fix bugs and add normalization feataure

models/stock_inventory_backdate.py

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