import random
from typing import Dict

import pandas as pd

from processing.ner.formats import BaseNameFormatter


class ExtendedSurnameFormatter(BaseNameFormatter):
    def transform(self, row: pd.Series) -> Dict:
        native_parts = self.parse_native_components(row['probable_native'])
        original_surname = row['probable_surname'] if pd.notna(row['probable_surname']) else ''

        # Add random additional surname
        additional_surname = random.choice(self.additional_surnames)
        combined_surname = f"{additional_surname} {original_surname}".strip()
        full_name = f"{row['probable_native']} {combined_surname}".strip()

        return {
            'name': full_name,
            'probable_native': row['probable_native'],
            'identify_name': row['probable_native'],
            'probable_surname': combined_surname,
            'identity_surname': combined_surname,
            'ner_entities': str(self.create_ner_tags(full_name, native_parts, combined_surname)),
            'transformation_type': self.transformation_type,
            **self.compute_derived_attributes(full_name)
        }

    @property
    def transformation_type(self) -> str:
        return 'extended_surname'