# Copyright (c) 2019, Frappe Technologies Pvt. Ltd. and Contributors
# License: MIT. See LICENSE

import frappe
import frappe.utils
from frappe.desk.query_report import build_xlsx_data, export_query
from frappe.tests.utils import FrappeTestCase
from frappe.utils.xlsxutils import make_xlsx


class TestQueryReport(FrappeTestCase):
	def test_xlsx_data_with_multiple_datatypes(self):
		"""Test exporting report using rows with multiple datatypes (list, dict)"""

		# Create mock data
		data = frappe._dict()
		data.columns = [
			{"label": "Column A", "fieldname": "column_a", "fieldtype": "Float"},
			{"label": "Column B", "fieldname": "column_b", "width": 100, "fieldtype": "Float"},
			{"label": "Column C", "fieldname": "column_c", "width": 150, "fieldtype": "Duration"},
		]
		data.result = [
			[1.0, 3.0, 600],
			{"column_a": 22.1, "column_b": 21.8, "column_c": 86412},
			{"column_b": 5.1, "column_c": 53234, "column_a": 11.1},
			[3.0, 1.5, 333],
		]

		# Define the visible rows
		visible_idx = [0, 2, 3]

		# Build the result
		xlsx_data, column_widths = build_xlsx_data(data, visible_idx, include_indentation=0)

		self.assertEqual(type(xlsx_data), list)
		self.assertEqual(len(xlsx_data), 4)  # columns + data
		# column widths are divided by 10 to match the scale that is supported by openpyxl
		self.assertListEqual(column_widths, [0, 10, 15])

		for row in xlsx_data:
			self.assertIsInstance(row, list)

		# ensure all types are preserved
		for row in xlsx_data[1:]:
			for cell in row:
				self.assertIsInstance(cell, (int, float))

	def test_xlsx_export_with_composite_cell_value(self):
		"""Test excel export using rows with composite cell value"""

		data = frappe._dict()
		data.columns = [
			{"label": "Column A", "fieldname": "column_a", "fieldtype": "Float"},
			{"label": "Column B", "fieldname": "column_b", "width": 150, "fieldtype": "Data"},
		]
		data.result = [
			[1.0, "Dummy 1"],
			{"column_a": 22.1, "column_b": ["Dummy 1", "Dummy 2"]},  # composite value in column_b
		]

		# Define the visible rows
		visible_idx = [0, 1]

		# Build the result
		xlsx_data, column_widths = build_xlsx_data(data, visible_idx, include_indentation=0)
		# Export to excel
		make_xlsx(xlsx_data, "Query Report", column_widths=column_widths)

		for row in xlsx_data:
			# column_b should be 'str' even with composite cell value
			self.assertEqual(type(row[1]), str)

	def test_csv(self):
		from csv import QUOTE_ALL, QUOTE_MINIMAL, QUOTE_NONE, QUOTE_NONNUMERIC, DictReader
		from io import StringIO

		REPORT_NAME = "Test CSV Report"
		REF_DOCTYPE = "DocType"
		REPORT_COLUMNS = ["name", "module", "issingle"]

		if not frappe.db.exists("Report", REPORT_NAME):
			report = frappe.new_doc("Report")
			report.report_name = REPORT_NAME
			report.ref_doctype = "User"
			report.report_type = "Query Report"
			report.query = frappe.qb.from_(REF_DOCTYPE).select(*REPORT_COLUMNS).limit(10).get_sql()
			report.is_standard = "No"
			report.save()

		for delimiter in (",", ";", "\t", "|"):
			for quoting in (QUOTE_ALL, QUOTE_MINIMAL, QUOTE_NONE, QUOTE_NONNUMERIC):
				frappe.local.form_dict = frappe._dict(
					{
						"report_name": REPORT_NAME,
						"file_format_type": "CSV",
						"csv_quoting": quoting,
						"csv_delimiter": delimiter,
						"include_indentation": 0,
						"visible_idx": [0, 1, 2],
					}
				)
				export_query()

				self.assertTrue(frappe.response["filename"].endswith(".csv"))
				self.assertEqual(frappe.response["type"], "binary")
				with StringIO(frappe.response["filecontent"].decode("utf-8")) as result:
					reader = DictReader(result, delimiter=delimiter, quoting=quoting)
					row = reader.__next__()
					for column in REPORT_COLUMNS:
						self.assertIn(column, row)

		frappe.delete_doc("Report", REPORT_NAME, delete_permanently=True)