def test_delete(self):
self._save_observations()
records = Observation.find(self.dataset)
self.assertNotEqual(records, [])
Observation.delete_all(self.dataset)
records = [x for x in Observation.find(self.dataset)]
self.assertEqual(records, [])
def test_delete_all(self):
self.__save_records()
records = Observation.find(self.dataset)
self.assertNotEqual(records, [])
Observation.delete_all(self.dataset)
records = Observation.find(self.dataset)
self.assertEqual(records, [])
def test_delete_one(self):
self.__save_records()
records = Observation.find(self.dataset)
self.assertNotEqual(records, [])
row = self.__decode(records[0])
Observation.delete(self.dataset, row[INDEX])
new_records = Observation.find(self.dataset)
# Dump to avoid problems with nan != nan.
self.assertEqual(dump_mongo_json(records[1:]),
dump_mongo_json(new_records))
def observations(self, query_args=None, as_cursor=False):
"""Return observations for this dataset.
:param query_args: An optional QueryArgs to hold the query arguments.
:param as_cursor: Return the observations as a cursor.
"""
return Observation.find(self, query_args or QueryArgs(),
as_cursor=as_cursor)
def _save_records(self):
Observation.save(self.get_data('good_eats.csv'),
self.dataset)
records = Observation.find(self.dataset)
self.assertTrue(isinstance(records, list))
self.assertTrue(isinstance(records[0], dict))
self.assertTrue('_id' in records[0].keys())
return records
def test_find_with_select_and_query(self):
self.__save_records()
self.query_args.select = {"rating": 1}
rows = Observation.find(self.dataset, self.query_args)
self.assertTrue(isinstance(rows, list))
row = self.__decode(rows[0])
self.assertEquals(sorted(row.keys()), ['_id', 'rating'])
def __save_records(self):
Observation.save(self.get_data('good_eats.csv'),
self.dataset)
records = Observation.find(self.dataset)
self.assertTrue(isinstance(records, list))
self.assertTrue(isinstance(records[0], dict))
self.assertTrue('_id' in records[0].keys())
return records
def observations(self, query_args=None, as_cursor=False):
"""Return observations for this dataset.
:param query_args: An optional QueryArgs to hold the query arguments.
:param as_cursor: Return the observations as a cursor.
"""
return Observation.find(self,
query_args or QueryArgs(),
as_cursor=as_cursor)
def observations(self, query=None, select=None, limit=0, order_by=None,
as_cursor=False):
"""Return observations for this dataset.
:param query: Optional query for MongoDB to limit rows returned.
:param select: Optional select for MongoDB to limit columns.
:param limit: If greater than 0, limit number of observations returned
to this maximum.
:param order_by: Order the returned observations.
"""
return Observation.find(self, query, select, limit=limit,
order_by=order_by, as_cursor=as_cursor)
def observations(self, query_args=QueryArgs(), as_cursor=False):
"""Return observations for this dataset.
:param query_args: An optional QueryArgs to hold the query arguments.
:param as_cursor: Return the observations as a cursor.
"""
if query_args.distinct:
as_cursor = True
observations = Observation.find(self, query_args, as_cursor=as_cursor)
if query_args.distinct:
observations = observations.distinct(query_args.distinct)
return observations
def test_dframe(self):
dataset = Dataset.create(self.test_dataset_ids['good_eats.csv'])
dataset.save_observations(
recognize_dates(self.get_data('good_eats.csv')))
records = [x for x in Observation.find(dataset)]
dframe = dataset.dframe()
self.assertTrue(isinstance(dframe, DataFrame))
self.assertTrue(all(self.get_data('good_eats.csv').reindex(
columns=dframe.columns).eq(dframe)))
columns = dframe.columns
# ensure no reserved keys
for key in MONGO_RESERVED_KEY_STRS:
self.assertFalse(key in columns)
# ensure date is converted
self.assertTrue(isinstance(dframe.submit_date[0], datetime))
def test_edit_row(self):
dataset_id = self._post_file()
index = 0
update = {'amount': 10, 'food_type': 'breakfast'}
expected_dframe = Dataset.find_one(dataset_id).dframe()
expected_row = expected_dframe.ix[0].to_dict()
expected_row.update(update)
expected_dframe.ix[0] = Series(expected_row)
results = json.loads(self.controller.row_update(dataset_id, index,
json.dumps(update)))
self.assertTrue(Datasets.SUCCESS in results.keys())
dataset = Dataset.find_one(dataset_id)
dframe = dataset.dframe()
self.assertEqual(self.NUM_ROWS, len(dframe))
self._check_dframes_are_equal(expected_dframe, dframe)
# check that previous row exists
all_observations = Observation.find(dataset, include_deleted=True)
self.assertEqual(self.NUM_ROWS + 1, len(all_observations))
def test_edit_row(self):
dataset_id = self._post_file()
index = 0
update = {'amount': 10, 'food_type': 'breakfast'}
expected_dframe = Dataset.find_one(dataset_id).dframe()
expected_row = expected_dframe.ix[0].to_dict()
expected_row.update(update)
expected_dframe.ix[0] = Series(expected_row)
results = json.loads(
self.controller.row_update(dataset_id, index, json.dumps(update)))
self.assertTrue(Datasets.SUCCESS in results.keys())
dataset = Dataset.find_one(dataset_id)
dframe = dataset.dframe()
self.assertEqual(self.NUM_ROWS, len(dframe))
self._check_dframes_are_equal(expected_dframe, dframe)
# check that previous row exists
all_observations = Observation.find(dataset, include_deleted=True)
self.assertEqual(self.NUM_ROWS + 1, len(all_observations))
def test_delete_row(self):
dataset_id = self._post_file()
dataset = Dataset.find_one(dataset_id)
index = 0
expected_dframe = Dataset.find_one(
dataset_id).dframe()[index + 1:].reset_index()
del expected_dframe['index']
results = json.loads(self.controller.row_delete(dataset_id, index))
self.assertTrue(Datasets.SUCCESS in results.keys())
dataset = Dataset.find_one(dataset_id)
dframe = dataset.dframe()
self.assertEqual(self.NUM_ROWS - 1, len(dframe))
self._check_dframes_are_equal(expected_dframe, dframe)
# check info updated
info = dataset.info()
self.assertEqual(self.NUM_ROWS - 1, info[Dataset.NUM_ROWS])
# check that row is softly deleted
all_observations = Observation.find(dataset, include_deleted=True)
self.assertEqual(self.NUM_ROWS, len(all_observations))
def test_delete_row(self):
dataset_id = self._post_file()
dataset = Dataset.find_one(dataset_id)
index = 0
expected_dframe = Dataset.find_one(
dataset_id).dframe()[index + 1:].reset_index()
del expected_dframe['index']
results = json.loads(self.controller.row_delete(dataset_id, index))
self.assertTrue(Datasets.SUCCESS in results.keys())
dataset = Dataset.find_one(dataset_id)
dframe = dataset.dframe()
self.assertEqual(self.NUM_ROWS - 1, len(dframe))
self._check_dframes_are_equal(expected_dframe, dframe)
# check info updated
info = dataset.info()
self.assertEqual(self.NUM_ROWS - 1, info[Dataset.NUM_ROWS])
# check that row is softly deleted
all_observations = Observation.find(dataset, include_deleted=True)
self.assertEqual(self.NUM_ROWS, len(all_observations))
def test_find_with_select(self):
self._save_observations()
query_args = QueryArgs(select={"rating": 1})
rows = Observation.find(self.dataset, query_args)
self.assertTrue(isinstance(rows, list))
self.assertEquals(sorted(rows[0].keys()), ['_id', 'rating'])
def test_find_with_query(self):
self._save_observations()
rows = Observation.find(self.dataset, self.query_args)
self.assertTrue(isinstance(rows, list))
def test_find(self):
self._save_observations()
rows = Observation.find(self.dataset)
self.assertTrue(isinstance(rows, list))
def test_save_over_bulk(self):
Observation.save(self.get_data('good_eats_large.csv'),
self.dataset)
records = Observation.find(self.dataset)
self.assertEqual(len(records), 1001)
def test_save_over_bulk(self):
Observation.save(self.get_data('good_eats_large.csv'),
self.dataset)
records = Observation.find(self.dataset)
self.assertEqual(len(records), 1001)
def test_find_with_select_and_query(self):
self._save_observations()
rows = Observation.find(self.dataset, '{"rating": "delectible"}',
'{"rating": 1}')
self.assertTrue(isinstance(rows, list))
self.assertEquals(sorted(rows[0].keys()), ['_id', 'rating'])
def test_find_with_query(self):
self._save_observations()
rows = Observation.find(self.dataset, '{"rating": "delectible"}')
self.assertTrue(isinstance(rows, list))
def test_find(self):
self.__save_records()
rows = Observation.find(self.dataset)
self.assertTrue(isinstance(rows, list))
def test_find_with_query(self):
self.__save_records()
rows = Observation.find(self.dataset, self.query_args)
self.assertTrue(isinstance(rows, list))
