def import_dataset(_file, dataset):
"""
For reading a URL and saving the corresponding dataset.
"""
dframe = read_csv(_file)
Dataset.build_schema(dataset, dframe.dtypes)
Observation.save(dframe, dataset)
def _save_records(self):
records = Observation.save(self.test_data['good_eats.csv'],
self.dataset)
cursor = Observation.find(self.dataset)
records = [x for x in cursor]
self.assertTrue(isinstance(records, list))
self.assertTrue(isinstance(records[0], dict))
self.assertTrue('_id' in records[0].keys())
return records
def setUp(self):
TestBase.setUp(self)
self.dataset = Dataset.save(self.test_dataset_ids['good_eats.csv'])
dframe = self.test_data['good_eats.csv']
Dataset.build_schema(self.dataset, dframe.dtypes)
Observation.save(dframe, self.dataset)
self.calculations = [
'rating',
'gps',
'amount + gps_alt',
'amount - gps_alt',
'amount + 5',
'amount - gps_alt + 2.5',
'amount * gps_alt',
'amount / gps_alt',
'amount * gps_alt / 2.5',
'amount + gps_alt * gps_precision',
'(amount + gps_alt) * gps_precision',
'amount = 2',
'10 < amount',
'10 < amount + gps_alt',
'not amount = 2',
'not(amount = 2)',
'amount = 2 and 10 < amount',
'amount = 2 or 10 < amount',
'not not amount = 2 or 10 < amount',
'not amount = 2 or 10 < amount',
'(not amount = 2) or 10 < amount',
'not(amount = 2 or 10 < amount)',
'amount ^ 3',
'(amount + gps_alt) ^ 2 + 100',
'-amount',
'-amount < gps_alt - 100',
'rating in ["delectible"]',
'risk_factor in ["low_risk"]',
'amount in ["9.0", "2.0", "20.0"]',
'(risk_factor in ["low_risk"]) and (amount in ["9.0", "20.0"])',
]
self.places = 5
def _save_observations_and_calculation(self, formula=None):
if not formula:
formula = self.formula
Observation.save(self.test_data['good_eats.csv'], self.dataset)
return Calculation.save(self.dataset, formula, self.name)
def test_save_over_bulk(self):
Observation.save(self.test_data['good_eats_large.csv'],
self.dataset)
cursor = Observation.find(self.dataset)
records = [x for x in cursor]
self.assertEqual(len(records), 1001)
def _save_observations(self):
return Observation.save(self.test_data['good_eats.csv'], self.dataset)
