def test_simple_take(self):
"""take 10 events in batch."""
timeseries = TimeSeries(SEPT_2014_DATA)
kcol = (
Pipeline().from_source(timeseries).take(10).to_keyed_collections())
new_ts = TimeSeries(dict(name='result', collection=kcol.get('all')))
self.assertEqual(new_ts.size(), 10)
def test_simple_take(self):
"""take 10 events in batch."""
timeseries = TimeSeries(SEPT_2014_DATA)
kcol = (
Pipeline()
.from_source(timeseries)
.take(10)
.to_keyed_collections()
)
new_ts = TimeSeries(dict(name='result', collection=kcol.get('all')))
self.assertEqual(new_ts.size(), 10)
def test_series_creation(self):
"""test timeseries creation.
Calls to to_json() are to trigger coverage for different variants.
"""
# from a wire format event list
ts1 = TimeSeries(DATA)
self.assertEqual(ts1.size(), len(DATA.get('points')))
# from a wire format index
ts2 = TimeSeries(AVAILABILITY_DATA)
self.assertEqual(ts2.size(), len(AVAILABILITY_DATA.get('points')))
self.assertEqual(ts2.to_json().get('name'), 'availability')
# from a list of events
ts3 = TimeSeries(dict(name='events', events=EVENT_LIST))
self.assertEqual(ts3.size(), len(EVENT_LIST))
# from a collection
ts4 = TimeSeries(
dict(name='collection', collection=self._canned_collection))
self.assertEqual(ts4.size(), self._canned_collection.size())
# copy constructor
ts5 = TimeSeries(ts4)
self.assertEqual(ts4.size(), ts5.size())
# from a wire format time range
ts6 = TimeSeries(TICKET_RANGE)
self.assertEqual(ts6.size(), len(TICKET_RANGE.get('points')))
self.assertEqual(ts6.to_json().get('name'), 'outages')
# non-utc indexed data variant mostly for coverage
idxd = copy.deepcopy(INDEXED_DATA)
idxd['utc'] = False
ts7 = TimeSeries(idxd)
self.assertFalse(ts7.is_utc())
self.assertFalse(ts7.to_json().get('utc'))
# indexed data variant using Index object - for coverage as well
idxd2 = copy.deepcopy(INDEXED_DATA)
idxd2['index'] = Index(idxd2.get('index'))
ts8 = TimeSeries(idxd2)
self.assertEqual(ts8.to_json().get('index'), '1d-625')
# make sure complex/deep/nested wire format is being handled correctly.
ts7 = TimeSeries(DATA_FLOW)
self.assertEqual(ts7.at(0).value('direction').get('in'), 1)
self.assertEqual(ts7.at(0).value('direction').get('out'), 2)
self.assertEqual(ts7.at(1).value('direction').get('in'), 3)
self.assertEqual(ts7.at(1).value('direction').get('out'), 4)
def test_series_creation(self):
"""test timeseries creation.
Calls to to_json() are to trigger coverage for different variants.
"""
# from a wire format event list
ts1 = TimeSeries(DATA)
self.assertEqual(ts1.size(), len(DATA.get('points')))
# from a wire format index
ts2 = TimeSeries(AVAILABILITY_DATA)
self.assertEqual(ts2.size(), len(AVAILABILITY_DATA.get('points')))
self.assertEqual(ts2.to_json().get('name'), 'availability')
# from a list of events
ts3 = TimeSeries(dict(name='events', events=EVENT_LIST))
self.assertEqual(ts3.size(), len(EVENT_LIST))
# from a collection
ts4 = TimeSeries(dict(name='collection', collection=self._canned_collection))
self.assertEqual(ts4.size(), self._canned_collection.size())
# copy constructor
ts5 = TimeSeries(ts4)
self.assertEqual(ts4.size(), ts5.size())
# from a wire format time range
ts6 = TimeSeries(TICKET_RANGE)
self.assertEqual(ts6.size(), len(TICKET_RANGE.get('points')))
self.assertEqual(ts6.to_json().get('name'), 'outages')
# non-utc indexed data variant mostly for coverage
idxd = copy.deepcopy(INDEXED_DATA)
idxd['utc'] = False
ts7 = TimeSeries(idxd)
self.assertFalse(ts7.is_utc())
self.assertFalse(ts7.to_json().get('utc'))
# indexed data variant using Index object - for coverage as well
idxd2 = copy.deepcopy(INDEXED_DATA)
idxd2['index'] = Index(idxd2.get('index'))
ts8 = TimeSeries(idxd2)
self.assertEqual(ts8.to_json().get('index'), '1d-625')
# make sure complex/deep/nested wire format is being handled correctly.
ts7 = TimeSeries(DATA_FLOW)
self.assertEqual(ts7.at(0).value('direction').get('in'), 1)
self.assertEqual(ts7.at(0).value('direction').get('out'), 2)
self.assertEqual(ts7.at(1).value('direction').get('in'), 3)
self.assertEqual(ts7.at(1).value('direction').get('out'), 4)