def user_info(user_ids):
return parser.select(
USERS_FILE,
lambda x: int(x[0]) in user_ids and "NULL" not in x,
parser.build_user,
lambda x: int(x[0])
)
def download_items():
http = httplib2.Http()
content = http.request(items_url(SERVER), method="GET", headers=header(TOKEN))[1].decode("utf-8")
fp = open(TMP_ITEMS, "w")
fp.write(content)
fp.close()
return parser.select(TMP_ITEMS, lambda x: True, parser.build_item, lambda x: int(x[0]))
def download_items():
http = httplib2.Http()
content = http.request(items_url(SERVER),
method="GET",
headers=header(TOKEN))[1].decode("utf-8")
fp = open(TMP_ITEMS, "w")
fp.write(content)
fp.close()
return parser.select(TMP_ITEMS, lambda x: True, parser.build_item,
lambda x: int(x[0]))
def user_info(user_ids):
return parser.select(USERS_FILE,
lambda x: int(x[0]) in user_ids and "NULL" not in x,
parser.build_user, lambda x: int(x[0]))
def parse_exp(l):
return select(EXP_RULES)(l)
from parser import build_item, build_user, select
from recommendation_worker import classify_worker
N_WORKERS = 2
USERS_FILE = "/students/iamishalkin/shared/ReqSys/data/users.csv"
ITEMS_FILE = "/students/iamishalkin/shared/ReqSys/data/items.csv"
INTERACTIONS_FILE = "/students/iamishalkin/shared/ReqSys/data/interactions.csv"
TARGET_USERS = "targetUsers.csv"
#TARGET_USERS='targetUsers_W_H.csv'
TARGET_ITEMS = "/students/iamishalkin/shared/ReqSys/data/targetItems.csv"
'''
1) Parse the challenge data, exclude all impressions
Exclude all impressions
'''
(header_users, users) = select(USERS_FILE, lambda x: True, build_user,
lambda x: int(x[0]))
(header_items, items) = select(ITEMS_FILE, lambda x: True, build_item,
lambda x: int(x[0]))
'''
4) Create target sets for items and users
'''
target_users = []
for line in open(TARGET_USERS):
target_users += [int(line.strip())]
target_users = set(target_users)
target_items = []
for line in open(TARGET_ITEMS):
target_items += [int(line.strip())]
'''
5) Schedule classification
