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Tweak code for importing into docs.
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language/sentiment/sentiment_analysis.py

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@@ -11,25 +11,16 @@
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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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# [START sentiment_tutorial]
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"""Demonstrates how to make a simple call to the Natural Language API."""
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# [START sentiment_tutorial_import]
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import argparse
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from google.cloud import language
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# [END sentiment_tutorial_import]
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def main(movie_review_filename):
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"""Run a sentiment analysis request on text within a passed filename."""
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language_client = language.Client()
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with open(movie_review_filename, 'r') as review_file:
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# Instantiates a plain text document.
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document = language_client.document_from_html(review_file.read())
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# Detects sentiment in the document.
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annotations = document.annotate_text(include_sentiment=True,
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include_syntax=False, include_entities=False)
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def print_result(annotations):
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score = annotations.sentiment.score
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magnitude = annotations.sentiment.magnitude
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@@ -47,6 +38,19 @@ def main(movie_review_filename):
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return 0
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def analyze(movie_review_filename):
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"""Run a sentiment analysis request on text within a passed filename."""
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language_client = language.Client()
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with open(movie_review_filename, 'r') as review_file:
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# Instantiates a plain text document.
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document = language_client.document_from_html(review_file.read())
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# Detects sentiment in the document.
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return document.annotate_text(include_sentiment=True,
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include_syntax=False, include_entities=False)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(
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description=__doc__,
@@ -55,4 +59,8 @@ def main(movie_review_filename):
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'movie_review_filename',
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help='The filename of the movie review you\'d like to analyze.')
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args = parser.parse_args()
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main(args.movie_review_filename)
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# Perform the analysis
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annotations = analyze(args.movie_review_filename)
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# Print the results
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print_result(annotations)
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# [END sentiment_tutorial]

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