feat: created python app. pending refresh

EmotionDetection/__init__.py

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+from . import emotion_detection

EmotionDetection/emotion_detection.py

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+import requests
+import json
+
+def emotion_detector(text_to_analyze):
+    url = 'https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict'
+    header = {"grpc-metadata-mm-model-id": "emotion_aggregated-workflow_lang_en_stock"}
+    myobj = { "raw_document": { "text": text_to_analyze } }
+    response = requests.post(url, json = myobj, headers=header)
+    formatted_response = json.loads(response.text)
+
+
+    if  response.status_code == 200:
+        emotions = formatted_response['emotionPredictions'][0]['emotion']
+        anger = emotions['anger']
+        disgust = emotions['disgust']
+        fear = emotions['fear']
+        joy = emotions['joy']
+        sadness = emotions['sadness']
+        dominant_emotion = max(emotions, key=emotions.get)
+    elif response.status_code == 400:
+        anger = None
+        disgust = None
+        fear = None
+        joy = None
+        sadness = None
+        dominant_emotion = None
+    elif response.status_code == 500:
+        anger = None
+        disgust = None
+        fear = None
+        joy = None
+        sadness = None
+        dominant_emotion = None    
+
+    return {'anger': anger, 'disgust': disgust, 'fear': fear, 'joy': joy, 'sadness': sadness, 'dominant_emotion': dominant_emotion}
+
+

server.py

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+""" imports flask and other methods"""
+from flask import Flask, render_template, request
+from EmotionDetection.emotion_detection import emotion_detector
+
+app = Flask("Emotion Detector")
+
+@app.route("/emotionDetector")
+def sent_detector():
+    """generate a response message given input"""
+
+    text_to_analyze = request.args.get('textToAnalyze')
+    response = emotion_detector(text_to_analyze)
+
+    anger = response['anger']
+    disgust = response['disgust']
+    fear = response['fear']
+    joy = response['joy']
+    sadness = response['sadness']
+    dominant_emotion = response['dominant_emotion']
+
+    if dominant_emotion is None:
+        return "Invalid text! Please try again!"
+    return "For the given statement, the system response is 'anger': {}, 'disgust': {}, 'fear': {}, 'joy': {}, and 'sadness': {}. The dominant emotion is {}.".format(anger, disgust, fear, joy, sadness, dominant_emotion) # pylint: disable=line-too-long # pylint: disable=consider-using-f-string
+
+
+@app.route("/")
+def render_index_page():
+    """render page"""
+    return render_template('index.html')
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=5000)
+

test_emotion_detection.py

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+from EmotionDetection.emotion_detection import emotion_detector
+import unittest
+
+class TestEmotionDetector(unittest.TestCase):
+    def test_emotion_detector(self):
+        result_1 = emotion_detector('I am glad this happened')
+        self.assertEqual(result_1['dominant_emotion'], 'joy')
+
+        result_2 = emotion_detector('I am really mad about this')
+        self.assertEqual(result_2['dominant_emotion'], 'anger')
+
+        result_3 = emotion_detector('I feel disgusted just hearing about this')
+        self.assertEqual(result_3['dominant_emotion'], 'disgust')
+
+        result_4 = emotion_detector('I am so sad about this')
+        self.assertEqual(result_4['dominant_emotion'], 'sadness')
+
+        result_5 = emotion_detector('I am really afraid that this will happen')
+        self.assertEqual(result_5['dominant_emotion'], 'fear')
+
+        result_6 = emotion_detector(' ')
+        self.assertEqual(result_6['dominant_emotion'], None)
+
+unittest.main()