145 lines
4.5 KiB
Python
145 lines
4.5 KiB
Python
import copy
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import datetime
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import decimal
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from dateutil.relativedelta import relativedelta
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from django.utils import timezone
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from django.utils.translation import ugettext_lazy as _
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from orchestra import plugins
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class Aggregation(plugins.Plugin, metaclass=plugins.PluginMount):
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""" filters and computes dataset usage """
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def filter(self, dataset):
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""" Filter the dataset to get the relevant data according to the period """
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raise NotImplementedError
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def historic_filter(self, dataset):
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""" Generates (date, dataset) tuples for resource data history reporting """
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raise NotImplementedError
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def compute_usage(self, dataset):
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""" given a dataset computes its usage according to the method (avg, sum, ...) """
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raise NotImplementedError
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class Last(Aggregation):
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""" Sum of the last value of all monitors """
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name = 'last'
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verbose_name = _("Last value")
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def filter(self, dataset, date=None):
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dataset = dataset.order_by('object_id', '-id').distinct('monitor')
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if date is not None:
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dataset = dataset.filter(created_at__lte=date)
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return dataset
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def monthly_historic_filter(self, dataset):
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now = timezone.now()
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date = datetime.datetime(
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year=now.year,
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month=now.month,
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day=1,
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tzinfo=timezone.utc,
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)
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while True:
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dataset_copy = copy.copy(dataset)
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dataset_copy = self.filter(dataset_copy, date=date)
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try:
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dataset_copy[0]
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except IndexError:
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raise StopIteration
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yield (date, dataset_copy)
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date -= relativedelta(months=1)
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def historic_filter(self, dataset):
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yield (timezone.now(), self.filter(dataset))
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yield from self.monthly_historic_filter(dataset)
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def compute_usage(self, dataset):
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values = dataset.values_list('value', flat=True)
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if values:
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return sum(values)
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return None
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class MonthlySum(Last):
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""" Monthly sum the values of all monitors """
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name = 'monthly-sum'
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verbose_name = _("Monthly Sum")
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def filter(self, dataset, date=None):
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if date is None:
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date = timezone.now()
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return dataset.filter(
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created_at__year=date.year,
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created_at__month=date.month,
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)
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def historic_filter(self, dataset):
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yield from self.monthly_historic_filter(dataset)
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class MonthlyAvg(MonthlySum):
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""" sum of the monthly averages of each monitor """
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name = 'monthly-avg'
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verbose_name = _("Monthly AVG")
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def filter(self, dataset, date=None):
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qs = super(MonthlyAvg, self).filter(dataset, date=date)
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return qs.order_by('created_at')
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def get_epoch(self, date=None):
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if date is None:
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date = timezone.now()
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return datetime.datetime(
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year=date.year,
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month=date.month,
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day=1,
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tzinfo=timezone.utc,
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)
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def compute_usage(self, dataset):
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result = 0
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has_result = False
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for monitor, dataset in dataset.group_by('monitor').items():
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try:
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last = dataset[-1]
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except IndexError:
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continue
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epoch = self.get_epoch(date=last.created_at)
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total = (last.created_at-epoch).total_seconds()
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ini = epoch
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for data in dataset:
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has_result = True
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slot = (data.created_at-ini).total_seconds()
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result += data.value * decimal.Decimal(str(slot/total))
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ini = data.created_at
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if has_result:
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return result
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return None
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class Last10DaysAvg(MonthlyAvg):
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""" sum of the last 10 days averages of each monitor """
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name = 'last-10-days-avg'
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verbose_name = _("Last 10 days AVG")
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days = 10
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def get_epoch(self, date=None):
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if date is None:
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date = timezone.now()
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return date - datetime.timedelta(days=self.days)
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def filter(self, dataset, date=None):
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epoch = self.get_epoch(date=date)
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dataset = dataset.filter(created_at__gt=epoch).order_by('created_at')
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if date is not None:
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dataset = dataset.filter(created_at__lte=date)
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return dataset
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def historic_filter(self, dataset):
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yield (timezone.now(), self.filter(dataset))
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yield from super(Last10DaysAvg, self).historic_filter(dataset)
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