def test_granular_dataset(self):
self.api.log_curl_commands = True
granular_dataset = Dataset(
name='Test-granular-dataset',
filters={"$and": [{"rp_entity_id": {"$in": ["D8442A"]}}, {"relevance": 90}]},
)
granular_dataset = self.api.create_dataset(granular_dataset)
try:
granular_dataset.json('2018-01-01 00:00', '2018-01-02 00:00')
finally:
granular_dataset.delete()
def test_indicator_dataset(self):
indicator_dataset = Dataset(
name='Test-indicator-dataset',
filters={"$and": [{
"rp_entity_id": {
"$in": ["D8442A"]
}
}]},
fields=[{
"average": {
"avg": {
"field": "EVENT_SENTIMENT_SCORE"
}
}
}],
frequency='daily',
)
indicator_dataset = self.api.create_dataset(indicator_dataset)
try:
# ask the indicator dataset for its data
response = indicator_dataset.json('2018-01-01 00:00',
'2018-01-02 00:00')
assert len(response) == 2 # we should get 2 rows
assert {r['rp_entity_id']
for r in response} == {'D8442A', 'ROLLUP'}
# do a request overriding fields and frequency to see the underlying data
response = indicator_dataset.json(
'2018-01-01 00:00',
'2018-01-02 00:00',
fields=['rp_story_id', 'rp_entity_id'],
frequency='granular')
assert len(
response) > 200, "We should have many granular analytics rows"
assert {r['rp_entity_id']
for r in response} == {'D8442A'
}, "All rows should be D8442A"
finally:
indicator_dataset.delete()