def get_spesific_values(a_list, key):
temp = []
for d in a_list:
temp.append(d['attributes'][key])
return temp
for i in range(len(candidates_attr)):
current_salary = candidates_attr[i]['attributes']['salary']
current_gpa = candidates_attr[i]['attributes']['gpa']
current_dependant = candidates_attr[i]['attributes']['dependant']
salary_normalized = normalizator.normalize_salary(get_spesific_values(candidates_attr, 'salary'), current_salary)
gpa_normalized = normalizator.normalize_gpa(get_spesific_values(candidates_attr, 'gpa'), current_gpa)
dependant_normalized = normalizator.normalize_dependant(get_spesific_values(candidates_attr, 'dependant'), current_dependant)
candidates_attr_normalized.append([candidates_attr[i]['id'],salary_normalized, gpa_normalized, dependant_normalized])
# Create a simple weight
# example, salary weight is 50%, gpa is 25% and dependant is 25%
role = [0.5, 0.25, 0.25]
results = []
accept = False
for i in range(len(candidates_attr_normalized)):
temp_result = 0
for g in range(len(candidates_attr_normalized[i])):
if g != 0:
accept = True
