def nearest_ratings(user_id, count, address):
"""Get Nearest Recommended business to user's address """
logger.debug("User %s rating requested for nearest address", user_id,
address)
ratings = recommendationengine.get_nearest_businesses(
user_id, count, address)
return json.dumps(ratings)
def add_ratings(user_id):
# get the ratings from the Flask POST request object http://<SERVER_IP>:5432/0/ratings/top/10
ratings_list = request.form.keys()[0].strip().split("\n")
ratings_list = map(lambda x: x.split(","), ratings_list)
# create a list with the format required by the negine (user_id, movie_id, rating)
ratings = map(lambda x: (user_id, int(x[0]), float(x[1])), ratings_list)
# add them to the model using then engine API
recommendationengine.add_ratings(ratings)
return json.dumps(ratings)
def data(self):
s = extrapolate_statistics(logging.statistics)
cherrypy.response.headers['Content-Type'] = 'application/json'
return json.dumps(s, sort_keys=True, indent=4)
def get_user_Ids():
logger.debug("Users")
userIds = recommendationengine.get_User_Ids()
return json.dumps(userIds)
def business_ratings(user_id, business_id):
logger.debug("User %s rating requested for business %s", user_id,
business_id)
ratings = recommendationengine.get_ratings_for_business_ids(
user_id, [business_id])
return json.dumps(ratings)
def ratings_within_category(user_id, count, category):
"""Get Top Recommendations within the category"""
logger.debug("User %s rating requested for category %s", user_id, category)
ratings = recommendationengine.get_business_in_categories(
user_id, count, category)
return json.dumps(ratings)
def ratings_within_state(user_id, count, state):
"""Get Top Recommendations within the state """
logger.debug("User %s rating requested for state %s", user_id, state)
ratings = recommendationengine.get_business_in_state(user_id, count, state)
data = json.dumps(ratings)
return data
def top_recommendation(user_id, count):
"""Get Top Recommendations """
top_ratings = recommendationengine.get_top_ratings_with_business_info(
user_id, count)
return json.dumps(top_ratings)
def data(self):
s = extrapolate_statistics(logging.statistics)
cherrypy.response.headers['Content-Type'] = 'application/json'
return json.dumps(s, sort_keys=True, indent=4)