KC2016

# For the implementation, it was used Python decorator in Django REST framework to define a view function that can handle HTTP requests.

@api_view(['GET'])
def getRakingRecomm(request):
    category_arg = request.query_params.get('chosen_category')
    # the ML model returns the id of 3 ranked recommended items based on the category selected on the search bar
#    recommendation_dir = os.path.join(settings.BASE_DIR, 'm_l', 'recommendation')
#    sys.path.append(recommendation_dir)
#    from  recommendation_f import create_ranking_df
    id1, id2, id3 = create_ranking_df(category_arg)

KC2016

import urllib.parse
import requests
import urllib.parse
from urllib.parse import urlparse


url_search = 'https://geofree.pythonanywhere.com/api/get-categories/'
response2 = requests.get(url_search)

parsed_url = urlparse(url_search)

KC2016

import sqlite3
import pandas as pd
import urllib.parse
import requests
from urllib.parse import urlparse
import json
import random


def create_ranking_df(chosen_category):