test: add coverage for Itemwise Recommended Reorder Level report

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

erpnext/stock/report/itemwise_recommended_reorder_level/test_itemwise_recommended_reorder_level.py

@@ -0,0 +1,66 @@
+# Copyright (c) 2026, Frappe Technologies Pvt. Ltd. and Contributors
+# See license.txt
+
+import frappe
+from frappe.utils import flt
+
+from erpnext.stock.doctype.item.test_item import make_item
+from erpnext.stock.doctype.stock_entry.stock_entry_utils import make_stock_entry
+from erpnext.stock.report.itemwise_recommended_reorder_level.itemwise_recommended_reorder_level import (
+	execute,
+)
+from erpnext.tests.utils import ERPNextTestSuite
+
+WAREHOUSE = "_Test Warehouse - _TC"
+
+
+class TestItemwiseRecommendedReorderLevel(ERPNextTestSuite):
+	def run_report(self, **extra):
+		filters = frappe._dict({"from_date": "2026-06-01", "to_date": "2026-06-10"})
+		filters.update(extra)
+		return execute(filters)[1]
+
+	def find_row(self, data, item_code):
+		for row in data:
+			if row[0] == item_code:
+				return row
+		return None
+
+	def test_consumption_drives_recommendation(self):
+		item = make_item(properties={"is_stock_item": 1, "lead_time_days": 3, "safety_stock": 5}).name
+
+		# Receive stock, then issue a known total across dates inside the report window.
+		make_stock_entry(item_code=item, to_warehouse=WAREHOUSE, qty=100, rate=10, posting_date="2026-06-01")
+		make_stock_entry(item_code=item, from_warehouse=WAREHOUSE, qty=20, posting_date="2026-06-03")
+		make_stock_entry(item_code=item, from_warehouse=WAREHOUSE, qty=30, posting_date="2026-06-07")
+
+		data = self.run_report(item_group="All Item Groups")
+		row = self.find_row(data, item)
+		self.assertIsNotNone(row, msg=f"Item {item} not found in report")
+
+		float_precision = frappe.db.get_default("float_precision")
+		# Window 2026-06-01..2026-06-10 inclusive => diff = 10 days.
+		diff = 10
+		total_outgoing = 50.0  # 20 + 30 issued
+		expected_avg = flt(total_outgoing / diff, float_precision)  # 5.0
+		expected_reorder = (expected_avg * 3) + 5  # avg * lead_time_days + safety_stock = 20
+
+		# Row shape: [item, item_name, item_group, brand, description,
+		#   safety_stock, lead_time_days, consumed, delivered, total_outgoing,
+		#   avg_daily_outgoing, reorder_level]
+		self.assertEqual(flt(row[7]), total_outgoing)  # consumed
+		self.assertEqual(flt(row[8]), 0.0)  # delivered
+		self.assertEqual(flt(row[9]), total_outgoing)  # total outgoing
+		self.assertEqual(flt(row[10]), expected_avg)  # avg daily outgoing
+		self.assertEqual(flt(row[11]), expected_reorder)  # reorder level
+
+	def test_no_consumption_yields_zero_outgoing(self):
+		item = make_item(properties={"is_stock_item": 1, "lead_time_days": 3, "safety_stock": 5}).name
+		make_stock_entry(item_code=item, to_warehouse=WAREHOUSE, qty=100, rate=10, posting_date="2026-06-01")
+
+		row = self.find_row(self.run_report(), item)
+		self.assertIsNotNone(row)
+		self.assertEqual(flt(row[9]), 0.0)  # total outgoing
+		self.assertEqual(flt(row[10]), 0.0)  # avg daily outgoing
+		# With no consumption, reorder level falls back to safety_stock only.
+		self.assertEqual(flt(row[11]), 5.0)