import socket, pickle, sys
from processdata import ProcessData
if len(sys.argv) != 3:
print ("Correct usage: script, IP address, port number",flush = True)
exit(0)
IP_address = str(sys.argv[1])
Port = int(sys.argv[2])
# Create a socket connection.
s = socket.socket(socket.AF_INET6, socket.SOCK_STREAM)
s.connect((IP_address, Port))
# Create an instance of ProcessData() to send to server.
variable = ProcessData()
# Pickle the object and send it to the server
data_string = pickle.dumps(variable)
s.send(data_string)
s.close()
print ('Data Sent to Server')
tweet_user = sys.argv[4]
logger.info("Extracting tweet data")
if not os.path.exists('{}/tweetdata/output/{}.csv'.format(
os.getcwd(), tweet_user)):
scrape_web = ScrapeWeb(user="******".format(tweet_user),
start_date=start_date,
end_date=end_date,
logger_name=logger_name)
scrape_web.get_tweets()
# Get tweet data for tweet_user
meta_data = GetMetaData(user="******".format(tweet_user),
logger_name=logger_name)
meta_data.get_metadata()
logger.info("Processing the stock and tweet data")
# Process retrieved data
process_data = ProcessData(ticker_list=ticker_list,
logger_name=logger_name)
processed_df_stock = process_data.process_data_stock(
'{}/stockdata/output/{}'.format(os.getcwd(), sys.argv[1]))
processed_df_tweet = process_data.process_data_tweet(
'{}/tweetdata/output/{}.csv'.format(os.getcwd(), sys.argv[4]))
logger.info("Performing sentiment analysis")
sa = SentimentAnalysis(csv_file='{}/tweetdata/output/{}.csv'.format(
os.getcwd(), sys.argv[4]),
logger_name=logger_name)
sa.plot(['favorite_count', 'retweet_count'])
logger.info("Plotting stock and tweet data")
for ticker in ticker_list:
filtered_df = process_data.filter_tweet(processed_df_tweet, ticker)
# Plot processed data
plot_data = Plots(logger_name=logger_name)
# plot_data.candlestick_stock_plot(processed_df_stock, 'AMZN')
