reviews_test = [json.loads(line) for line in f]
users_rev_dic = {}
for rev in reviews:
if not users_rev_dic.has_key(rev["user_id"]):
biz_rev_dic = {rev["business_id"]: rev["stars"]}
users_rev_dic[rev["user_id"]] = biz_rev_dic
else:
users_rev_dic[rev["user_id"]][rev["business_id"]] = rev["stars"]
print 'dic built'
#Build the model
model = MatrixPreferenceDataModel(users_rev_dic)
print 'Model built'
#Build the similarity
similarity = UserSimilarity(model, pearson_correlation)
print 'Similarity built'
#Build the User based recommender_sample.py
recommender = UserBasedRecommender(model, similarity, with_preference=True)
print 'Recommender built'
recommender.estimate_preference("EMpFiVyiaMS58XsLZdS6vA", 'QL3vFMAsEHqfi1KGH-4igg')
print 'end'
