import sentiment_analysis as sentiment
import connections
import boto.sqs
if __name__ == "__main__":
# connect to mysql database
db_conn, db_cur = connections.connect_to_mysql()
# connect to Amazon sqs
queue_name = "TwitterMap_gp_2"
sqs_queue = connections.connect_to_sqs(queue_name)
# sqs_queue = conn_sqs.get_queue(queue_name)
# connect to the sns
conn_sns, topic_arn = connections.connect_to_sns()
# sentiment_analysis module performs the following
# 1. Reads messages from the SQS queue and performs sentiment_analysis and updates the mysql with sentiment score
# 2. Upon successful update to mysql, inserts a notification into Amazon SNS which will later be consumed by the front end
sentiment.sentiment_main(sqs_queue, db_conn, db_cur, conn_sns, topic_arn)
import temp as sentiment import connections if __name__ == '__main__': #connect to mysql database db_conn,db_cur = connections.connect_to_mysql() #connect to Amazon sqs sqs_queue = connections.connect_to_sqs() #sentiment_analysis module performs the following # 1. Reads messages from the SQS queue and performs sentiment_analysis and updates the mysql with sentiment score # 2. Upon successful update to mysql, inserts a notification into Amazon SNS which will later be consumed by the front end sentiment.process_msg(sqs_queue,db_conn,db_cur)