Odoo 19 Wave Picking:
Optimize Warehouse Throughput

from odoo import api, fields, models
from datetime import timedelta


class StockWaveScheduler(models.Model):
    _name = "stock.wave.scheduler"
    _description = "Automated Wave Release Scheduler"

    name = fields.Char(required=True)
    carrier_id = fields.Many2one("delivery.carrier")
    warehouse_id = fields.Many2one("stock.warehouse", required=True)
    cutoff_hour = fields.Float(
        string="Shipping Cutoff (24h)",
        help="Hour of day for carrier pickup. "
             "Waves release 3 hours before cutoff.",
    )
    max_picks_per_wave = fields.Integer(default=200)

    def _cron_release_waves(self):
        """Called by ir.cron every 30 minutes."""
        now = fields.Datetime.now()
        for scheduler in self.search([]):
            # Check if we're within the release window
            cutoff = now.replace(
                hour=int(scheduler.cutoff_hour),
                minute=int((scheduler.cutoff_hour % 1) * 60),
            )
            release_time = cutoff - timedelta(hours=3)
            if not (release_time <= now <= cutoff):
                continue

            # Find unassigned ready transfers
            domain = [
                ('picking_type_id.warehouse_id', '=',
                 scheduler.warehouse_id.id),
                ('picking_type_id.code', '=', 'outgoing'),
                ('state', '=', 'assigned'),
                ('batch_id', '=', False),
            ]
            if scheduler.carrier_id:
                domain.append(
                    ('carrier_id', '=', scheduler.carrier_id.id)
                )

            picks = self.env['stock.picking'].search(
                domain,
                limit=scheduler.max_picks_per_wave,
                order='priority desc, scheduled_date asc',
            )
            if not picks:
                continue

            wave = self.env['stock.picking.batch'].create({
                'is_wave': True,
                'picking_ids': [(6, 0, picks.ids)],
            })
            wave.action_confirm()

def get_wave_progress(self, wave_id):
    """Return wave completion metrics for dashboard."""
    wave = self.env['stock.picking.batch'].browse(wave_id)
    picks = wave.picking_ids

    total = len(picks)
    done = len(picks.filtered(lambda p: p.state == 'done'))
    in_progress = len(picks.filtered(
        lambda p: p.state == 'assigned'
    ))
    waiting = len(picks.filtered(
        lambda p: p.state in ('waiting', 'confirmed')
    ))

    return {
        'wave_name': wave.name,
        'total_transfers': total,
        'completed': done,
        'in_progress': in_progress,
        'waiting': waiting,
        'completion_pct': round((done / total) * 100, 1)
            if total else 0,
        'estimated_finish': self._estimate_finish_time(
            wave, done, total
        ),
    }

def _estimate_finish_time(self, wave, done, total):
    """Estimate wave completion based on current velocity."""
    if done == 0:
        return None
    elapsed = fields.Datetime.now() - wave.create_date
    rate = done / elapsed.total_seconds()  # picks per second
    remaining = total - done
    seconds_left = remaining / rate if rate > 0 else 0
    return fields.Datetime.now() + timedelta(
        seconds=seconds_left
    )