17-1-skku-oss / stocktalk Goto Github PK

from stocktalk import streaming, visualize

streaming(credentials, 'TSLA', ['TSLA', 'Tesla'], 30, path, realtime=True, logSentiment=True)
visualize('TSLA', 30, path)

pip install stocktalk

stocktalk-corpus
or
python -m nltk.downloader vader_lexicon

from stocktalk import streaming

# Credentials to access Twitter API 
API_KEY = 'XXXXXXXXXX'
API_SECRET = 'XXXXXXXXXX'
ACCESS_TOKEN = 'XXXXXXXXXX'
ACCESS_TOKEN_SECRET = 'XXXXXXXXXX'
credentials = [API_KEY, API_SECRET, ACCESS_TOKEN, ACCESS_TOKEN_SECRET]

# First element must be ticker/name, proceeding elements are extra queries
TSLA = ['TSLA', 'Tesla']
SNAP = ['SNAP', 'Snapchat']
AAPL = ['AAPL', 'Apple']
AMZN = ['AMZN', 'Amazon']

# Variables
tickers = [TSLA,SNAP,AAPL,AMZN]  # Used for identification purposes
queries =  TSLA+SNAP+AAPL+AMZN   # Filters tweets containing one or more query 
refresh = 30                     # Process and log data every 30 seconds

# Create a folder to collect logs and temporary files
path = "/Users/Anthony/Desktop/Data/"

streaming(credentials, tickers, queries, refresh, path, \
realtime=True, logTracker=True, logTweets=True, logSentiment=True, debug=True)

from stocktalk import visualize

# Make sure these variables are consistent with streaming.py
tickers = ['TSLA','SNAP','AAPL','AMZN']
refresh = 30
path = "/Users/Anthony/Desktop/Data/"

visualize(tickers, refresh, path)

'''
Steps to run local bokeh server
1. Make sure streaming.py is running...
2. Traverse in console to the directory containing visualize.py
3. python -m bokeh serve --show visualize.py
'''

# Note: Volume is the thick blue line while sentiment is the thin white line

textOne = "@TeslaMotors shares jump as shipments more than double! #winning"
print(process(textOne))

textTwo = "Tesla announces its best sales quarter: http://trib.al/RbTxvSu $TSLA" 
print(process(textTwo))

textThree = "Tesla $TSLA reports deliveries of 24500, above most views."
print(process(textThree))

textOne = "shares jump as shipments more than double winning"
print(sentiment(textOne))

textTwo = "tesla reports deliveries of number above most views"
print(sentiment(textTwo))

textThree = "not looking good for tesla competition on the rise"
print(sentiment(textThree))