def test_staging_new_table(self):
# For the entry in MetaTable without a table, create a staging table.
# We'll need to read from a fixture csv.
with Staging(self.unloaded_meta,
source_path=self.radio_path) as s_table:
all_rows = session.execute(s_table.table.select()).fetchall()
self.assertEqual(len(all_rows), 5)
def test_staging_existing_table(self):
# With a fixture CSV whose columns match the existing dataset,
# create a staging table.
with Staging(self.existing_meta, source_path=self.dog_path) as s_table:
with postgres_engine.begin() as connection:
all_rows = connection.execute(s_table.table.select()).fetchall()
self.assertEqual(len(all_rows), 5)
def test_col_info_provided(self):
# The frontend should send back strings compatible with the COL_VALUES in etl.point
col_info_raw = [('event_name', 'string'),
('date', 'date'),
('lat', 'float'),
('lon', 'float')]
stored_col_info = [{'field_name': name, 'data_type': d_type}
for name, d_type in col_info_raw]
self.unloaded_meta.contributed_data_types = json.dumps(stored_col_info)
with Staging(self.unloaded_meta, source_path=self.radio_path) as s_table:
observed_names = self.extract_names(s_table.cols)
self.assertEqual(set(observed_names), set(self.expected_radio_col_names))
def test_col_info_existing(self):
with Staging(self.existing_meta, source_path=self.dog_path) as s_table:
observed_col_names = self.extract_names(s_table.cols)
self.assertEqual(set(observed_col_names),
set(self.expected_dog_col_names))
def test_col_info_infer(self):
with Staging(self.unloaded_meta,
source_path=self.radio_path) as s_table:
observed_names = self.extract_names(s_table.cols)
self.assertEqual(set(observed_names),
set(self.expected_radio_col_names))