def enrich_tweet(self, scrap): """Function that calls all tweet fetchers """ self._fetch_counters(scrap) self._remove_punctuations() self._fetch_text(scrap) self._fetch_hashtags(scrap) self._fetch_date(scrap, False) self._fetch_username(scrap) self._fetch_tweet_id(scrap) self._sentiment = TwitterClient().get_sentiment(self.text)
if args.train: print("Forcing the model to retrain") model = train(args.eval) else: try: model = joblib.load(model_filename) except: model = train(args.eval) cv = model['vec'] clf = model['clf'] if args.tweets_file is not None: with open(args.tweets_file, 'r') as f: tweets = f.read().split('\n') df = pd.DataFrame(tweets, columns=['text']) else: client = TwitterClient() tweets = client.get_tweets(query=args.query, count=200) df = pd.DataFrame(tweets) tc = TextCleaner() cleaned_text = tc.fit_transform(df.text) counts = cv.transform(cleaned_text) preds = clf.predict(counts) for text, pred in zip(df.text, preds): print("\nSentiment: %s. Tweet: %s" % (pred, text))
from testserver import Server # se server.py import logging LOG_FILE = 'kwitter.log' logging.basicConfig(filename=LOG_FILE, level=logging.DEBUG) if __name__ == '__main__': # Ladda in tweets att testa, från fil with open("test_tweets.txt", "r") as source_tweets: tweets = source_tweets.readlines() # Samt felmeddelande with open("test_errormsg.txt", "r") as error_source: error_msg = error_source.readlines() title = "Kwitter" # Fönstertitel client = TwitterClient() # Testverktyget try: # Försök starta Firefox + ladda sidan server = Server() client.get_url(server.port) client.assert_connection(title) try: msg = "Startar testning" logging.info(msg) print(msg) client.test_tweets(tweets, error_msg[0]) client.test_checkboxes() client.test_refresh()