def test_place_each_data_point_multi_value(self):
multi_data_points = [{
**dp, "total_population": 100
} for dp in _DATA_POINTS]
multi_value_keys = ["total_population", "total_revocations"]
expected = [
[0, 0, 1, 1, 2, 0, 0, 1, 1, 2, 2],
[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
[0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100],
[100, 68, 73, 41, 10, 30, 36, 51, 38, 15, 4],
]
fresh_data_values = self._create_new_data_values()
fresh_data_values.append([]) # Add one more for this test case
for data_point in multi_data_points:
optimized_metric_big_query_view_exporter.place_in_compact_matrix(
data_point,
fresh_data_values,
multi_value_keys,
_DIMENSION_MANIFEST,
)
self.assertEqual(expected, fresh_data_values)
def test_place_each_data_point_single_value(self):
fresh_data_values = self._create_new_data_values()
for data_point in _DATA_POINTS:
optimized_metric_big_query_view_exporter.place_in_compact_matrix(
data_point,
fresh_data_values,
_VALUE_KEYS,
_DIMENSION_MANIFEST,
)
self.assertEqual(_DATA_VALUES, fresh_data_values)
def test_place_value_not_in_dataset(self):
fresh_data_values = self._create_new_data_values()
new_data_point = {
"district": "6",
"year": 2020,
"month": 11,
"supervision_type": "PROBATION",
"other_value": 5,
}
optimized_metric_big_query_view_exporter.place_in_compact_matrix(
new_data_point,
fresh_data_values,
_VALUE_KEYS,
_DIMENSION_MANIFEST,
)
self.assertEqual([[2], [0], [1], [0], [0]], fresh_data_values)
def test_place_value_not_in_dataset(self):
fresh_data_values = self._create_new_data_values()
new_data_point = {
'district': '6',
'year': 2020,
'month': 11,
'supervision_type': 'PROBATION',
'other_value': 5
}
optimized_metric_big_query_view_exporter.place_in_compact_matrix(
new_data_point,
fresh_data_values,
_VALUE_KEYS,
_DIMENSION_MANIFEST,
)
self.assertEqual([[2], [0], [1], [0], [0]], fresh_data_values)
def test_place_dimensions_not_in_dataset(self):
fresh_data_values = self._create_new_data_values()
with pytest.raises(KeyError) as e:
new_data_point = {
"district": "4",
"year": 2020,
"month": 5,
"supervision_type": "PAROLE",
"total_revocations": 10,
}
optimized_metric_big_query_view_exporter.place_in_compact_matrix(
new_data_point,
fresh_data_values,
_VALUE_KEYS,
_DIMENSION_MANIFEST,
)
self.assertIn("month: 5", e.message)
def test_place_happy_path_single_value(self):
fresh_data_values = self._create_new_data_values()
optimized_metric_big_query_view_exporter.place_in_compact_matrix(
_DATA_POINTS[3],
fresh_data_values,
_VALUE_KEYS,
_DIMENSION_MANIFEST,
)
self.assertEqual([[1], [0], [1], [0], [41]], fresh_data_values)
optimized_metric_big_query_view_exporter.place_in_compact_matrix(
_DATA_POINTS[8],
fresh_data_values,
_VALUE_KEYS,
_DIMENSION_MANIFEST,
)
self.assertEqual([[1, 1], [0, 1], [1, 1], [0, 0], [41, 38]],
fresh_data_values)
def test_place_dimensions_not_in_dataset(self):
fresh_data_values = self._create_new_data_values()
with pytest.raises(KeyError) as e:
new_data_point = {
'district': '4',
'year': 2020,
'month': 5,
'supervision_type': 'PAROLE',
'total_revocations': 10,
}
optimized_metric_big_query_view_exporter.place_in_compact_matrix(
new_data_point,
fresh_data_values,
_VALUE_KEYS,
_DIMENSION_MANIFEST,
)
self.assertIn('month: 5', e.message)
