catch exceptions from scrapper
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@ -14,6 +14,7 @@ def sentiment_prediction(data):
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def clear_data(data):
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def clear_data(data):
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data = [re.sub(r"[^A-Za-zżźćńółęąśŻŹĆĄŚĘŁÓŃ ']+", r"", i) for i in data['sentences']]
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data = [re.sub(r"[^A-Za-zżźćńółęąśŻŹĆĄŚĘŁÓŃ ']+", r"", i) for i in data['sentences']]
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data = [x for x in data if x != '']
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data = [i.strip() for i in data]
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data = [i.strip() for i in data]
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data = [i.lower() for i in data]
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data = [i.lower() for i in data]
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return data
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return data
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@ -46,5 +47,5 @@ def scrapp_comments(url):
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for comment in post['comments_full']:
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for comment in post['comments_full']:
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comments.append(comment['comment_text'])
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comments.append(comment['comment_text'])
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all['post'] = text_post
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all['post'] = text_post
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all['comments'] = comments
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all['sentences'] = comments
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return all
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return all
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@ -10,7 +10,8 @@ sentiment_service = Blueprint("sentiment_service", __name__)
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@sentiment_service.route("/get_sentiment_data", methods=['POST'])
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@sentiment_service.route("/get_sentiment_data", methods=['POST'])
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def get_data():
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def get_data():
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data = request.get_json()
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data = request.get_json()
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data_clear = clear_data(data) #czyszczenie danych wejsciowych
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data_clear = clear_data(data)
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print(data_clear) #czyszczenie danych wejsciowych
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predicitons = sentiment_prediction(data_clear) #predykcje
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predicitons = sentiment_prediction(data_clear) #predykcje
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count_labels = count_predictions(predicitons) #dane do wykresu
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count_labels = count_predictions(predicitons) #dane do wykresu
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@ -23,6 +24,10 @@ def get_data():
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@sentiment_service.route("/scrapp_comments", methods=['POST'])
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@sentiment_service.route("/scrapp_comments", methods=['POST'])
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def scrapp():
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def scrapp():
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url = request.get_json()
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try:
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result = scrapp_comments(url['link'])
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url = request.get_json()
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return result
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result = scrapp_comments(url['link'])
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result['status'] = True
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return result
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except:
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return jsonify({'status':False})
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