json_data=request.json
(featureGroup_name, features, datalake_source, enable_Dme, dme_host, dme_port, bucket, token, source_name,db_org)=check_featureGroup_data(json_data)
# the features are stored in string format in the db, and has to be passed as list of feature to the dme. Hence the conversion.
- features_list = features.split(", ")
+ features_list = features.split(",")
add_featuregroup(featureGroup_name, features, datalake_source, enable_Dme, PS_DB_OBJ,dme_host, dme_port, bucket, token, source_name,db_org )
if enable_Dme == True :
response= create_dme_filtered_data_job(TRAININGMGR_CONFIG_OBJ, source_name, db_org, bucket, token, features_list, featureGroup_name, dme_host, dme_port)
feature_group=[]
if result:
for res in result:
- features=res[1].split(", ")
+ features=res[1].split(",")
dict_data={
"featuregroup_name": res[0],
"features": features,