def GetNearRest(uid):
con= databaseCon.Database()
return json.dumps(con.NearRestaurants(uid),indent=2)
def GetNameRest(uid):
con= databaseCon.Database()
return json.dumps(con.getRestoName(),indent=2)
def RateRestaurant(Restaurantid,value,uid):
con= databaseCon.Database()
return con.RateRestaurant(Restaurantid,value,uid)
def GetUser(uid):
con= databaseCon.Database()
return json.dumps(con.getUser(uid),indent=2)
def createUser(uid):
con= databaseCon.Database()
return con.CreatetUser(uid)
def getUser(uid):
print("Came here")
con = databaseCon.Database()
return json.dumps(con.getUser(uid),indent=2)
from surprise import SVD
import pandas as pd
from surprise import Dataset
from surprise import Reader
from collections import defaultdict
from surprise.model_selection import cross_validate
import databaseCon
con = databaseCon.Database()
loadedData = con.selectAll()
userGroupId = loadedData[0]
ingredientId = loadedData[1]
ratings = loadedData[2]
def do_Predict():
ratings_dict = {
'userID': userGroupId,
'itemID': ingredientId,
'rating': ratings
}
df = pd.DataFrame(ratings_dict)
reader = Reader(rating_scale=(1, 4))
data = Dataset.load_from_df(df[['userID', 'itemID', 'rating']], reader)
trainset = data.build_full_trainset()
algo = SVD()
algo.fit(trainset)
testset = trainset.build_anti_testset()
predictions = algo.test(testset)
cross_validate(algo, data, measures=['RMSE', 'MAE'], cv=5, verbose=True)
def rateItem(itemName, ratedValue, uid):
con = databaseCon.Database()
return con.rateItem(itemName, ratedValue, uid)
