def runLiveSentimentAnalysis(keyword, maxTweets=300, maxTime=0, backup=10):
maxTweets = int(maxTweets)
maxTime = int(maxTime)
backup = int(backup)
Creds = loadCreds()
CONSUMER_KEY = Creds['CONSUMER_KEY']
CONSUMER_SECRET = Creds['CONSUMER_SECRET']
OAUTH_TOKEN = Creds['OAUTH_TOKEN']
OAUTH_TOKEN_SECRET = Creds['OAUTH_TOKEN_SECRET']
auth = OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(OAUTH_TOKEN, OAUTH_TOKEN_SECRET)
api = API(auth,
wait_on_rate_limit=True,
wait_on_rate_limit_notify=True,
retry_count=10,
retry_delay=5,
retry_errors=5)
twitterStream = Stream(auth=api.auth,
listener=listener(count, maxTweets, maxTime,
backup))
twitterStream.filter(track=[keyword])
if settings["datalog"] == True:
writeToFile(tweetJSON, 'live-sentiment')
while plt.fignum_exists(1):
plt.show()
plt.pause(0.0001)
return tweetJSON
import tweepy #The Twitter API
from time import sleep
from datetime import datetime
from textblob import TextBlob #For Sentiment Analysis
import matplotlib.pyplot as plt #For Graphing the Data
from settingHandler import loadSettings
from writeFile import writeToFile
from loadCreds import loadCreds
Creds = loadCreds()
CONSUMER_KEY = Creds['CONSUMER_KEY']
CONSUMER_SECRET = Creds['CONSUMER_SECRET']
OAUTH_TOKEN = Creds['OAUTH_TOKEN']
OAUTH_TOKEN_SECRET = Creds['OAUTH_TOKEN_SECRET']
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(OAUTH_TOKEN, OAUTH_TOKEN_SECRET)
api = tweepy.API(auth)
def runSentimentAnalysis(keyword, tweetNumber=100, backup=10):
if backup == '0':
backup = '1'
tweetNumber = int(tweetNumber)
polarity_list = []
numbers_list = []
number = 1
settings = loadSettings()
tweetJSON = {}