def _fetch_queries(self):
query_aggregations = aggregate_queries(self._data_queries)
for dataset_id, query_map in query_aggregations.items():
for query in query_map.values():
df = fetch_query(query)
for query_dimensions, query_infos in query['queries'].items():
if valid_dimensions(query_dimensions, df):
queried_df = df.query(
build_query_string(query_dimensions))
for query_info in query_infos:
query_info.data = queried_df[
query_info.query.coordinate.measure]
else:
for query_info in query_infos:
query_info.data = Series()
for query_info in self._data_queries:
if query_info.data is None or len(query_info.data) == 0:
query_info.processor.calculate(
query_info.attr,
ProcessorResult(
False, f'No data found for '
f'Coordinate {query_info.query.coordinate}'))
else:
query_info.processor.calculate(
query_info.attr, ProcessorResult(True, query_info.data))
def _fetch_queries(self):
query_aggregations = aggregate_queries(self._data_queries)
for dataset_id, query_map in query_aggregations.items():
for query in query_map.values():
df = fetch_query(query)
for query_dimensions, query_infos in query['queries'].items():
if valid_dimensions(query_dimensions, df):
queried_df = df.query(
build_query_string(query_dimensions))
for query_info in query_infos:
measure = query_info.query.coordinate.measure
query_info.data = queried_df[measure if isinstance(
measure, str) else measure.value]
else:
for query_info in query_infos:
query_info.data = Series()
for query_info in self._data_queries:
if query_info.data is None or len(query_info.data) == 0:
asyncio.get_event_loop().run_until_complete(
query_info.processor.calculate(
query_info.attr,
ProcessorResult(
False, f'No data found for '
f'Coordinate {query_info.query.coordinate}'),
self.rule_cache))
else:
asyncio.get_event_loop().run_until_complete(
query_info.processor.calculate(
query_info.attr,
ProcessorResult(True,
query_info.data), self.rule_cache))