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()
