formatting.py

import json

def clean_recommendations(file_path, new_file_path):
    #추천질의 시작이 "1.~~"이 아닌 "물론입니다. 1.~~" 같은 데이터가 있을경우 번호 앞에 내용을 전부 제거함
    with open(file_path, 'r', encoding='utf-8') as file:
        data = json.load(file)
    count = 0
    modified_count = 0
    for entry in data:
        if '추천질의' in entry and entry['추천질의']:
            questions = entry['추천질의'].split('\n')
            updated_questions = []
            for i, question in enumerate(questions, start=1):
                new_question = f"{i}. {question.split('. ', 1)[-1]}"
                if new_question != question:
                    modified_count += 1
                updated_questions.append(new_question)
            entry['추천질의'] = '\n'.join(updated_questions)
            count += 1
    
    with open(new_file_path, 'w', encoding='utf-8') as file:
        json.dump(data, file, ensure_ascii=False, indent=4)
    print(f"\033[94mclean_recommendations 완료. 포매팅된 개수: {modified_count} / {count} \033[0m")


def trim_long_recommendations(file_path, new_file_path):
    # 추천질의가 4개 이상인 것들은 3개까지만 저장되도록 포매팅
    with open(file_path, 'r', encoding='utf-8') as file:
        data = json.load(file)
    
    count = 0
    modified_count = 0
    for entry in data:
        if '추천질의' in entry and entry['추천질의']:
            questions = entry['추천질의'].split('\n')
            updated_questions = []
            for i, question in enumerate(questions, start=1):
                if i > 3 and len(question.split('. ')) > 1:
                    break
                updated_questions.append(question)
            if len(updated_questions) != len(questions):
                modified_count += 1
            entry['추천질의'] = '\n'.join(updated_questions)
            count += 1
    
    with open(new_file_path, 'w', encoding='utf-8') as file:
        json.dump(data, file, ensure_ascii=False, indent=4)

    print(f"\033[94mtrim_long_recommendations 완료. 변경된 데이터 개수: {modified_count} / {count} \033[0m")
    
if __name__=="__main__":
    file_path = '/dataset/question_recommendation/QR_v1.5.json'
    new_file_path = '/dataset/question_recommendation/QR_v1.5_1.json'
    
    clean_recommendations(file_path, new_file_path)
    trim_long_recommendations(new_file_path, new_file_path)
    
    print("\033[94m\nDONE!\033[0m")