def test_reference_filter_for_an_unselected_metric(self):
reference_filter = ReferenceFilter(self.dataset.fields.unused_metric, ComparisonOperator.gt, 5)
reference = DayOverDay(self.dataset.fields.timestamp, filters=[reference_filter])
result_df = apply_reference_filters(self.df, reference)
pd.testing.assert_frame_equal(result_df, self.df)
def test_reference_filter_with_not_equal_to(self):
reference_filter = ReferenceFilter(self.dataset.fields.metric0, ComparisonOperator.ne, 5)
reference = DayOverDay(self.dataset.fields.timestamp, filters=[reference_filter])
result_df = apply_reference_filters(self.df, reference)
pd.testing.assert_frame_equal(
result_df.reset_index(drop=True),
pd.DataFrame.from_dict({"$metric0": [1, 3, 4], "$metric0_dod": [1, 9, 12]}),
)
def test_reference_filter_with_2_filters_combined(self):
reference_filter_gt = ReferenceFilter(self.dataset.fields.metric0, ComparisonOperator.gt, 3)
reference_filter_lt = ReferenceFilter(self.dataset.fields.metric0, ComparisonOperator.lt, 10)
reference = DayOverDay(
self.dataset.fields.timestamp,
filters=[reference_filter_gt, reference_filter_lt],
)
result_df = apply_reference_filters(self.df, reference)
pd.testing.assert_frame_equal(
result_df.reset_index(drop=True),
pd.DataFrame.from_dict({"$metric0": [2, 3], "$metric0_dod": [5, 9]}),
)
def fetch(self, hint=None) -> Union[Iterable[Dict], Dict]:
"""
Fetch the data for this query and transform it into the widgets.
:param hint:
A query hint label used with database vendors which support it. Adds a label comment to the query.
:return:
A list of dict (JSON) objects containing the widget configurations.
"""
queries = add_hints(self.sql, hint)
operations = find_operations_for_widgets(self._widgets)
dimensions = self.dimensions
share_dimensions = find_share_dimensions(dimensions, operations)
annotation_frame = None
if dimensions and self.dataset.annotation:
alignment_dimension_alias = self.dataset.annotation.dataset_alignment_field_alias
first_dimension = find_field_in_modified_field(dimensions[0])
if first_dimension.alias == alignment_dimension_alias:
annotation_frame = self.fetch_annotation()
max_rows_returned, data_frame = fetch_data(
self.dataset.database,
queries,
dimensions,
share_dimensions,
self.reference_groups,
)
# Apply reference filters
for reference in self._references:
data_frame = apply_reference_filters(data_frame, reference)
# Apply operations
for operation in operations:
for reference in [None] + self._references:
df_key = alias_selector(reference_alias(operation, reference))
data_frame[df_key] = operation.apply(data_frame, reference)
data_frame = scrub_totals_from_share_results(data_frame, dimensions)
data_frame = special_cases.apply_operations_to_data_frame(operations, data_frame)
data_frame = paginate(
data_frame,
self._widgets,
orders=self.orders,
limit=self._client_limit,
offset=self._client_offset,
)
# Apply transformations
widget_data = [
widget.transform(
data_frame,
dimensions,
self._references,
annotation_frame,
)
for widget in self._widgets
]
return self._transform_for_return(widget_data, max_rows_returned=max_rows_returned)
