vacaly commented on code in PR #192: URL: https://github.com/apache/flink-ml/pull/192#discussion_r1099882916
########## flink-ml-python/pyflink/ml/lib/recommendation/tests/test_swing.py: ########## @@ -0,0 +1,165 @@ +################################################################################ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +################################################################################ +from pyflink.common import Types +from pyflink.table import Table +from typing import List +from py4j.protocol import Py4JJavaError: + +from pyflink.ml.lib.recommendation.swing import Swing +from pyflink.ml.tests.test_utils import PyFlinkMLTestCase + + +# Tests Swing. +class SwingTest(PyFlinkMLTestCase): + def setUp(self): + super(SwingTest, self).setUp() + self.train_data = self.t_env.from_data_stream( + self.env.from_collection([ + (0, 10), + (0, 11), + (0, 12), + (1, 13), + (1, 12), + (2, 10), + (2, 11), + (2, 12), + (3, 13), + (3, 12) + ], + type_info=Types.ROW_NAMED( + ['user', 'item'], + [Types.LONG(), Types.LONG()]) + )) + + self.wrong_type_data = self.t_env.from_data_stream( + self.env.from_collection([ + (0, 10), + (1, 11), + (2, 12) + ], + type_info=Types.ROW_NAMED( + ['user', 'item'], + [Types.INT(), Types.LONG()]) + )) + + self.none_value_data = self.t_env.from_data_stream( + self.env.from_collection([ + (0, 10), + (None, 11), + (2, 12) + ], + type_info=Types.ROW_NAMED( + ['user', 'item'], + [Types.LONG(), Types.LONG()]) + )) + + self.expected_data = [ + [10, '11,0.058845768947156235;12,0.058845768947156235'], + [11, '10,0.058845768947156235;12,0.058845768947156235'], + [12, '13,0.09134833828228624;10,0.058845768947156235;11,0.058845768947156235'], + [13, '12,0.09134833828228624']] + + def test_param(self): + swing = Swing() + self.assertEqual("item", swing.item_col) + self.assertEqual("user", swing.user_col) + self.assertEqual(100, swing.k) + self.assertEqual(10, swing.min_user_items) + self.assertEqual(1000, swing.max_user_items) + self.assertEqual(15, swing.alpha1) + self.assertEqual(0, swing.alpha2) + self.assertEqual(0.3, swing.beta, delta=1e-9) + + swing.set_item_col("item_1") \ + .set_user_col("user_1") \ + .set_k(20) \ + .set_min_user_behavior(20) \ + .set_max_user_behavior(50) \ + .set_alpha1(5) \ + .set_alpha2(1) \ + .set_beta(0.35) + + self.assertEqual("item", swing.item_col) + self.assertEqual("user", swing.user_col) + self.assertEqual(20, swing.k) + self.assertEqual(20, swing.min_user_items) + self.assertEqual(50, swing.max_user_items) + self.assertEqual(5, swing.alpha1) + self.assertEqual(1, swing.alpha2) + self.assertEqual(0.35, swing.beta, delta=1e-9) + + def test_output_schema(self): + swing = Swing() \ + .set_item_col('test_item') \ + .set_user_col('test_user') \ + .set_output_col("item_score") + + output = swing.transform(self.train_data.alias(['test_user', 'test_item']))[0] + self.assertEqual( + ['test_item', 'item_score'], + output.get_schema().get_field_names()) + + def test_transform(self): + swing = Swing().set_min_user_behavior(1) + output = swing.transform(self.train_data)[0] + self.verify_output_result( + output, + swing.get_item_col(), + output.get_schema().get_field_names(), + self.expected_data) + + def test_save_load_and_transform(self): + swing = Swing().set_min_user_behavior(1) + reloaded_swing = self.save_and_reload(swing) + output = reloaded_swing.transform(self.train_data)[0] + self.verify_output_result( + output, + swing.get_item_col(), + output.get_schema().get_field_names(), + self.expected_data) + + def test_data_type(self): + try: + swing = Swing().set_min_user_behavior(1) + output = swing.transform(self.wrong_type_data)[0] + self.t_env.to_data_stream(output).execute_and_collect() + except Py4JJavaError: + pass + + def test_number_format(self): Review Comment: Thanks for your advice. As you say, it cannot test if an exception was thrown. This test was attempt to check whether Error information is available and has been removed. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
