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()