With shop_id as mandatory filter and other optional filters as input, returns most trendy prod_ids from the prod_id's shop category. The app is mostly used by visualytics for dashboard purposes and by the solr updater from the pipeline.
The application runs with Flask dockerized in a container. It uses the zookeeper client for the solr connection.
reads from: Live Solr
returns picalike ids with highest trend score based on the given filters
This is how a response looks like:
{ "count": count, "description":"Attribute Trends", "link":"http://picalike.com", "generator":"http://picalike.com", "title":"picalike Request", "modified":str(datetime.datetime.now()), "ids": [ {"name":_name, "shop_cat":_shop_cat, "img":_img, "gender":_gender, "price":_price, "extraimg":_extraimg, "location":_location, "id":_picalike_id, "picalike_cat":_picalike_cat, "w":_cluster_trend, "prod_id":_prod_id, "prod_type": _prod_type, "available": _available, "attributes": _attributes, "keywords": _keywords} ] }
Adjust MongoDB Adress if API runs on different server than frontend05-hpc, currently uses ip adress instead of an url