def test_envelopes_responses_if_return_additional_metadata_True(
self, mock_fetch_data):
dataset = DataSet(
table=politicians_table,
database=test_database,
return_additional_metadata=True,
fields=[
Field(
"timestamp1",
label="timestamp1",
definition=politicians_table.timestamp1,
data_type=DataType.text,
hyperlink_template="http://example.com/{political_party}",
)
],
)
df = pd.DataFrame({
'political_party': ['a', 'b', 'c']
}).set_index('political_party')
mock_fetch_data.return_value = 100, df
result = dataset.latest(dataset.fields.timestamp1).fetch()
self.assertEqual(dict(max_rows_returned=100), result['metadata'])
self.assertTrue(result['data'].equals(
pd.Series(['a'], index=['political_party'])))
def setUpClass(cls):
db = TestDatabase()
t0 = Table("test0")
cls.dataset = DataSet(
table=t0,
database=db,
fields=[
Field(
"timestamp",
label="Timestamp",
definition=t0.timestamp,
data_type=DataType.date,
),
Field(
"metric0",
label="Metric0",
definition=t0.metric,
data_type=DataType.number,
),
Field(
"unused_metric",
label="Unused Metric",
definition=t0.unused_metric,
data_type=DataType.number,
),
],
)
cls.df = pd.DataFrame.from_dict({
"$metric0": [1, 2, 3, 4],
"$metric0_dod": [1, 5, 9, 12]
})
def test_reference_filters_are_applied(self, mock_fetch: Mock, mock_2: Mock, mock_apply_reference_filters: Mock):
db = TestDatabase()
t0 = Table("test0")
dataset = DataSet(
table=t0,
database=db,
fields=[
Field(
"timestamp",
label="Timestamp",
definition=t0.timestamp,
data_type=DataType.date,
),
Field(
"metric0",
label="Metric0",
definition=t0.metric,
data_type=DataType.number,
),
],
)
mock_widget = f.Widget(dataset.fields.metric0)
mock_widget.transform = Mock()
reference_filter = ReferenceFilter(
dataset.fields.metric0,
ComparisonOperator.gt,
5
)
reference = f.DayOverDay(dataset.fields.timestamp, filters=[reference_filter])
df = pd.DataFrame.from_dict({"$value": [1]})
mock_fetch.return_value = 100, df
mock_apply_reference_filters.return_value = df
(
dataset.query()
.dimension(dataset.fields.timestamp)
.widget(mock_widget)
.reference(reference)
).fetch()
mock_apply_reference_filters.assert_called_once_with(df, reference)
def test_pivoted_df_transformation_formats_totals_correctly(self):
test_table = Table('test')
ds = DataSet(
table=test_table,
database=test_database,
fields=[
Field('date', label='Date', definition=test_table.date, data_type=DataType.date),
Field('locale', label='Locale', definition=test_table.locale, data_type=DataType.text),
Field('company', label='Company', definition=test_table.text, data_type=DataType.text),
Field('metric1', label='Metric1', definition=Sum(test_table.number), data_type=DataType.number),
Field('metric2', label='Metric2', definition=Sum(test_table.number), data_type=DataType.number),
],
)
df = pd.DataFrame.from_dict(
{
'$metric1': {('~~totals', '~~totals'): 3, ('za', '~~totals'): 3, ('za', 'C1'): 2, ('za', 'C2'): 1},
'$metric2': {('~~totals', '~~totals'): 4, ('za', '~~totals'): 4, ('za', 'C1'): 2, ('za', 'C2'): 2},
}
)
df.index.names = [f(ds.fields.locale.alias), f(ds.fields.company.alias)]
result = Pandas(ds.fields.metric1, ds.fields.metric2, pivot=[ds.fields.company]).transform(
df, [Rollup(ds.fields.locale), Rollup(ds.fields.company)], [], use_raw_values=True
)
self.assertEqual(['Metrics', 'Company'], list(result.columns.names))
self.assertEqual(
[
('Metric1', 'C1'),
('Metric1', 'C2'),
('Metric1', 'Totals'),
('Metric2', 'C1'),
('Metric2', 'C2'),
('Metric2', 'Totals'),
],
result.columns.values.tolist(),
)
self.assertEqual(['Locale'], list(result.index.names))
self.assertEqual(['za', 'Totals'], result.index.values.tolist())
self.assertEqual([['2', '1', '3', '2', '2', '4'], ['', '', '3', '', '', '4']], result.values.tolist())