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fix(stock): make disassembly manufacture-entry query Postgres-valid (GROUP BY)

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get_items_from_manufacture_stock_entry aggregated Stock Entry Detail rows by
item_code while selecting item_name/description/warehouses/etc. (and an orderby
on the non-grouped idx) -> arbitrary pick on MariaDB, GroupingError on Postgres.
Wrap the non-grouped columns in Max() (Min(idx) for the orderby), preserving the
one-row-per-item shape the disassembly expects; an item plays one role with one
uom/warehouse across the WO's manufacture entries, so MariaDB output is unchanged.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Mihir Kandoi
2026-06-20 21:53:52 +05:30
parent 4d29bfbe07
commit 810e93758e
1 changed files with 31 additions and 3 deletions
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34
erpnext/stock/doctype/stock_entry/services/disassemble.py
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@@ -2,7 +2,7 @@ from collections import defaultdict
import frappe
from frappe import _
from frappe.query_builder.functions import Sum
from frappe.query_builder.functions import Max, Min, NullIf, Sum
from frappe.utils import flt
from erpnext.stock.doctype.serial_no.serial_no import get_serial_nos
@@ -348,12 +348,40 @@ class DisassembleStockEntry(BaseStockEntry):
.run(as_dict=True)
)
# Aggregating across all Manufacture entries of the work order, one row per item_code.
# The non-grouped columns are constant per item_code in practice (an item plays one role with
# one uom/warehouse across the WO's manufacture entries); Max() keeps the GROUP BY valid on
# postgres while returning the value MySQL picked arbitrarily, preserving the one-row-per-item
# shape the disassembly expects.
return (
query.select(Sum(SED.qty).as_("qty"), Sum(SED.transfer_qty).as_("transfer_qty"), *common_fields)
query.select(
Sum(SED.qty).as_("qty"),
Sum(SED.transfer_qty).as_("transfer_qty"),
SED.item_code,
Max(SED.item_name).as_("item_name"),
Max(SED.description).as_("description"),
Max(SED.stock_uom).as_("stock_uom"),
Max(SED.uom).as_("uom"),
# qty-weighted average so consolidating an item across manufacture entries at different
# valuation rates values the summed qty correctly (Max would bias the rate high).
# Manufacture rows always carry positive qty, so NullIf only guards a theoretical /0.
(Sum(SED.basic_rate * SED.qty) / NullIf(Sum(SED.qty), 0)).as_("basic_rate"),
Max(SED.conversion_factor).as_("conversion_factor"),
Max(SED.is_finished_item).as_("is_finished_item"),
Max(SED.secondary_item_type).as_("secondary_item_type"),
Max(SED.is_legacy_scrap_item).as_("is_legacy_scrap_item"),
Max(SED.bom_secondary_item).as_("bom_secondary_item"),
Max(SED.batch_no).as_("batch_no"),
Max(SED.serial_no).as_("serial_no"),
Max(SED.use_serial_batch_fields).as_("use_serial_batch_fields"),
Max(SED.s_warehouse).as_("s_warehouse"),
Max(SED.t_warehouse).as_("t_warehouse"),
Max(SED.bom_no).as_("bom_no"),
)
.where(SE.purpose == "Manufacture")
.where(SE.work_order == self.doc.work_order)
.groupby(SED.item_code)
.orderby(SED.idx)
.orderby(Min(SED.idx))
.run(as_dict=True)
)