analyzer sample

+import argparse
+
+from google.cloud import language_v1
+
+def print_result(annotations):
+    score = annotations.document_sentiment.score
+    magnitude = annotations.document_sentiment.magnitude
+
+    tot = 0
+    positive = 0
+    negative = 0
+    neutral = 0
+    for index, sentence in enumerate(annotations.sentences):
+        sentence_sentiment = sentence.sentiment.score
+        if sentence_sentiment > 0:
+            positive += 1
+        elif sentence_sentiment < 0:
+            negative += 1
+        else:
+            neutral += 1
+        # print(
+            # "Sentence {} has a sentiment score of {}".format(index, sentence_sentiment)
+        # )
+        tot += 1
+    print(
+        "Overall Sentiment: score of {} with magnitude of {}".format(score, magnitude)
+    )
+    return tot, positive, negative
+
+def analyze(movie_review_filename):
+    client = language_v1.LanguageServiceClient()
+
+    with open(movie_review_filename, "r", encoding='utf-8-sig') as review_file:
+        # Instantiates a plain text document.
+        content = review_file.read()
+    document = language_v1.Document(content=content, type_=language_v1.Document.Type.PLAIN_TEXT)
+    annotations = client.analyze_sentiment(request={'document': document})
+
+    print_result(annotations)
+
+if __name__ == "__main__":
+    analyze("data.txt")
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