import datetime import decimal import itertools from django.utils import timezone from django.utils.translation import ugettext_lazy as _ from orchestra.utils.python import AttrDict from orchestra import plugins class Aggregation(plugins.Plugin, metaclass=plugins.PluginMount): """ filters and computes dataset usage """ aggregated_history = False def filter(self, dataset): """ Filter the dataset to get the relevant data according to the period """ raise NotImplementedError def compute_usage(self, dataset): """ given a dataset computes its usage according to the method (avg, sum, ...) """ raise NotImplementedError def aggregate_history(self, dataset): raise NotImplementedError class Last(Aggregation): """ Sum of the last value of all monitors """ name = 'last' verbose_name = _("Last value") def filter(self, dataset, date=None): dataset = dataset.order_by('object_id', '-id').distinct('monitor') if date is not None: dataset = dataset.filter(created_at__lte=date) return dataset def compute_usage(self, dataset): values = dataset.values_list('value', flat=True) if values: return sum(values) return None def aggregate_history(self, dataset): prev_object_id = None for mdata in dataset.order_by('object_id', 'created_at'): object_id = mdata.object_id if object_id != prev_object_id: if prev_object_id is not None: yield (mdata.content_object_repr, datas) datas = [mdata] else: datas.append(mdata) prev_object_id = object_id if prev_object_id is not None: yield (mdata.content_object_repr, datas) class MonthlySum(Last): """ Monthly sum the values of all monitors """ name = 'monthly-sum' verbose_name = _("Monthly Sum") aggregated_history = True def filter(self, dataset, date=None): if date is None: date = timezone.now().date() return dataset.filter( created_at__year=date.year, created_at__month=date.month, ) def aggregate_history(self, dataset): prev = None prev_object_id = None datas = [] sink = AttrDict(object_id=-1, value=-1, content_object_repr='', created_at=AttrDict(year=-1, month=-1)) for mdata in itertools.chain(dataset.order_by('object_id', 'created_at'), [sink]): object_id = mdata.object_id ymonth = (mdata.created_at.year, mdata.created_at.month) if object_id != prev_object_id or ymonth != prev.ymonth: if prev_object_id is not None: data = AttrDict( date=datetime.date( year=prev.ymonth[0], month=prev.ymonth[1], day=1 ), value=current, content_object_repr=prev.content_object_repr ) datas.append(data) current = mdata.value else: current += mdata.value if object_id != prev_object_id: if prev_object_id is not None: yield(prev.content_object_repr, datas) datas = [] prev = mdata prev.ymonth = ymonth prev_object_id = object_id class MonthlyAvg(MonthlySum): """ sum of the monthly averages of each monitor """ name = 'monthly-avg' verbose_name = _("Monthly AVG") aggregated_history = False def get_epoch(self, date=None): if date is None: date = timezone.now().date() return datetime.date( year=date.year, month=date.month, day=1, ) def compute_usage(self, dataset): result = 0 has_result = False aggregate = [] for object_id, dataset in dataset.order_by('created_at').group_by('object_id').items(): try: last = dataset[-1] except IndexError: continue epoch = self.get_epoch(date=last.created_at) total = (last.created_at-epoch).total_seconds() ini = epoch current = 0 for mdata in dataset: has_result = True slot = (mdata.created_at-ini).total_seconds() current += mdata.value * decimal.Decimal(str(slot/total)) ini = mdata.created_at else: result += current if has_result: return result return None def aggregate_history(self, dataset): yield from super(MonthlySum, self).aggregate_history(dataset) class Last10DaysAvg(MonthlyAvg): """ sum of the last 10 days averages of each monitor """ name = 'last-10-days-avg' verbose_name = _("Last 10 days AVG") days = 10 def get_epoch(self, date=None): if date is None: date = timezone.now().date() return date - datetime.timedelta(days=self.days) def filter(self, dataset, date=None): epoch = self.get_epoch(date=date) dataset = dataset.filter(created_at__gt=epoch) if date is not None: dataset = dataset.filter(created_at__lte=date) return dataset