def call_usecases(
dataset_representation, source_name, dataset_url, api_url, username, password
):
dataset_representation = process_start_service_date_for_gtfs_metadata(
dataset_representation
)
dataset_representation = process_end_service_date_for_gtfs_metadata(
dataset_representation
)
# TODO: fix the actual issue. might be taken care of once validator is deployed.
try:
dataset_representation = process_start_timestamp_for_gtfs_metadata(
dataset_representation
)
except TypeError as te:
print(
f"process_start_timestamp_for_gtfs_metadata for source {source_name},"
f"dataset {dataset_url} raised: \n {te}",
file=sys.stderr,
)
try:
dataset_representation = process_end_timestamp_for_gtfs_metadata(
dataset_representation
)
except TypeError as te:
print(
f"process_end_timestamp_for_gtfs_metadata for source {source_name}, dataset {dataset_url} raised: \n {te}",
file=sys.stderr,
)
dataset_representation = process_main_language_code_for_gtfs_metadata(
dataset_representation
)
dataset_representation = process_timezones_for_gtfs_metadata(dataset_representation)
dataset_representation = process_bounding_box_for_gtfs_metadata(
dataset_representation
)
dataset_representation = process_bounding_octagon_for_gtfs_metadata(
dataset_representation
)
dataset_representation = process_agencies_count_for_gtfs_metadata(
dataset_representation
)
dataset_representation = process_routes_count_by_type_for_gtfs_metadata(
dataset_representation
)
dataset_representation = process_stops_count_by_type_for_gtfs_metadata(
dataset_representation
)
dataset_representation = create_dataset_entity_for_gtfs_metadata(
dataset_representation, api_url, username, password
)
return dataset_representation
def test_process_routes_count_by_type_with_every_route(self, mock_env):
test_env = {
TRAM_CODE: "test_tram_code",
SUBWAY_CODE: "test_subway_code",
RAIL_CODE: "test_rail_code",
BUS_CODE: "test_bus_code",
FERRY_CODE: "test_ferry_code",
CABLE_TRAM_CODE: "test_cable_tram_code",
AERIAL_LIFT_CODE: "test_aerial_lift_code",
FUNICULAR_CODE: "test_funicular_code",
TROLLEY_BUS_CODE: "test_trolley_bus_code",
MONORAIL_CODE: "test_monorail_code",
}
mock_env.__getitem__.side_effect = test_env.__getitem__
mock_routes = PropertyMock(return_value=pd.DataFrame(
{ROUTE_TYPE: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]}))
mock_dataset = MagicMock()
mock_dataset.__class__ = Feed
type(mock_dataset).routes = mock_routes
mock_metadata = MagicMock()
mock_metadata.__class__ = GtfsMetadata
mock_gtfs_representation = MagicMock()
mock_gtfs_representation.__class__ = GtfsRepresentation
type(mock_gtfs_representation).dataset = mock_dataset
type(mock_gtfs_representation).metadata = mock_metadata
under_test = process_routes_count_by_type_for_gtfs_metadata(
mock_gtfs_representation)
self.assertIsInstance(under_test, GtfsRepresentation)
mock_routes.assert_called()
self.assertEqual(
mock_metadata.routes_count_by_type,
{
"test_tram_code": 1,
"test_subway_code": 1,
"test_rail_code": 1,
"test_bus_code": 1,
"test_ferry_code": 1,
"test_cable_tram_code": 1,
"test_aerial_lift_code": 1,
"test_funicular_code": 1,
"test_trolley_bus_code": 1,
"test_monorail_code": 1,
},
)
def test_process_routes_count_with_missing_files(self, mock_env):
mock_dataset = MagicMock()
mock_dataset.__class__ = Feed
mock_metadata = MagicMock()
mock_metadata.__class__ = GtfsMetadata
mock_gtfs_representation = MagicMock()
mock_gtfs_representation.__class__ = GtfsRepresentation
type(mock_gtfs_representation).dataset = mock_dataset
type(mock_gtfs_representation).metadata = mock_metadata
under_test = process_routes_count_by_type_for_gtfs_metadata(
mock_gtfs_representation)
self.assertIsInstance(under_test, GtfsRepresentation)
mock_env.assert_not_called()
mock_metadata.routes_count_by_type.assert_not_called()
def test_process_routes_count_by_type_with_no_routes(self, mock_env):
mock_routes = PropertyMock(return_value=pd.DataFrame({ROUTE_TYPE: []}))
mock_dataset = MagicMock()
mock_dataset.__class__ = Feed
type(mock_dataset).routes = mock_routes
mock_metadata = MagicMock()
mock_metadata.__class__ = GtfsMetadata
mock_gtfs_representation = MagicMock()
mock_gtfs_representation.__class__ = GtfsRepresentation
type(mock_gtfs_representation).dataset = mock_dataset
type(mock_gtfs_representation).metadata = mock_metadata
under_test = process_routes_count_by_type_for_gtfs_metadata(
mock_gtfs_representation)
self.assertIsInstance(under_test, GtfsRepresentation)
mock_metadata.routes_count_by_type.assert_not_called()
def test_process_routes_count_with_valid_gtfs_representation_should_return_instance(
self, mock_env):
test_env = {
TRAM_CODE: "test_tram_code",
SUBWAY_CODE: "test_subway_code",
RAIL_CODE: "test_rail_code",
BUS_CODE: "test_bus_code",
FERRY_CODE: "test_ferry_code",
CABLE_TRAM_CODE: "test_cable_tram_code",
AERIAL_LIFT_CODE: "test_aerial_lift_code",
FUNICULAR_CODE: "test_funicular_code",
TROLLEY_BUS_CODE: "test_trolley_bus_code",
MONORAIL_CODE: "test_monorail_code",
}
mock_env.__getitem__.side_effect = test_env.__getitem__
mock_gtfs_representation = MagicMock()
mock_gtfs_representation.__class__ = GtfsRepresentation
under_test = process_routes_count_by_type_for_gtfs_metadata(
mock_gtfs_representation)
self.assertIsInstance(under_test, GtfsRepresentation)
dataset_representation)
dataset_representation = process_end_service_date_for_gtfs_metadata(
dataset_representation)
dataset_representation = process_start_timestamp_for_gtfs_metadata(
dataset_representation)
dataset_representation = process_end_timestamp_for_gtfs_metadata(
dataset_representation)
dataset_representation = process_main_language_code_for_gtfs_metadata(
dataset_representation)
dataset_representation = process_timezones_for_gtfs_metadata(
dataset_representation)
dataset_representation = process_bounding_box_for_gtfs_metadata(
dataset_representation)
dataset_representation = process_bounding_octagon_for_gtfs_metadata(
dataset_representation)
dataset_representation = process_agencies_count_for_gtfs_metadata(
dataset_representation)
dataset_representation = process_routes_count_by_type_for_gtfs_metadata(
dataset_representation)
dataset_representation = process_stops_count_by_type_for_gtfs_metadata(
dataset_representation)
dataset_representation = create_dataset_entity_for_gtfs_metadata(
dataset_representation, api_url)
# Print results
data_repository.print_dataset_representation(dataset_key)
# Print memory usage
print("\n--------------- Memory Usage ---------------\n")
print(hpy().heap())