import os
import yaml
import pandas as pd
import logging
from typing import Any, Dict, List

# 設定 logging 基本參數
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# 如果需要檔案鎖定，可以使用 filelock 模組（需先安裝：pip install filelock）
try:
    from filelock import FileLock
    FILELOCK_AVAILABLE = True
except ImportError:
    FILELOCK_AVAILABLE = False
    logger.warning("filelock 模組未安裝，未啟用檔案鎖定機制。")

class YAMLProcessor:
    def __init__(self, yaml_path: str = "local_data.yaml") -> None:
        """
        處理 YAML 讀寫的類別。

        Args:
            yaml_path (str): YAML 檔案路徑。
        """
        self.yaml_path = yaml_path

        # 檢查目錄是否存在，不存在則建立
        directory = os.path.dirname(os.path.abspath(self.yaml_path))
        if directory and not os.path.exists(directory):
            try:
                os.makedirs(directory, exist_ok=True)
                logger.info("建立目錄：%s", directory)
            except Exception as e:
                logger.error("建立目錄失敗：%s", e)

        # 如果檔案不存在，就建立一個空的
        if not os.path.isfile(self.yaml_path):
            try:
                with open(self.yaml_path, "w", encoding="utf-8") as f:
                    yaml.safe_dump([], f, allow_unicode=True)
                logger.info("建立 YAML 檔案：%s", self.yaml_path)
            except Exception as e:
                logger.error("建立 YAML 檔案失敗：%s", e)

    def load_local_data(self) -> pd.DataFrame:
        """
        從 YAML 中讀取資料並轉成 DataFrame。

        Returns:
            pd.DataFrame: YAML 檔案內容。
        """
        data: List[Dict[str, Any]] = []
        try:
            # 如果有啟用檔案鎖定，則使用 filelock 保護檔案讀取
            if FILELOCK_AVAILABLE:
                lock_path = self.yaml_path + ".lock"
                with FileLock(lock_path):
                    with open(self.yaml_path, "r", encoding="utf-8") as f:
                        data = yaml.safe_load(f)
            else:
                with open(self.yaml_path, "r", encoding="utf-8") as f:
                    data = yaml.safe_load(f)
        except Exception as e:
            logger.error("讀取 YAML 時發生錯誤：%s", e)
            data = []

        if data is None:
            data = []

        return pd.DataFrame(data)

    def save_local_data(self, df: pd.DataFrame) -> None:
        """
        將 DataFrame 內容回存到 YAML。

        Args:
            df (pd.DataFrame): 要存回 YAML 的 DataFrame。
        """
        data_list = df.to_dict(orient="records")
        try:
            # 如果有啟用檔案鎖定，則使用 filelock 保護檔案寫入
            if FILELOCK_AVAILABLE:
                lock_path = self.yaml_path + ".lock"
                with FileLock(lock_path):
                    with open(self.yaml_path, "w", encoding="utf-8") as f:
                        yaml.safe_dump(data_list, f, allow_unicode=True)
            else:
                with open(self.yaml_path, "w", encoding="utf-8") as f:
                    yaml.safe_dump(data_list, f, allow_unicode=True)
            logger.info("成功儲存 YAML 檔案：%s", self.yaml_path)
        except Exception as e:
            logger.error("儲存 YAML 時發生錯誤：%s", e)

def main():
    # 指定 YAML 檔案路徑（可依需求調整）
    yaml_file = "local_data.yaml"
    processor = YAMLProcessor(yaml_file)

    # 載入 YAML 檔案內容為 DataFrame
    df = processor.load_local_data()
    print("目前 YAML 檔案資料：")
    print(df)

    # 定義一筆新的資料記錄
    new_record = {"name": "Alice", "age": 30, "city": "Taipei"}

    # 如果 DataFrame 為空，建立新的 DataFrame；否則新增一筆資料
    if df.empty:
        df = pd.DataFrame([new_record])
    else:
        df.loc[len(df)] = new_record

    # 將更新後的 DataFrame 儲存回 YAML 檔案
    processor.save_local_data(df)
    print("更新後的資料已儲存回 YAML 檔案。")

if __name__ == "__main__":
    main()