import spacy
import names
from faker import Faker

nlp = spacy.load("en_core_web_sm")
fake = Faker()
with open('./src/female_names.txt', 'r') as file:
    female = [current_name.rstrip() for current_name in file.readlines()]


def anonymize(text):
    doc = nlp(text)
    name_to_anonymize = " ".join(
        [entity.text for entity in doc.ents if entity.label_ == 'PERSON'])
    orga_to_anonymize = " ".join(
        [entity.text for entity in doc.ents if entity.label_ == 'ORG'])
    # Anonymize Name and Surname 
    if len(name_to_anonymize) != 0:
        counter = 0
        while counter < (len(name_to_anonymize.split(' '))-1):
            if str(name_to_anonymize.split(' ')[counter]).upper() in female:
                text = text.replace(str(name_to_anonymize.split(
                    ' ')[counter]), names.get_first_name(gender='female'))
            else:
                text = text.replace(str(name_to_anonymize.split(
                    ' ')[counter]), names.get_first_name(gender='male'))
            text = text.replace(str(name_to_anonymize.split(
                ' ')[counter+1]), names.get_last_name())
            counter += 2
    
    # Anonymize Corporation
    if len(orga_to_anonymize) != 0:
        counter_org = 0
        while counter_org < (len(orga_to_anonymize.split(' '))):
            text = text.replace(str(orga_to_anonymize.split(' ')[
                                counter_org]), fake.company())
            counter_org += 1
    return text