def test_basic_response(self):
metric = metric_classes['NamespaceEdits'](
name='NamespaceEdits',
namespaces=[0, 1, 2],
start_date='2013-01-01 00:00:00',
end_date='2013-01-02 00:00:00',
)
options = {
'individualResults': True,
'aggregateResults': True,
'aggregateSum': True,
'aggregateAverage': True,
'aggregateStandardDeviation': True,
}
ar = AggregateReport(
metric,
self.cohort,
options,
user_id=self.owner_user_id,
)
result = ar.task.delay(ar).get()
assert_equals(result[Aggregation.IND][self.editor(0)]['edits'], 2)
assert_equals(result[Aggregation.AVG]['edits'], r(1.0))
assert_equals(result[Aggregation.STD]['edits'], r(1.0))
def test_basic_response(self):
cohort = self.session.query(Cohort).get(self.test_cohort_id)
metric = metric_classes['NamespaceEdits'](
name='NamespaceEdits',
namespaces=[0, 1, 2],
start_date='2013-06-01',
end_date='2013-09-01',
)
ar = AggregateReport(
cohort,
metric,
individual=True,
aggregate=True,
aggregate_sum=True,
aggregate_average=True,
aggregate_std_deviation=True,
user_id=self.test_user_id,
)
result = ar.task.delay(ar).get()
aggregate_key = self.session.query(PersistentReport)\
.filter(PersistentReport.id == ar.persistent_id)\
.one()\
.result_key
assert_equals(
result[aggregate_key][Aggregation.IND][0][
self.test_mediawiki_user_id]['edits'], 2)
assert_equals(result[aggregate_key][Aggregation.AVG]['edits'],
Decimal(1.25))
def test_aggregate_empty_results(self):
'''
Tests what happens when no users are
returned for the initial metric run
so there are no users to agreggate
'''
self.create_wiki_cohort()
metric = metric_classes['NamespaceEdits'](
name='NamespaceEdits',
namespaces=[0, 1, 2],
start_date='2010-01-01 00:00:00',
end_date='2010-01-02 00:00:00',
)
options = {
'individualResults': True,
'aggregateResults': True,
'aggregateSum': True,
'aggregateAverage': True,
'aggregateStandardDeviation': True,
}
ar = AggregateReport(
metric,
self.basic_wiki_cohort,
options,
user_id=self.basic_wiki_cohort_owner,
)
result = ar.task.delay(ar).get()
assert_equals(result[Aggregation.IND].keys(), [])
assert_equals(result[Aggregation.SUM]['edits'], r(0))
assert_equals(result[Aggregation.AVG]['edits'], r(0))
assert_equals(result[Aggregation.STD]['edits'], r(0))
def test_timeseries_day(self):
metric = NamespaceEdits(
namespaces=[0],
start_date='2012-12-31 00:00:00',
end_date='2013-01-03 00:00:00',
timeseries=TimeseriesChoices.DAY,
)
options = {
'individualResults': True,
'aggregateResults': True,
'aggregateSum': True,
'aggregateAverage': True,
'aggregateStandardDeviation': True,
}
ar = AggregateReport(
metric,
self.cohort,
options,
user_id=self.owner_user_id,
)
results = ar.task.delay(ar).get()
self.session.commit()
assert_equals(
results[Aggregation.IND][self.editor(0)]['edits'], {
'2012-12-31 00:00:00': 1,
'2013-01-01 00:00:00': 2,
'2013-01-02 00:00:00': 0,
})
assert_equals(
results[Aggregation.SUM]['edits'], {
'2012-12-31 00:00:00': 1,
'2013-01-01 00:00:00': 5,
'2013-01-02 00:00:00': 2,
})
assert_equals(
results[Aggregation.AVG]['edits'], {
'2012-12-31 00:00:00': r(0.25),
'2013-01-01 00:00:00': r(1.25),
'2013-01-02 00:00:00': r(0.5),
})
assert_equals(
results[Aggregation.STD]['edits'], {
'2012-12-31 00:00:00': r(0.4330),
'2013-01-01 00:00:00': r(0.4330),
'2013-01-02 00:00:00': r(0.8660),
})
def test_repr(self):
cohort = self.session.query(Cohort).get(self.test_cohort_id)
metric = metric_classes['NamespaceEdits'](
name='NamespaceEdits',
namespaces=[0, 1, 2],
start_date='2013-06-01',
end_date='2013-09-01',
)
ar = AggregateReport(
cohort,
metric,
individual=True,
aggregate=True,
aggregate_sum=True,
aggregate_average=True,
aggregate_std_deviation=True,
user_id=self.test_user_id,
)
assert_true(str(ar).find('AggregateReport') >= 0)
def test_does_not_aggregate_null_values(self):
metric = metric_classes['Threshold'](name='Threshold', )
options = {
'individualResults': True,
'aggregateResults': True,
'aggregateSum': True,
'aggregateAverage': True,
'aggregateStandardDeviation': True,
}
ar = AggregateReport(
metric,
self.cohort,
options,
user_id=self.owner_user_id,
)
finished = ar.finish([
{
1: {
'edits': 2,
'submetric': 1
},
2: {
'edits': 3,
'submetric': None
},
3: {
'edits': 0,
'submetric': 3
},
None: {
'edits': 0
}
},
])
assert_equals(finished[Aggregation.SUM]['submetric'], 4)
assert_equals(finished[Aggregation.AVG]['submetric'], 2)
def test_repr(self):
metric = metric_classes['NamespaceEdits'](
name='NamespaceEdits',
namespaces=[0, 1, 2],
start_date='2013-05-01 00:00:00',
end_date='2013-09-01 00:00:00',
)
options = {
'individualResults': True,
'aggregateResults': True,
'aggregateSum': True,
'aggregateAverage': True,
'aggregateStandardDeviation': True,
}
ar = AggregateReport(
metric,
self.cohort,
options,
user_id=self.owner_user_id,
)
assert_true(str(ar).find('AggregateReport') >= 0)
def test_finish(self):
cohort = self.session.query(Cohort).get(self.test_cohort_id)
metric = metric_classes['NamespaceEdits'](
name='NamespaceEdits',
namespaces=[0, 1, 2],
start_date='2013-06-01',
end_date='2013-09-01',
)
ar = AggregateReport(
cohort,
metric,
individual=True,
aggregate=True,
aggregate_sum=True,
aggregate_average=True,
aggregate_std_deviation=True,
user_id=self.test_user_id,
)
finished = ar.finish([
{
'namespace edits - fake cohort': {
1: {
'edits': 2
},
2: {
'edits': 3
},
3: {
'edits': 0
},
None: {
'edits': 0
}
}
},
{
'some other metric - fake cohort': {
1: {
'other_sub_metric': Decimal(2.3)
},
2: {
'other_sub_metric': Decimal(3.4)
},
3: {
'other_sub_metric': Decimal(0.0)
},
None: {
'other_sub_metric': 0
}
}
},
])
assert_equals(finished[ar.result_key][Aggregation.SUM]['edits'], 5)
assert_equals(
finished[ar.result_key][Aggregation.SUM]['other_sub_metric'],
Decimal(5.7))
assert_equals(
finished[ar.result_key][Aggregation.AVG]['edits'],
# TODO: Again, figure out this crazy "None" user id
Decimal(1.25))
assert_equals(
finished[ar.result_key][Aggregation.AVG]['other_sub_metric'],
Decimal(1.425))
def test_finish(self):
metric = metric_classes['NamespaceEdits'](
name='NamespaceEdits',
namespaces=[0, 1, 2],
start_date='2013-05-01 00:00:00',
end_date='2013-09-01 00:00:00',
)
options = {
'individualResults': True,
'aggregateResults': True,
'aggregateSum': True,
'aggregateAverage': True,
'aggregateStandardDeviation': True,
}
ar = AggregateReport(
metric,
self.cohort,
options,
user_id=self.owner_user_id,
)
finished = ar.finish([
{
1: {
'edits': 2
},
2: {
'edits': 3
},
3: {
'edits': 0
},
None: {
'edits': 0
}
},
])
assert_equals(finished[Aggregation.SUM]['edits'], 5)
assert_equals(finished[Aggregation.AVG]['edits'], r(1.25))
finished = ar.finish([
{
1: {
'other_sub_metric': r(2.3)
},
2: {
'other_sub_metric': r(3.4)
},
3: {
'other_sub_metric': r(0.0)
},
None: {
'other_sub_metric': 0
}
},
])
assert_equals(finished[Aggregation.SUM]['other_sub_metric'], r(5.7))
assert_equals(finished[Aggregation.AVG]['other_sub_metric'], r(1.425))
assert_equals(finished[Aggregation.STD]['other_sub_metric'], r(1.4771))
def test_finish_timeseries(self):
metric = NamespaceEdits(
namespaces=[0],
start_date='2012-12-31 00:00:00',
end_date='2013-01-03 00:00:00',
timeseries=TimeseriesChoices.DAY,
)
options = {
'individualResults': True,
'aggregateResults': True,
'aggregateSum': True,
'aggregateAverage': True,
'aggregateStandardDeviation': True,
}
ar = AggregateReport(
metric,
self.cohort,
options,
user_id=self.owner_user_id,
)
finished = ar.finish([
{
1: {
'edits': {
'date1': 1,
'date2': 2
}
},
2: {
'edits': {
'date1': 0,
'date2': 1
}
},
3: {
'edits': {
'date1': 0,
'date2': 0
}
},
None: {
'edits': {
'date1': None,
'date2': None
}
}
},
])
assert_equals(finished[Aggregation.SUM]['edits'], {
'date1': 1,
'date2': 3
})
assert_equals(finished[Aggregation.AVG]['edits'], {
'date1': r(0.3333),
'date2': r(1.0)
})
assert_equals(finished[Aggregation.STD]['edits'], {
'date1': r(0.4714),
'date2': r(0.8165)
})
finished = ar.finish([
{
1: {
'other_sub_metric': {
'date3': r(2.3),
'date4': 0
}
},
2: {
'other_sub_metric': {
'date3': 0,
'date4': r(3.4)
}
},
3: {
'other_sub_metric': {
'date3': None,
'date4': None
}
},
None: {
'other_sub_metric': {
'date3': None,
'date4': None
}
}
},
])
assert_equals(finished[Aggregation.SUM]['other_sub_metric'], {
'date3': r(2.3),
'date4': r(3.4)
})
assert_equals(finished[Aggregation.AVG]['other_sub_metric'], {
'date3': r(1.15),
'date4': r(1.7)
})
assert_equals(finished[Aggregation.STD]['other_sub_metric'], {
'date3': r(1.15),
'date4': r(1.7)
})
