Used newspaper

modules/headline.py

@@ -1,28 +1,18 @@
-import urllib.request
-from bs4 import BeautifulSoup
 from textblob.classifiers import NaiveBayesClassifier
 from textblob import TextBlob
+import newspaper
 
 class title:
 
     #Initialisations
     def __init__(self): 
         self.news_url="https://edition.cnn.com/2019/08/25/politics/trump-g7-boris-johnson-emmanuel-macron/index.html"
 
-
     def extract_headline(self):
-        self.net_con=True #Expecting Internet Connection to be working initially
-        try:
-            news_page=urllib.request.urlopen(self.news_url)   
-            soup = BeautifulSoup(news_page,'html.parser')
-            headline_in_html=soup.find('h1')
-            headline=headline_in_html.text.strip()
-            return headline
-
-        except urllib.error.URLError:
-            print("\nCONNECTIION ERROR:There may be a connection problem. Please check if the device is connected to the Internet")
-            self.net_con=False #Value update if the program is unable to connenct
-
+        article = newspaper.Article(self.news_url)
+        article.download()
+        article.parse()
+        return article.title.strip()
 
     #Adding Training Data
     def train_data(self, headline):
@@ -33,10 +23,7 @@ def train_data(self, headline):
                 return sentiment
 
         except:
-            if self.net_con==False:
-                pass
-            else:
-                print("\n\nProgram Error")
+            print("\n\n Connection/Program Error")
 
 
     def headline_category(self,headline,sentiment):