fix bugs and add normalization feataure
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@ -1,5 +1,6 @@
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from odoo import api, fields, models, _
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from odoo.exceptions import UserError, ValidationError
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from odoo.tools import float_is_zero, float_compare
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import logging
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_logger = logging.getLogger(__name__)
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@ -548,5 +549,170 @@ class StockInventoryBackdateLine(models.Model):
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# Invalidate cache
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self.env.cache.invalidate()
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# Ghost Value Fix: Propagate consumption to subsequent sales
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# Note: We pass the backdate because move.date might still be cached as 'now' until full reload
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self._propagate_consumption(move, backdate)
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return move
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def _propagate_consumption(self, move, backdate_datetime):
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"""
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Ghost Value Fix:
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Simulate 'FIFO' consumption for the newly backdated layer against subsequent outgoing moves.
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If we retroactively add stock to Jan 1, but we sold stock on Jan 2,
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that sale should have consumed this (cheaper/older) stock depending on FIFO/AVCO.
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This logic creates 'Correction SVLs' to expense the value of the backdated layer
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that corresponds to quantities subsequently sold.
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"""
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if move.product_id.categ_id.property_cost_method not in ['average', 'fifo']:
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return
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# 1. Identify the new Layer
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new_svl = self.env['stock.valuation.layer'].search([
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('stock_move_id', '=', move.id)
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], limit=1)
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if not new_svl:
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return
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# Check if we have quantity to propagate
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# We generally only propagate INCOMING adjustments (Positive Qty) that have remaining qty
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# But for robustness (and user request), we ensure float comparison
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if float_compare(new_svl.quantity, 0, precision_rounding=move.product_uom.rounding) <= 0:
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return
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if float_compare(new_svl.remaining_qty, 0, precision_rounding=move.product_uom.rounding) <= 0:
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return
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# 2. Find Subsequent Outgoing Moves (The "Missed" Sales)
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# We look for outgoing SVLs (qty < 0) created AFTER the backdate
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outgoing_svls = self.env['stock.valuation.layer'].search([
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('product_id', '=', move.product_id.id),
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('company_id', '=', move.company_id.id),
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('quantity', '<', 0), # Outgoing
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('create_date', '>', backdate_datetime),
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], order='create_date asc, id asc')
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if not outgoing_svls:
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return
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# 3. Consumption Loop
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qty_to_consume_total = 0.0
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for out_layer in outgoing_svls:
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if new_svl.remaining_qty <= 0:
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break
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# How much can this sale consume from our new layer?
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# It can consume whole sale qty, limited by what we have in the new layer.
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sale_qty = abs(out_layer.quantity)
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# Logic: In strict FIFO, this sale `out_layer` MIGHT have already consumed
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# some OLDER layer if it wasn't empty.
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# But the whole point of "Ghost Value" is that we assume the user wanted this Backdated Stock
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# to be available "Back Then".
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# So effectively, we are injecting this layer into the past.
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# Ideally, we should re-run the WHOLE fifo queue. That's too risky/complex.
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# Approximate Logic: "Any subsequent sale is a candidate to consume this 'unexpected' old stock".
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consume_qty = min(new_svl.remaining_qty, sale_qty)
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if consume_qty <= 0:
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continue
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# Calculate Value to Expense
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# We expense based on OUR layer's unit cost (since we are consuming OUR layer)
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unit_val = new_svl.value / new_svl.quantity if new_svl.quantity else 0
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expense_value = consume_qty * unit_val
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# Rounding
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expense_value = move.company_id.currency_id.round(expense_value)
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if float_is_zero(expense_value, precision_rounding=move.company_id.currency_id.rounding):
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continue
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# --- ACTION: REDUCE OUR LAYER ---
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# We update SQL directly to avoid ORM side effects / recomputes
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# Reduce remaining_qty and remaining_value
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# Note: We need to fetch latest state of new_svl inside loop if we modify it?
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# Yes, new_svl.remaining_qty is simple float in memory, we update it manually here to track loop.
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new_svl.remaining_qty -= consume_qty
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new_svl.remaining_value -= expense_value
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# Commit this reduction to DB immediately so it sticks
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self.env.cr.execute(
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"UPDATE stock_valuation_layer SET remaining_qty = remaining_qty - %s, remaining_value = remaining_value - %s WHERE id = %s",
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(consume_qty, expense_value, new_svl.id)
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)
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# --- ACTION: CREATE Expense Entry (Correction) ---
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# Credit Asset (we just reduced remaining_value, effectively saying "It's gone")
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# Debit COGS (Expense it)
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stock_val_acc = move.product_id.categ_id.property_stock_valuation_account_id.id
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cogs_acc = move.product_id.categ_id.property_stock_account_output_categ_id.id
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if not stock_val_acc or not cogs_acc:
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continue
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move_lines = [
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(0, 0, {
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'name': _('Backdate Correction for %s') % out_layer.stock_move_id.name,
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'account_id': cogs_acc,
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'debit': expense_value,
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'credit': 0,
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'product_id': move.product_id.id,
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}),
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(0, 0, {
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'name': _('Backdate Correction for %s') % out_layer.stock_move_id.name,
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'account_id': stock_val_acc,
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'debit': 0,
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'credit': expense_value,
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'product_id': move.product_id.id,
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}),
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]
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am_vals = {
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'ref': f"{move.name} - Consumed by {out_layer.stock_move_id.name}",
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'date': out_layer.create_date.date(), # Match the SALE date
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'journal_id': move.account_move_ids[0].journal_id.id if move.account_move_ids else False,
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# Use same journal as original move adjustment? Or Stock Journal?
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# Generally Stock Journal.
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'line_ids': move_lines,
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'move_type': 'entry',
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'company_id': move.company_id.id,
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}
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# Fallback journal if not found
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if not am_vals['journal_id']:
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am_vals['journal_id'] = move.product_id.categ_id.property_stock_journal.id
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am = self.env['account.move'].create(am_vals)
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am.action_post()
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# Create Correction SVL
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# Value is negative (Reducing Asset)
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self.env['stock.valuation.layer'].create({
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'product_id': move.product_id.id,
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'value': -expense_value,
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'quantity': 0,
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'unit_cost': 0,
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'remaining_qty': 0,
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'stock_move_id': out_layer.stock_move_id.id, # Link to sale move
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'company_id': move.company_id.id,
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'description': _('Backdate Correction (from %s)') % move.name,
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'account_move_id': am.id,
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})
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# Backdate this correction SVL to match sale date
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# We don't have the ID easily here as create returns record but separate from SQL.
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# But standard create sets create_date=Now.
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# We want it to look like it happened AT SALE TIME.
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# We can find it via account_move_id
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self.env.cr.execute(
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"UPDATE stock_valuation_layer SET create_date = %s WHERE account_move_id = %s",
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(out_layer.create_date, am.id)
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)
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_logger.info(f"Propagated consumption: Consumed {consume_qty} from Backdate Layer for Sale {out_layer.stock_move_id.name}")
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