tests for config importer

hub/tests/test_import_from_config.py

@@ -0,0 +1,138 @@
+from io import StringIO
+from unittest import mock
+
+from django.core.management import call_command
+from django.test import TestCase
+
+import pandas as pd
+
+from hub.models import AreaData, DataSet
+
+
+class ImportTestCase(TestCase):
+    fixtures = ["areas.json"]
+
+    def call_command(self, quiet=True, *args, **kwargs):
+        out = StringIO()
+        call_command(
+            self.command,
+            quiet=quiet,
+            *args,
+            stdout=out,
+            stderr=StringIO(),
+            **kwargs,
+        )
+        return out.getvalue()
+
+
+class ImportAgeDataTestCase(ImportTestCase):
+    command = "import_from_config"
+
+    @mock.patch("hub.management.commands.import_from_config.pd.read_excel")
+    @mock.patch("hub.management.commands.import_from_config.json.load")
+    def test_import(self, patch_get_json, patch_get_excel):
+        data = {
+            "0-9": [0.123, 0.132, 0.1],
+            "10-19": [0.095, 0.144, 0],
+            "ONSConstID": [
+                "E10000001",
+                "E10000002",
+                "E40000001",
+            ],
+        }
+        patch_get_excel.return_value = pd.DataFrame(data=data)
+
+        config = [
+            {
+                "name": "constituency_age_distribution",
+                "label": "Constituency age distribution",
+                "data_type": "percent",
+                "category": "place",
+                "subcategory": "",
+                "release_date": "2021",
+                "is_range": True,
+                "source_label": "Data from ONS (England and Wales), NRS (Scotland), and NISRA (Northern Ireland), collated by House of Commons Library.",
+                "source": "https://commonslibrary.parliament.uk/constituency-statistics-population-by-age/",
+                "data_url": "https://commonslibrary.parliament.uk/constituency-statistics-population-by-age/",
+                "exclude_countries": None,
+                "fill_blanks": False,
+                "source_type": "xlxs",
+                "file_type": "excel",
+                "uses_gss": True,
+                "data_file": "file.xlsx",
+                "table": "areadata",
+                "default_value": 50,
+                "is_shadable": True,
+                "is_filterable": True,
+                "is_public": True,
+                "comparators": DataSet.numerical_comparators(),
+                "unit_type": "percentage",
+                "unit_distribution": "people_in_area",
+                "area_type": "WMC",
+                "constituency_col": "ONSConstID",
+                "data_types": [
+                    {
+                        "name": "ages_0_9",
+                        "label": "Ages 0 - 9",
+                        "data_col": "0-9",
+                    },
+                    {
+                        "name": "ages_10_19",
+                        "label": "Ages 10 - 19",
+                        "data_col": "10-19",
+                    },
+                ],
+            }
+        ]
+
+        patch_get_json.return_value = config
+
+        out = self.call_command(import_name="constituency_age_distribution")
+
+        self.assertEqual(
+            out,
+            "Failed to find area with code E40000001\nFailed to find area with code E40000001\n",
+        )
+        area_data = AreaData.objects.all()
+        self.assertEqual(area_data.count(), 4)
+
+        south_data = (
+            AreaData.objects.filter(area__gss="E10000001", area__area_type__code="WMC")
+            .order_by("data_type__name")
+            .all()
+        )
+
+        self.assertEqual(south_data[0].value(), 0.123)
+        self.assertEqual(south_data[1].value(), 0.095)
+
+        self.assertEqual(south_data[0].data_type.average, 0.1275)
+        self.assertEqual(south_data[1].data_type.average, 0.1195)
+
+        config[0]["multiply_percentage"] = True
+
+        out = self.call_command(import_name="constituency_age_distribution")
+
+        area_data = AreaData.objects.all()
+        self.assertEqual(area_data.count(), 4)
+        south_data = (
+            AreaData.objects.filter(area__gss="E10000001", area__area_type__code="WMC")
+            .order_by("data_type__name")
+            .all()
+        )
+
+        under_ten_data = (
+            AreaData.objects.filter(
+                data_type__name="ages_0_9", area__area_type__code="WMC"
+            )
+            .order_by("data_type__name")
+            .all()
+        )
+
+        self.assertEqual(south_data[0].value(), 12.3)
+        self.assertEqual(south_data[1].value(), 9.5)
+
+        self.assertEqual(round(under_ten_data[0].value(), 1), 12.3)
+        self.assertEqual(round(under_ten_data[1].value(), 1), 13.2)
+
+        self.assertEqual(south_data[0].data_type.average, 12.75)
+        self.assertEqual(south_data[1].data_type.average, 11.95)