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')