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Commit 31aeffb

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beccasaurusbeccasaurus
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Add small, generated version of language_sentiment_text (GoogleCloudPlatform#1660)
* Generated sample: language_sentiment_text FYI generated from the following YAML GAPIC config: sample_value_sets: - id: analyze_sentiment title: "Analyzing Sentiment" description: "Proof of concept for analyzing sentiment" parameters: defaults: - document.type=PLAIN_TEXT - document.content="Your text to analyze, e.g. Hello, world!" attributes: - parameter: document.content sample_argument: true on_success: - define: sentiment=$resp.document_sentiment - print: - "Score: %s" - sentiment.score - print: - "Magnitude: %s" - sentiment.magnitude samples: standalone: - calling_forms: ".*" value_sets: analyze_sentiment region_tag: language_sentiment_text * Add requirements.txt (not currently generated) * Add test for language_sentiment_text (not currently generated) * Move language_python_migration_document_text Move language_python_migration_document_text so it uses a different snippet in preparation for deprecation of existing language_sentiment_text sample * Rename generated snippets so filename == region tag * Fix test for generated code sample (file rename to match region tag) * Update Copyright year to 2018 in new hand-written file * Fix lint errors of #language_sentiment_text test * Regenerate #language_sentiment_text to fix lint errors (updated Python sample template) * Binary string support in samples! From PR googleapis/gapic-generator#2272
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‎language/cloud-client/v1/snippets.py

Copy file name to clipboardExpand all lines: language/cloud-client/v1/snippets.py
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@@ -39,12 +39,10 @@ def sentiment_text(text):
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text = text.decode('utf-8')
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# Instantiates a plain text document.
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# [START language_python_migration_document_text]
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# [START language_python_migration_sentiment_text]
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document = types.Document(
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content=text,
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type=enums.Document.Type.PLAIN_TEXT)
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# [END language_python_migration_document_text]
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# Detects sentiment in the document. You can also analyze HTML with:
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# document.type == enums.Document.Type.HTML
@@ -87,9 +85,11 @@ def entities_text(text):
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# Instantiates a plain text document.
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# [START language_python_migration_entities_text]
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# [START language_python_migration_document_text]
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document = types.Document(
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content=text,
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type=enums.Document.Type.PLAIN_TEXT)
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# [END language_python_migration_document_text]
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# Detects entities in the document. You can also analyze HTML with:
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# document.type == enums.Document.Type.HTML

‎language/generated-samples/v1/language_sentiment_text.py

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# -*- coding: utf-8 -*-
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#
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# Copyright 2018 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# DO NOT EDIT! This is a generated sample ("Request", "analyze_sentiment")
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# To install the latest published package dependency, execute the following:
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# pip install google-cloud-language
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import sys
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# [START language_sentiment_text]
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from google.cloud import language_v1
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from google.cloud.language_v1 import enums
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import six
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def sample_analyze_sentiment(content):
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# [START language_sentiment_text_core]
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client = language_v1.LanguageServiceClient()
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# content = 'Your text to analyze, e.g. Hello, world!'
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if isinstance(content, six.binary_type):
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content = content.decode('utf-8')
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type_ = enums.Document.Type.PLAIN_TEXT
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document = {'type': type_, 'content': content}
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response = client.analyze_sentiment(document)
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sentiment = response.document_sentiment
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print('Score: {}'.format(sentiment.score))
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print('Magnitude: {}'.format(sentiment.magnitude))
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# [END language_sentiment_text_core]
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# [END language_sentiment_text]
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def main():
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# FIXME: Convert argv from strings to the correct types.
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sample_analyze_sentiment(*sys.argv[1:])
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if __name__ == '__main__':
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main()

‎language/generated-samples/v1/language_sentiment_text_test.py

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# -*- coding: utf-8 -*-
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# Copyright 2018 Google, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import language_sentiment_text
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def test_analyze_sentiment_text_positive(capsys):
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language_sentiment_text.sample_analyze_sentiment('Happy Happy Joy Joy')
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out, _ = capsys.readouterr()
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assert 'Score: 0.' in out
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def test_analyze_sentiment_text_negative(capsys):
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language_sentiment_text.sample_analyze_sentiment('Angry Angry Sad Sad')
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out, _ = capsys.readouterr()
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assert 'Score: -0.' in out

‎language/generated-samples/v1/requirements.txt

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google-cloud-language==1.0.2

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