def recommend_joke():
'''
session - user_pref, joke_num(0-19)
'''
#write code to get the first joke and compute the matrix
#we have loaded the data
data_raw = pd.read_csv('ratings.csv' ,index_col = 0)
data_jokes = pd.read_csv('jokes.csv', index_col = 0)
data_final = data_raw[:100000]
#create an object of recommender
reco = Recommender(data_final, data_jokes)
res = reco.get_most_popular()
joke = res[0]
joke_num = res[1]
if request.method == 'GET':
#we will randomly select one of the highest rated joke and display it
#insert code to get the joke
session['joke_num'] = joke_num #this is default but you will need to get the joke number you are displaying
session['prev_joke'] = joke
return render_template('joke.html', joke= joke)
else:
#This is the value which the user gave to the previous joke which is represented by joke_num
value = request.form["rating"]
session.pop('rating',None)
#get the joke_num
last_joke = session['joke_num']
session.pop('joke_num',None)
prev_joke = session['prev_joke']
session.pop('prev_joke',None)
#RDS ADD JOKE FOR FUTURE ANALYSIS
joke_add = Jokes(joke = prev_joke,rating = value)
db.session.add(joke_add)
db.session.commit()
#now that we have the joke number we will create the svd with this information
#check if session is set
if 'user_pref' in session:
curr_user_pref = list(session['user_pref'])
session.pop('user_pref',None)
curr_user_pref[last_joke] = int(value)
#fetch the data
#create the matrix
#append the user_pref
#calculate svd
#first we will get the interaction matrix
interaction_df = reco.get_interaction()
#append the user_pref
new_df = reco.append_new_user(interaction_df, curr_user_pref)
#calculate svd using the user_pref
preds_df = reco.get_svd(new_df)
#get the prediction
recommended_res = reco.recommend_joke(preds_df,curr_user_pref)
joke = recommended_res[0]
joke_num= recommended_res[1]
#set the sessions
session['joke_num'] = joke_num
session['user_pref'] = curr_user_pref
session['prev_joke'] = joke
return render_template('recommended_jokes.html', joke= joke)
else :
#first we will get the interaction matrix
interaction_df = reco.get_interaction()
#for that we will set a user_pref
user_pref = [0]*interaction_df.shape[1] #create a list with the length of the number of jokes
user_pref[last_joke] = int(value)
#append the user_pref
new_df = reco.append_new_user(interaction_df, user_pref)
#calculate svd using the user_pref
preds_df = reco.get_svd(new_df)
#get the prediction
recommended_res = reco.recommend_joke(preds_df,user_pref)
joke = recommended_res[0]
joke_num= recommended_res[1]
new_joke = joke
new_joke_number = joke_num#needs to be the one that is being recommend_joke
#set the sessions
session['joke_num'] = new_joke_number
session['user_pref'] = user_pref
session['prev_joke'] = joke
return render_template('recommended_jokes.html', joke= new_joke)
