def test_should_return_same_df_when_column_not_exists(self): transformation = Transformation(self.test_data) transformation.split_content("time", ["day", "month", "year"]) current_result = transformation.dataframe.columns expected_result = self.test_data.columns self.assertEqual(current_result, expected_result)
def test_should_return_same_df_when_columns_param_is_empty(self): transformation = Transformation(self.test_data) transformation.split_content("", []) current_result = transformation.dataframe.columns expected_result = self.test_data.columns self.assertEqual(current_result, expected_result)
def test_should_split_column_content_into_three_new_columns(self): transformation = Transformation(self.test_data) transformation.split_content("coordinates", ["longitude", "latitude", "depth"]) current_result = transformation.dataframe.columns expected_result = [ "date", "place", "mag", "status", "longitude", "latitude", "depth", "alert" ] self.assertCountEqual(current_result, expected_result)
def test_should_return_transformed_data_using_all_pipeline_components( self, mock_get_data): self.create_tmp_folder() fake_api_input = ApiInput(self.FAKE_URL) mock_get_data.return_value = self.FAKE_INPUT_DATA extraction_process = Extraction(fake_api_input) extraction_process.extract() raw_data = extraction_process.data raw_df = self.spark.createDataFrame( raw_data, ["date", "place", "mag", "status", "coordinates", "alert"]) transformation_process = Transformation(raw_df) transformation_process.drop(["alert"]) transformation_process.rename({"mag": "magnitude", "place": "city"}) transformation_process.replace_null_values({"status": "Automatic"}) transformation_process.lowercase(["status"]) transformation_process.convert_data_type({"date": IntegerType()}) transformation_process.split_content( "coordinates", ["longitude", "latitude", "depth"]) transformed_df = transformation_process.dataframe csv_storage = CsvStorage(self.OUTPUT_FILEPATH) loading_process = Loading(csv_storage) loading_process.load(transformed_df) current_result = self.spark \ .read \ .csv(self.OUTPUT_FILEPATH, header=True, inferSchema=True) \ .collect() expected_result = self.spark \ .createDataFrame(self.FAKE_EXPECTED_DATA, ["date", "city", "magnitude", "status", "longitude", "latitude", "depth"]) \ .collect() self.assertEqual(current_result, expected_result) self.delete_test_file()