data-maker/pipeline.py

#!/usr/bin/env python3
		SQL = SQL.replace(':dataset',args['dataset']) #+ " LIMIT 1000 "
		_args['gpu'] = args['gpu'] if 'gpu' in args else 0

				#	In case we want slow-mode, we can store the partitions in mongodb and process (Yes|No)?
				#
				
		# _args['num_gpu'] = int(args['num_gpu']) if 'num_gpu' in args else 1 
			_args['data'][name] = _dc[name]
			channel.connection.close()
		info = json.loads(stream)
		logger = factory.instance(type='mongo.MongoWriter',args={'dbname':'aou','doc':SYS_ARGS['context']})
		
		#
		# This will start a worker just in case to listen to a queue