def setUp(self): self.config = { "method": "inverted_index", "converter": { "string_filter_types": {}, "string_filter_rules": [], "num_filter_types": {}, "num_filter_rules": [], "string_types": {}, "string_rules": [{"key": "*", "type": "str", "sample_weight": "bin", "global_weight": "bin"}], "num_types": {}, "num_rules": [{"key": "*", "type": "num"}], }, "parameter": {}, } TestUtil.write_file("config_recommender.json", json.dumps(self.config)) self.srv = TestUtil.fork_process("recommender", port, "config_recommender.json") self.cli = recommender(host, port)
import calendar from jubatus.recommender.client import recommender from jubatus.recommender.types import * typhoon_client = recommender('127.0.0.1', 9199) harvest_client = recommender('127.0.0.1', 9299) method = "inverted_index" converter = """ { \"string_filter_types\" : {}, \"string_filter_rules\" : [], \"num_filter_types\" : {}, \"num_filter_rules\" : [], \"string_types\" : {}, \"string_rules\" : [], \"num_types\" : {}, \"num_rules\" : [ { \"key\" : \"*\", \"type\" : \"num\" } ] } """ config = config_data(method, converter) # train -- typhoon typhoon_client.set_config('', config) typhoon_years = []
#!/usr/bin/env python # -*- coding: utf-8 -*- import sys from jubatus.recommender import client from jubatus.recommender import types if __name__ == '__main__': recommender = client.recommender("127.0.0.1",9199) for i in range(0,943): sr = recommender.similar_row_from_id("movie_len", str(i) , 10); print "user ", str(i), " is similar to :", sr
#!/usr/bin/python # -*- coding: utf-8 -*- import sys from jubatus.recommender import client from jubatus.recommender import types import MySQLdb if __name__ == "__main__": recommender = client.recommender("localhost",9199) # Analyze connector = MySQLdb.connect(host="localhost",db="jubatus_sample",user="******",passwd="") cursor = connector.cursor() cursor.execute("select * from plus_info_1") result = cursor.fetchall() list = [] for row in result: userid = row[0] if userid not in list: print "============= Analyze" list.append(userid) sr = recommender.similar_row_from_id("", str(userid) , 3); print "user ", str(userid), " is similar to :", sr cursor.close() connector.close()