django-orchestra-test/orchestra/contrib/resources/aggregations.py

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