OK'),
('warning', 'Warning'),
('out_of_spec', 'Out of Spec'),
],
string='Status',
compute='_compute_status',
store=True,
)
notes = fields.Char(
string='Notes',
)
# ==========================================================================
@api.onchange('parameter_id')
def _onchange_parameter_prefill_value(self):
"""Pre-fill `value` from the tank's setpoint when the parameter is a
temperature reading.
This means the operator (or backend user) hits "add reading", picks
Temperature, and the tank's `default_temperature` lands in the value
column automatically — they confirm with one tap or nudge with
keyboard arrows. Avoids retyping the same number every shift.
Fires only when value is currently empty so the user's edits aren't
clobbered if they go back and pick a different parameter.
"""
for rec in self:
if not rec.parameter_id or rec.value:
continue
if rec.parameter_id.parameter_type != 'temperature':
continue
tank = rec.log_id.bath_id.tank_id
if tank and tank.default_temperature:
rec.value = tank.default_temperature
@api.depends('parameter_id', 'log_id.bath_id')
def _compute_targets(self):
"""Resolve target range: per-bath override first, parameter default second."""
for rec in self:
tmin = tmax = 0.0
if rec.log_id.bath_id and rec.parameter_id:
override = rec.log_id.bath_id.target_line_ids.filtered(
lambda t: t.parameter_id.id == rec.parameter_id.id
)[:1]
if override:
tmin, tmax = override.target_min, override.target_max
else:
tmin = rec.parameter_id.target_min
tmax = rec.parameter_id.target_max
rec.target_min = tmin
rec.target_max = tmax
@api.depends('value', 'target_min', 'target_max', 'parameter_id.warning_tolerance')
def _compute_status(self):
for rec in self:
if rec.target_min == 0.0 and rec.target_max == 0.0:
rec.status = 'ok'
continue
v, lo, hi = rec.value, rec.target_min, rec.target_max
if v < lo or v > hi:
rec.status = 'out_of_spec'
continue
tol_pct = (rec.parameter_id.warning_tolerance or 0.0) / 100.0
span = max(hi - lo, 1e-9)
if tol_pct > 0 and (v - lo < span * tol_pct or hi - v < span * tol_pct):
rec.status = 'warning'
else:
rec.status = 'ok'
# ------------------------------------------------------------------
# T1.2 — Auto-suggest replenishment on every log line
# ------------------------------------------------------------------
@api.model_create_multi
def create(self, vals_list):
lines = super().create(vals_list)
lines._spawn_replenishment_suggestions()
return lines
def _spawn_replenishment_suggestions(self):
"""For every out-of-spec reading, run the matching replenishment
rule and create a pending suggestion the operator can apply."""
Rule = self.env['fusion.plating.bath.replenishment.rule']
Suggestion = self.env['fusion.plating.bath.replenishment.suggestion']
for line in self:
if not line.parameter_id or not line.log_id.bath_id:
continue
bath = line.log_id.bath_id
rules = Rule._find_rules(bath, line.parameter_id.id)
for rule in rules:
dose = rule._compute_dose(
line.value, line.target_min, line.target_max, bath.volume,
)
if dose <= 0:
continue
Suggestion.create({
'bath_id': bath.id,
'log_line_id': line.id,
'rule_id': rule.id,
'parameter_id': line.parameter_id.id,
'current_value': line.value,
'target_min': line.target_min,
'target_max': line.target_max,
'product_name': rule.product_name,
'dose_amount': dose,
'dose_uom': rule.dose_uom,
'state': 'pending',
})
bath.message_post(
body=f'Replenishment suggested: add {dose} {rule.dose_uom} '
f'of {rule.product_name} ({line.parameter_id.name} '
f'reading: {line.value})',
)