def get_total(self, types, begin, end, groupby=None, filters=None):
total = copy.deepcopy(self.total_sample)
series = []
filter_func = functools.partial(self.__filter_func, types, filters,
begin, end)
points = filter(filter_func, self._points)
for point in points:
target_serie = self.__get_target_serie(point, series, groupby)
target_serie['values'][0][1] += point['fields']['qty']
target_serie['values'][0][2] += point['fields']['price']
total['series'] = series
return resultset.ResultSet(total)
def retrieve(self,
types,
filters,
begin,
end,
offset=0,
limit=1000,
paginate=True):
output = copy.deepcopy(self.total_sample)
filter_func = functools.partial(self.__filter_func, types, filters,
begin, end)
points = list(filter(filter_func, self._points))
columns = set()
for point in points:
columns.update(point['tags'].keys())
columns.update(point['fields'].keys())
columns.add('time')
series = {
'name': 'dataframes',
'columns': list(columns),
}
values = []
def __get_tag_or_field(point, key):
if key == 'time':
return point['time'].isoformat()
return point['tags'].get(key) or point['fields'].get(key)
for point in points:
values.append(
[__get_tag_or_field(point, key) for key in series['columns']])
series['values'] = values
output['series'] = [series]
return len(list(points)), resultset.ResultSet(output)