# script used to convert original json
import json
from pathlib import Path

def map_answer_to_index(answer_letter):
    """Convert answer letter to numerical index (0-based)"""
    return {'a': 0, 'b': 1, 'c': 2, 'd': 3}[answer_letter.lower()]

def find_correct_answer(question):
    """Correct answer is always A / 0"""
    return 0

def transform_question(question):
    """Transform a single question from original format to target format"""
    
    # Base question structure
    transformed = {
        "language": "de",
        "country": "Germany",
        "file_name": "fragenkatalog3b.json",
        "source": "https://www.bundesnetzagentur.de/SharedDocs/Downloads/DE/Sachgebiete/Telekommunikation/Unternehmen_Institutionen/Frequenzen/Amateurfunk/Fragenkatalog/PruefungsfragenZIP.html - Prüfungsfragen zum Erwerb von Amateurfunkprüfungsbescheinigungen, Bundesnetzagentur, 3. Auflage, März 2024, (www.bundesnetzagentur.de/amateurfunk), Datenlizenz Deutschland – Namensnennung – Version 2.0 (www.govdata.de/dl-de/by-2-0)",
        "license": "DL-DE->BY-2.0",
        "level": f"Official Exam (Class {question['class']})", 
        "category_en": "Amateur Radio",
        "category_original_lang": "Amateurfunk",
        "original_question_num": question["number"],
        "question": question["question"].strip(),
        "parallel_question_id": None,
        "image_png": None,
        "image_information": None,
        "image_type": None
    }

    # Handle options based on question type
    if any(key.startswith('picture_') for key in question.keys()):
        # Question with images
        if 'picture_a' in question:
            # Multiple choice with image options
            transformed["options"] = [
                question['picture_a'] + ".png",
                question['picture_b'] + ".png", 
                question['picture_c'] + ".png",
                question['picture_d'] + ".png"
            ]
        else:
            # Text options with question image
            transformed["options"] = [
                question['answer_a'].strip(),
                question['answer_b'].strip(),
                question['answer_c'].strip(), 
                question['answer_d'].strip()
            ]
            if 'picture_question' in question:
                transformed["image_png"] = question["picture_question"] + ".png"
                transformed["image_information"] = "essential"
                transformed["image_type"] = "diagram"
    else:
        # Regular text-only question
        transformed["options"] = [
            question['answer_a'].strip(),
            question['answer_b'].strip(),
            question['answer_c'].strip(),
            question['answer_d'].strip()
        ]

    # Set the correct answer
    transformed["answer"] = find_correct_answer(question)

    return transformed

def convert_questions(input_file):
    """Convert all questions from input file to new format"""
    with open(input_file, 'r', encoding='utf-8') as f:
        data = json.load(f)
    
    transformed_questions = []
    
    def process_section(section):
        if 'questions' in section:
            for q in section['questions']:
                transformed_questions.append(transform_question(q))
        if 'sections' in section:
            for subsection in section['sections']:
                process_section(subsection)
    
    process_section(data)
    
    return transformed_questions

def main():
    input_file = Path('fragenkatalog3b.json')
    output_file = input_file.with_stem(input_file.stem + '_transformed')
    
    transformed = convert_questions(input_file)
    
    with open(output_file, 'w', encoding='utf-8') as f:
        json.dump(transformed, f, ensure_ascii=False, indent=2)

if __name__ == "__main__":
    main()