====== Get Product Trend Solr ====== 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. ===== Host ===== http://pci01.picalike.corpex-kunden.de:8001/get_product_trends ===== Git ===== https://git.picalike.corpex-kunden.de/picalike/get-product-trends-solr ===== DB source ===== 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} ] } === Input === * shop_id: string * * i: prod_id = False # If given, the app only returns the trend score of the given prod_id * * ignore_not_available: boolean = True * picalike_cat: string = None # if picalike_cat name given, only returns prods from this picalike_cat * prod_type: string = None * limit: int = 10 * price_from: int = None * price_till: int = None * gender: string = False * size: string or int = None * r: boolean = False # r=1 or r=False for not returning the prod_ref * shop_cat: string = None * format: json or csv –> Default: json ==== TODO ==== Adjust MongoDB Adress if API runs on different server than frontend05-hpc, currently uses ip adress instead of an url