def test_set_day_offset_none(self):
tr = TimeRange()
self.assertIsNone(tr.start)
self.assertIsNone(tr.start_org)
tr.set_start_day_offset(5)
self.assertIsNone(tr.start)
self.assertIsNone(tr.start_org)
def test_set_day_offset_neg(self):
start_dt = datetime(2020, 2, 14, 1, 1, 1, tzinfo=pytz.UTC)
tr = TimeRange(start=start_dt)
self.assertEqual(start_dt, tr.start)
self.assertEqual(start_dt, tr.start_org)
tr.set_start_day_offset(-5)
self.assertEqual(start_dt, tr.start_org)
self.assertEqual(start_dt - timedelta(days=5), tr.start)
def mean_message_count(
self, channel_oids: Union[ObjectId, List[ObjectId]], *, hours_within: Optional[int] = None,
start: Optional[datetime] = None, end: Optional[datetime] = None, tzinfo_: PytzInfo = UTC.to_tzinfo(),
max_mean_days: int = 5) -> \
MeanMessageResultGenerator:
match_d = self._channel_oids_filter_(channel_oids)
trange = TimeRange(range_hr=hours_within,
start=start,
end=end,
tzinfo_=tzinfo_)
trange.set_start_day_offset(-max_mean_days)
self._attach_time_range_(match_d, trange=trange)
pipeline = [{
"$match": match_d
}, {
"$group": {
"_id": {
MeanMessageResultGenerator.KEY_DATE: {
"$dateToString": {
"date": "$_id",
"format": MeanMessageResultGenerator.FMT_DATE,
"timezone": tzinfo_.tzidentifier
}
}
},
MeanMessageResultGenerator.KEY_COUNT: {
"$sum": 1
}
}
}, {
"$sort": {
"_id": pymongo.ASCENDING
}
}]
return MeanMessageResultGenerator(list(self.aggregate(pipeline)),
HourlyResult.data_days_collected(
self,
match_d,
hr_range=hours_within,
start=trange.start_org,
end=end),
tzinfo_,
trange=trange,
max_mean_days=max_mean_days)