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language.py
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language.py
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# Copyright 2016 Google Inc.
#
# Licensed 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.
import unittest
from google.cloud import exceptions
from google.cloud import language
from google.cloud import storage
from system_test_utils import unique_resource_id
from retry import RetryErrors
class Config(object):
"""Run-time configuration to be modified at set-up.
This is a mutable stand-in to allow test set-up to modify
global state.
"""
CLIENT = None
TEST_BUCKET = None
def setUpModule():
Config.CLIENT = language.Client()
# Now create a bucket for GCS stored content.
storage_client = storage.Client()
bucket_name = 'new' + unique_resource_id()
Config.TEST_BUCKET = storage_client.bucket(bucket_name)
# 429 Too Many Requests in case API requests rate-limited.
retry_429 = RetryErrors(exceptions.TooManyRequests)
retry_429(Config.TEST_BUCKET.create)()
def tearDownModule():
# 409 Conflict if the bucket is full.
# 429 Too Many Requests in case API requests rate-limited.
bucket_retry = RetryErrors(
(exceptions.TooManyRequests, exceptions.Conflict))
bucket_retry(Config.TEST_BUCKET.delete)(force=True)
class TestLanguage(unittest.TestCase):
NAME1 = 'Michelangelo Caravaggio'
NAME2 = 'Italian'
NAME3 = 'The Calling of Saint Matthew'
TEXT_CONTENT = '%s, %s painter, is known for %r.' % (NAME1, NAME2, NAME3)
def setUp(self):
self.to_delete_by_case = []
def tearDown(self):
for value in self.to_delete_by_case:
value.delete()
def _check_analyze_entities_result(self, entities):
from google.cloud.language.entity import EntityType
self.assertEqual(len(entities), 3)
entity1, entity2, entity3 = entities
# Verify entity 1.
self.assertEqual(entity1.name, self.NAME1)
self.assertEqual(entity1.entity_type, EntityType.PERSON)
self.assertGreater(entity1.salience, 0.0)
# Other mentions may occur, e.g. "painter".
self.assertIn(entity1.name, entity1.mentions)
self.assertEqual(entity1.wikipedia_url,
'http://en.wikipedia.org/wiki/Caravaggio')
self.assertIsInstance(entity1.metadata, dict)
# Verify entity 2.
self.assertEqual(entity2.name, self.NAME2)
self.assertEqual(entity2.entity_type, EntityType.LOCATION)
self.assertGreater(entity2.salience, 0.0)
self.assertEqual(entity2.mentions, [entity2.name])
self.assertEqual(entity2.wikipedia_url,
'http://en.wikipedia.org/wiki/Italy')
self.assertIsInstance(entity2.metadata, dict)
# Verify entity 3.
self.assertEqual(entity3.name, self.NAME3)
choices = (EntityType.EVENT, EntityType.WORK_OF_ART)
self.assertIn(entity3.entity_type, choices)
self.assertGreater(entity3.salience, 0.0)
self.assertEqual(entity3.mentions, [entity3.name])
wiki_url = ('http://en.wikipedia.org/wiki/'
'The_Calling_of_St_Matthew_(Caravaggio)')
self.assertEqual(entity3.wikipedia_url, wiki_url)
self.assertIsInstance(entity3.metadata, dict)
def test_analyze_entities(self):
document = Config.CLIENT.document_from_text(self.TEXT_CONTENT)
entities = document.analyze_entities()
self._check_analyze_entities_result(entities)
def test_analyze_entities_from_blob(self):
# Upload the text to a blob.
bucket_name = Config.TEST_BUCKET.name
blob_name = 'document.txt'
blob = Config.TEST_BUCKET.blob(blob_name)
self.to_delete_by_case.append(blob) # Clean-up.
blob.upload_from_string(self.TEXT_CONTENT)
# Create a document referencing that blob.
gcs_url = 'gs://%s/%s' % (bucket_name, blob_name)
document = Config.CLIENT.document_from_url(gcs_url)
entities = document.analyze_entities()
self._check_analyze_entities_result(entities)
def test_analyze_sentiment(self):
positive_msg = 'Jogging is fun'
document = Config.CLIENT.document_from_text(positive_msg)
sentiment = document.analyze_sentiment()
self.assertEqual(sentiment.score, 0.5)
self.assertTrue(0.0 < sentiment.magnitude < 1.5)
def _verify_token(self, token, text_content, part_of_speech, lemma):
from google.cloud.language.syntax import Token
self.assertIsInstance(token, Token)
self.assertEqual(token.text_content, text_content)
self.assertEqual(token.part_of_speech, part_of_speech)
self.assertEqual(token.lemma, lemma)
def _check_analyze_syntax_result(self, tokens):
from google.cloud.language.syntax import PartOfSpeech
self.assertEqual(len(tokens), 3)
token1, token2, token3 = tokens
# Verify token 1.
self._verify_token(token1, 'Jogging', PartOfSpeech.NOUN, 'Jogging')
# Verify token 2.
self._verify_token(token2, 'is', PartOfSpeech.VERB, 'be')
# Verify token 3.
self._verify_token(token3, 'fun', PartOfSpeech.ADJECTIVE, 'fun')
def test_analyze_syntax(self):
positive_msg = 'Jogging is fun'
document = Config.CLIENT.document_from_text(positive_msg)
tokens = document.analyze_syntax()
self._check_analyze_syntax_result(tokens)