NLTK code for sentiments analysis

python/AnalyseNLTKBySentences.py

@@ -0,0 +1,36 @@
+from flask import request
+from flask import Flask, jsonify
+from nltk.sentiment.vader import SentimentIntensityAnalyzer
+
+app = Flask(__name__)
+
+'''array = '{"sentences": ["apple", "banana", "orange"]}'''
+
+@app.route('/sentiments', methods=['POST'])
+def create_task():  
+    tasks = []      
+    for sentence in request.json['sentences']  :
+      sid = SentimentIntensityAnalyzer()    
+      polarity ="none"
+      ss = sid.polarity_scores(sentence)
+      sent=max(ss['neg'],ss['pos'],ss['neu'])
+
+      if sent==ss['neg']:      
+        polarity ="negative";
+
+      elif sent==ss['pos']:      
+         polarity ="positive";
+
+      else  :     
+        polarity ="neutral";  
+
+      task = {'sentence': sentence,'polarity':polarity }
+
+
+
+
+      tasks.append(task)
+    return jsonify({'tasks': tasks}), 200
+
+if __name__ == '__main__':
+    app.run(debug=True)   

python/desktop.py

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+from nltk.sentiment.vader import SentimentIntensityAnalyzer
+from flask import Flask
+
+app = Flask(__name__)
+
+@app.route('/<content>')
+def getAnalyseByNltk( content ):
+ sid = SentimentIntensityAnalyzer()
+
+
+ ss = sid.polarity_scores(content)
+ sent=max(ss['neg'],ss['pos'],ss['neu'])
+
+ if sent==ss['neg']:      
+  return "negative";
+
+ elif sent==ss['pos']:      
+  return "positive";
+
+ else  :     
+  return "neutral"; 
+
+
+'''@app.route('/<user_id>/<username>')
+def show(user_id, username='Anonymous'):
+    return user_id + ':' + username'''
+# Now you can call getAnalyseByNltk function
+#getAnalyseByNltk(content="I want to travel")
+
+
+if __name__ == '__main__':
+    app.run(debug=True,port=8000)
+
+