Optimized text cleanup and function parameters

Main.py

@@ -93,7 +93,7 @@ axes[1].tick_params(which='minor', length=0)
 plotFileUrl = f'./plots/{TodayDate}.png'
 plt.savefig(plotFileUrl)
 
-"""
-media = mastodonInstance.media_post(plotFileUrl, mime_type="image/png", description=f"Sentiment analysis of local timeline on fedihum.org, showing the moods of the toots on, and the compounds up to {TodayDate}.")
+
+media = mastodonInstance.media_post(plotFileUrl, mime_type="image/png", description=f"Sentiment analysis of local timeline on fedihum.org, showing the moods of the toots on, and the sentiment mean up to {TodayDate}.")
 mastodonInstance.status_post(f'The moods of the toots on and up to {TodayDate}.', media_ids=media, language='en')
-"""
+

SentiTooter.py

@@ -28,14 +28,14 @@ class SentiTooter:
         self.labels = ['negative', 'neutral', 'positive']
         self.sia = SentimentIntensityAnalyzer()
 
-    def analyze(self, toot):
-        match toot.language:
+    def analyze(self, language, content):
+        match language:
             case 'de':
-                sentiment = self.deModel.predict_sentiment([toot.content])
+                sentiment = self.deModel.predict_sentiment([content])
                 sentiment.append('germanSentiment')
                 return sentiment
             case 'en':
-                text = preprocess(toot.content)
+                text = preprocess(content)
                 encoded_input = self.enTokenizer(text, return_tensors='pt')
                 output = self.enModel(**encoded_input)
                 scores = output[0][0].detach().numpy()
@@ -45,7 +45,7 @@ class SentiTooter:
                 sentiment = [sentimentLabel, 'twitter-roberta-base-sentiment']
                 return sentiment
             case _:
-                compound = self.sia.polarity_scores(toot.content)['compound']
+                compound = self.sia.polarity_scores(content)['compound']
                 if compound > (1 / 3):
                     return ['positive', 'vaderSentiment']
                 elif compound < (-1 / 3):

TootCrawler.py

@@ -31,18 +31,18 @@ class TootCrawler():
             timelinePagination = self.mastodonInstance.fetch_previous(timelinePagination)
         for i in allTimelineResults:
             content = self.cleanhtml(i.content)
-            sentiment = self.sentiTooter.analyze(i)
-            toots.append(
-                    {
+            language = detect(content)
+            sentiment = self.sentiTooter.analyze(language, content)
+            toot = {
                 "sentiment": sentiment[0],
                 "model": sentiment[1],
-                            "userName": i.account.display_name,
-                            "userId": i.account.id,
                 "toot": content,
                 "datetime": i.created_at.astimezone(self.localTimezone),
-                            "language": detect(content),
+                "language": language,
+                "userName": i.account.display_name,
+                "userId": i.account.id,
                 "tootId": i.id
             }
-                )
+            toots.append(toot)
         toots.sort(key=lambda item:item.get('datetime'))
         return pd.DataFrame.from_records(toots)