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)