import csv
import os
import random

class QuestionLoaderLocal:
    def __init__(self, file_path, question_count):
        """
        Initializes the QuestionLoader with a base path for local files.

        :param base_path: The base path where the question files are located.
        """
        self.base_path = "candidate_assesment/data"
        self.question_count = question_count
        self.file_path = file_path

    def fetch_questions(self):
        """
        Fetches the questions for the given technology from the local file system.

        :param technology: The technology (e.g., Python, Django) to fetch questions for.
        :return: A list of dictionaries, where each dictionary represents a question.
        :raises: Exception if the file cannot be fetched or read.
        """
        # file_path = os.path.join(BASE_DIR, "questions", technology, "questions.csv")
        if not os.path.exists(self.file_path):
            return []
            # raise FileNotFoundError(f"No questions found for technology")

        try:
            questions = []

            # Read and parse the CSV file
            with open(self.file_path, mode="r", encoding="utf-8") as file:
                csv_reader = csv.DictReader(file)
                for row in csv_reader:
                    questions.append({
                        "question": row["question"],
                        "option1": row["option1"],
                        "option2": row["option2"],
                        "option3": row["option3"],
                        "option4": row["option4"],
                        "answer": row["answer"],
                        "difficulty": row["difficulty"].lower()
                    })
            # Randomly select 20 questions
            sampled_questions = random.sample(questions, min(self.question_count, len(questions)))
            return sampled_questions

        except Exception as e:
            raise RuntimeError(f"Failed to fetch questions: {str(e)}")