made runnable

textclassifier/TextClassifier.py

@@ -66,7 +66,7 @@ class TextClassifier:
         """
         df_sentiment = self.ts.scrape_by_user(user_name)
         df_sentiment['sentiment'] = df_sentiment['tweet'].apply(self.classify_sentiment)
-        self.df = df_sentiment
+        return df_sentiment
 
     def analyze_sentiment(self, text: str, sentiment: str):
         """
@@ -142,14 +142,11 @@ class TextClassifier:
         """
 
     def __repr__(self):
-        if self.df is None:
-            return "No dataframe available."
-        else:
-            return self.df.to_string()
+        return "TwitterScraper(from_date={}, to_date={}, num_tweets={})".format(self.from_date, self.to_date, self.num_tweets)
 
 
 if __name__ == "__main__":
     tc = TextClassifier(model_name="text-davinci-002", from_date='2022-01-01', to_date=str(date.today()), num_tweets=20)
     print(tc)
-    tc.classify_sentiment_of_tweets("jimmieakesson")
-    print(tc)
+    df = tc.classify_sentiment_of_tweets("jimmieakesson")
+    print(df)