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Add snippets and tests for language tutorial. [(#729)](#729)
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gguuss authored and busunkim96 committed Sep 29, 2020
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20 changes: 20 additions & 0 deletions language/snippets/tutorial/README.rst.in
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# This file is used to generate README.rst

product:
name: Google Cloud Natural Language Tutorial
short_name: Cloud Natural Language Tutorial
url: https://cloud.google.com/natural-language/docs/
description: >
The `Google Cloud Natural Language API`_ provides natural language
understanding technologies to developers, including sentiment analysis,
entity recognition, and syntax analysis. This API is part of the larger
Cloud Machine Learning API.

setup:
- auth
- install_deps

samples:
- name: Language tutorial
file: tutorial.py
show_help: true
1 change: 1 addition & 0 deletions language/snippets/tutorial/requirements.txt
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google-api-python-client==1.5.5
19 changes: 19 additions & 0 deletions language/snippets/tutorial/reviews/bladerunner-mixed.txt
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I really wanted to love 'Bladerunner' but ultimately I couldn't get
myself to appreciate it fully. However, you may like it if you're into
science fiction, especially if you're interested in the philosophical
exploration of what it means to be human or machine. Some of the gizmos
like the flying cars and the Vouight-Kampff machine (which seemed very
steampunk), were quite cool.

I did find the plot pretty slow and but the dialogue and action sequences
were good. Unlike most science fiction films, this one was mostly quiet, and
not all that much happened, except during the last 15 minutes. I didn't
understand why a unicorn was in the movie. The visual effects were fantastic,
however, and the musical score and overall mood was quite interesting.
A futurist Los Angeles that was both highly polished and also falling apart
reminded me of 'Outland.' Certainly, the style of the film made up for
many of its pedantic plot holes.

If you want your sci-fi to be lasers and spaceships, 'Bladerunner' may
disappoint you. But if you want it to make you think, this movie may
be worth the money.
3 changes: 3 additions & 0 deletions language/snippets/tutorial/reviews/bladerunner-neg.txt
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What was Hollywood thinking with this movie! I hated,
hated, hated it. BORING! I went afterwards and demanded my money back.
They refused.
2 changes: 2 additions & 0 deletions language/snippets/tutorial/reviews/bladerunner-neutral.txt
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I neither liked nor disliked this movie. Parts were interesting, but
overall I was left wanting more. The acting was pretty good.
10 changes: 10 additions & 0 deletions language/snippets/tutorial/reviews/bladerunner-pos.txt
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`Bladerunner` is often touted as one of the best science fiction films ever
made. Indeed, it satisfies many of the requisites for good sci-fi: a future
world with flying cars and humanoid robots attempting to rebel against their
creators. But more than anything, `Bladerunner` is a fantastic exploration
of the nature of what it means to be human. If we create robots which can
think, will they become human? And if they do, what makes us unique? Indeed,
how can we be sure we're not human in any case? `Bladerunner` explored
these issues before such movies as `The Matrix,' and did so intelligently.
The visual effects and score by Vangelis set the mood. See this movie
in a dark theatre to appreciate it fully. Highly recommended!
71 changes: 71 additions & 0 deletions language/snippets/tutorial/tutorial.py
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#!/usr/bin/env python

# 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.
# [START full_tutorial_script]
# [START import_libraries]
import argparse
import io

from googleapiclient import discovery
from oauth2client.client import GoogleCredentials
# [END import_libraries]


def print_sentiment(filename):
"""Prints sentiment analysis on a given file contents."""
# [START authenticating_to_the_api]
credentials = GoogleCredentials.get_application_default()
service = discovery.build('language', 'v1', credentials=credentials)
# [END authenticating_to_the_api]

# [START constructing_the_request]
with io.open(filename, 'r') as review_file:
review_file_contents = review_file.read()

service_request = service.documents().analyzeSentiment(
body={
'document': {
'type': 'PLAIN_TEXT',
'content': review_file_contents,
}
}
)
response = service_request.execute()
# [END constructing_the_request]

# [START parsing_the_response]
score = response['documentSentiment']['score']
magnitude = response['documentSentiment']['magnitude']

for n, sentence in enumerate(response['sentences']):
sentence_sentiment = sentence['sentiment']['score']
print('Sentence {} has a sentiment score of {}'.format(n,
sentence_sentiment))

print('Overall Sentiment: score of {} with magnitude of {}'.format(
score, magnitude))
# [END parsing_the_response]


# [START running_your_application]
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'movie_review_filename',
help='The filename of the movie review you\'d like to analyze.')
args = parser.parse_args()
print_sentiment(args.movie_review_filename)
# [END running_your_application]
# [END full_tutorial_script]
51 changes: 51 additions & 0 deletions language/snippets/tutorial/tutorial_test.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 re

import tutorial


def test_neutral(capsys):
tutorial.print_sentiment('reviews/bladerunner-neutral.txt')
out, _ = capsys.readouterr()
assert re.search(r'Sentence \d has a sentiment score of \d', out, re.I)
assert re.search(
r'Overall Sentiment: score of -?[0-2]\.?[0-9]? with '
r'magnitude of [0-1]\.?[0-9]?', out, re.I)


def test_pos(capsys):
tutorial.print_sentiment('reviews/bladerunner-pos.txt')
out, _ = capsys.readouterr()
assert re.search(r'Sentence \d has a sentiment score of \d', out, re.I)
assert re.search(
r'Overall Sentiment: score of [0-9]\.?[0-9]? with '
r'magnitude of [0-9]\.?[0-9]?', out, re.I)


def test_neg(capsys):
tutorial.print_sentiment('reviews/bladerunner-neg.txt')
out, _ = capsys.readouterr()
assert re.search(r'Sentence \d has a sentiment score of \d', out, re.I)
assert re.search(
r'Overall Sentiment: score of -[0-9]\.?[0-9]? with '
r'magnitude of [2-7]\.?[0-9]?', out, re.I)


def test_mixed(capsys):
tutorial.print_sentiment('reviews/bladerunner-mixed.txt')
out, _ = capsys.readouterr()
assert re.search(r'Sentence \d has a sentiment score of \d', out, re.I)
assert re.search(
r'Overall Sentiment: score of -?[0-9]\.?[0-9]? with '
r'magnitude of [3-6]\.?[0-9]?', out, re.I)

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