| # |
| # 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. |
| # |
| |
| """Test for the distrib_optimization example.""" |
| |
| from __future__ import absolute_import |
| |
| import logging |
| import os |
| import tempfile |
| import unittest |
| from ast import literal_eval as make_tuple |
| |
| import numpy as np |
| from mock import MagicMock |
| from mock import patch |
| |
| from apache_beam.testing.util import open_shards |
| |
| FILE_CONTENTS = 'OP01,8,12,0,12\n' \ |
| 'OP02,30,14,3,12\n' \ |
| 'OP03,25,7,3,14\n' \ |
| 'OP04,87,7,2,2\n' \ |
| 'OP05,19,1,7,10' |
| |
| EXPECTED_MAPPING = { |
| 'OP01': 'A', |
| 'OP02': 'B', |
| 'OP03': 'B', |
| 'OP04': 'C', |
| 'OP05': 'A' |
| } |
| |
| |
| class DistribOptimizationTest(unittest.TestCase): |
| |
| def create_file(self, path, contents): |
| logging.info('Creating temp file: %s', path) |
| with open(path, 'w') as f: |
| f.write(contents) |
| |
| def test_basics(self): |
| # Setup the files with expected content. |
| temp_folder = tempfile.mkdtemp() |
| self.create_file(os.path.join(temp_folder, 'input.txt'), FILE_CONTENTS) |
| |
| # Run pipeline |
| # Avoid dependency on SciPy |
| scipy_mock = MagicMock() |
| result_mock = MagicMock(x=np.ones(3)) |
| scipy_mock.optimize.minimize = MagicMock(return_value=result_mock) |
| modules = { |
| 'scipy': scipy_mock, |
| 'scipy.optimize': scipy_mock.optimize |
| } |
| |
| with patch.dict('sys.modules', modules): |
| from apache_beam.examples.complete import distribopt |
| distribopt.run( |
| ['--input=%s/input.txt' % temp_folder, |
| '--output', os.path.join(temp_folder, 'result')], |
| save_main_session=False) |
| |
| # Load result file and compare. |
| with open_shards(os.path.join(temp_folder, 'result-*-of-*')) as result_file: |
| lines = result_file.readlines() |
| |
| # Only 1 result |
| self.assertEqual(len(lines), 1) |
| |
| # parse result line and verify optimum |
| optimum = make_tuple(lines[0]) |
| self.assertAlmostEqual(optimum['cost'], 454.39597, places=3) |
| self.assertDictEqual(optimum['mapping'], EXPECTED_MAPPING) |
| production = optimum['production'] |
| for plant in ['A', 'B', 'C']: |
| np.testing.assert_almost_equal(production[plant], np.ones(3)) |
| |
| |
| if __name__ == '__main__': |
| logging.getLogger().setLevel(logging.INFO) |
| unittest.main() |