| # |
| # 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. |
| # |
| |
| """Integration tests for Google Cloud Video Intelligence API transforms.""" |
| |
| from __future__ import absolute_import |
| |
| import logging |
| import unittest |
| |
| from nose.plugins.attrib import attr |
| |
| import apache_beam as beam |
| from apache_beam.testing.test_pipeline import TestPipeline |
| from apache_beam.testing.util import assert_that |
| from apache_beam.testing.util import equal_to |
| |
| # Protect against environments with google-cloud-dlp unavailable. |
| # pylint: disable=wrong-import-order, wrong-import-position, ungrouped-imports |
| try: |
| from google.cloud import dlp_v2 |
| except ImportError: |
| dlp_v2 = None |
| else: |
| from apache_beam.ml.gcp.cloud_dlp import InspectForDetails |
| from apache_beam.ml.gcp.cloud_dlp import MaskDetectedDetails |
| # pylint: enable=wrong-import-order, wrong-import-position, ungrouped-imports |
| |
| _LOGGER = logging.getLogger(__name__) |
| |
| INSPECT_CONFIG = {"info_types": [{"name": "EMAIL_ADDRESS"}]} |
| |
| DEIDENTIFY_CONFIG = { |
| "info_type_transformations": { |
| "transformations": [{ |
| "primitive_transformation": { |
| "character_mask_config": { |
| "masking_character": '#' |
| } |
| } |
| }] |
| } |
| } |
| |
| |
| def extract_inspection_results(response): |
| yield beam.pvalue.TaggedOutput('info_type', response[0].info_type.name) |
| |
| |
| @unittest.skipIf(dlp_v2 is None, 'GCP dependencies are not installed') |
| class CloudDLPIT(unittest.TestCase): |
| def setUp(self): |
| self.test_pipeline = TestPipeline(is_integration_test=True) |
| self.runner_name = type(self.test_pipeline.runner).__name__ |
| self.project = self.test_pipeline.get_option('project') |
| |
| @attr("IT") |
| def test_deidentification(self): |
| with TestPipeline(is_integration_test=True) as p: |
| output = ( |
| p | beam.Create(["mary.sue@example.com"]) |
| | MaskDetectedDetails( |
| project=self.project, |
| deidentification_config=DEIDENTIFY_CONFIG, |
| inspection_config=INSPECT_CONFIG)) |
| assert_that(output, equal_to(['####################'])) |
| |
| @attr("IT") |
| def test_inspection(self): |
| with TestPipeline(is_integration_test=True) as p: |
| output = ( |
| p | beam.Create(["mary.sue@example.com"]) |
| | InspectForDetails( |
| project=self.project, inspection_config=INSPECT_CONFIG) |
| | beam.ParDo(extract_inspection_results).with_outputs( |
| 'quote', 'info_type')) |
| assert_that(output.info_type, equal_to(['EMAIL_ADDRESS']), 'Type matches') |
| |
| |
| if __name__ == '__main__': |
| logging.getLogger().setLevel(logging.WARN) |
| unittest.main() |