| # |
| # 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. |
| # |
| # pytype: skip-file |
| |
| """Unit tests for Google Cloud Natural Language API transform.""" |
| |
| import unittest |
| |
| import mock |
| |
| import apache_beam as beam |
| from apache_beam.metrics import MetricsFilter |
| from apache_beam.testing.test_pipeline import TestPipeline |
| |
| # Protect against environments where Google Cloud Natural Language client |
| # is not available. |
| # pylint: disable=wrong-import-order, wrong-import-position, ungrouped-imports |
| try: |
| from google.cloud import language |
| except ImportError: |
| language = None |
| else: |
| from apache_beam.ml.gcp import naturallanguageml |
| # pylint: enable=wrong-import-order, wrong-import-position, ungrouped-imports |
| |
| |
| @unittest.skipIf(language is None, 'GCP dependencies are not installed') |
| class NaturalLanguageMlTest(unittest.TestCase): |
| def assertCounterEqual(self, pipeline_result, counter_name, expected): |
| metrics = pipeline_result.metrics().query( |
| MetricsFilter().with_name(counter_name)) |
| try: |
| counter = metrics['counters'][0] |
| self.assertEqual(expected, counter.result) |
| except IndexError: |
| raise AssertionError('Counter "{}" was not found'.format(counter_name)) |
| |
| def test_document_source(self): |
| document = naturallanguageml.Document('Hello, world!') |
| dict_ = naturallanguageml.Document.to_dict(document) |
| self.assertTrue('content' in dict_) |
| self.assertFalse('gcs_content_uri' in dict_) |
| |
| document = naturallanguageml.Document('gs://sample/location', from_gcs=True) |
| dict_ = naturallanguageml.Document.to_dict(document) |
| self.assertFalse('content' in dict_) |
| self.assertTrue('gcs_content_uri' in dict_) |
| |
| def test_annotate_test_called(self): |
| with mock.patch('apache_beam.ml.gcp.naturallanguageml._AnnotateTextFn' |
| '._get_api_client'): |
| p = TestPipeline() |
| features = [ |
| naturallanguageml.types.AnnotateTextRequest.Features( |
| extract_syntax=True) |
| ] |
| _ = ( |
| p | beam.Create([naturallanguageml.Document('Hello, world!')]) |
| | naturallanguageml.AnnotateText(features)) |
| result = p.run() |
| result.wait_until_finish() |
| self.assertCounterEqual(result, 'api_calls', 1) |
| |
| |
| if __name__ == '__main__': |
| unittest.main() |