from stocktalk import streaming, visualize
streaming(credentials, 'TSLA', ['TSLA', 'Tesla'], 30, path, realtime=True, logSentiment=True)
visualize('TSLA', 30, path)
pip install stocktalkstocktalk-corpus
or
python -m nltk.downloader vader_lexiconfrom 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
Streaming Now...
---10:00:00---
TSLA Volume: 25
TSLA Sentiment: 0.29
SNAP Volume: 218
SNAP Sentiment: 0.03
AAPL Volume: 63
AAPL Sentiment: 0.14
AMZN Volume: 64
AMZN Sentiment: 0.34
---10:00:30---
TSLA Volume: 23
TSLA Sentiment: -0.05
SNAP Volume: 298
SNAP Sentiment: 0.02
AAPL Volume: 112
AAPL Sentiment: 0.01
AMZN Volume: 150
AMZN Sentiment: 0.11
TSLA_Tracker.txt
datetime,volume,sentiment,duration
03/01/2017 10:30:00,22,0.26,30
03/01/2017 10:30:30,27,0.33,30
03/01/2017 10:31:00,24,0.23,30
03/01/2017 10:31:30,23,0.25,30
03/01/2017 10:32:00,25,0.18,30
TSLA_Tweets.txt
datetime,tweet,sentiment
03/01/2017 10:30:02,#Tesla zeroing in market with strong relations,0.54
03/01/2017 10:30:03,$TSLA needs 8 Billion for Supercharger network,0.0
03/01/2017 10:30:03,#Tesla grossing high yet still losing money,-0.32
03/01/2017 10:30:03,Tesla's soon to be as affordable as gas-powered cars,0.11
03/01/2017 10:30:05,The technical reason why Tesla shares could soon rise,0.42
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))shares jump as shipments more than double winning
tesla announces its best sales quarter
tesla reports deliveries of number above most views
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))0.706
0.077
-0.341