import pandas as pd
from typing import List, Optional, Union, Tuple
import logging
from mylib.logging_config import setup_logging

# Setup custom logging
setup_logging()
logger = logging.getLogger('excel_tool')

class ExcelProcessor:
    def __init__(self, file_path, header_row=1):
        """Initialize Excel processor"""
        self.file_path = file_path
        self.header_row = header_row
        self.df = self.read_file(self.file_path, self.header_row)

    def _column_letter_to_index(self, col: str) -> int:
        """将Excel列字母转换为索引（A=0, B=1,...）"""
        index = 0
        for char in col.upper():
            if not 'A' <= char <= 'Z':
                raise ValueError(f"无效的列字母: {col}")
            index = index * 26 + (ord(char) - ord('A') + 1)
        return index - 1

    def _index_to_column_letter(self, index: int) -> str:
        """将列索引转换为Excel列字母（0=A, 1=B,...）"""
        if index < 0:
            raise ValueError("列索引不能为负数")
        letters = []
        while index >= 0:
            letters.append(chr(ord('A') + (index % 26)))
            index = index // 26 - 1
        return ''.join(reversed(letters))

    def search_headers(self, keywords: Union[str, List[str]]) -> List[Tuple[str, str]]:
        """
        从表头搜索关键词，返回匹配的列名和列字母
        
        Args:
            keywords (Union[str, List[str]]): 要搜索的关键词或关键词列表
            
        Returns:
            List[Tuple[str, str]]: 匹配的列名和列字母列表，格式为[(列名, 列字母), ...]
        """
        try:
            # 如果输入是单个字符串，转换为列表
            if isinstance(keywords, str):
                keywords = [keywords]
                
            # 获取所有列名
            columns = self.df.columns.tolist()
            
            # 查找匹配的列
            matches = []
            for idx, col in enumerate(columns):
                if any(keyword.lower() in str(col).lower() for keyword in keywords):
                    col_letter = self._index_to_column_letter(idx)
                    matches.append((col, col_letter))
                    
            logger.info(f"搜索关键词 {keywords} 找到 {len(matches)} 个匹配列")
            return matches
            
        except Exception as e:
            logger.error(f"搜索表头失败: {str(e)}")
            raise

    def read_file(self, file_path: str, header_row: Optional[int] = 0) -> pd.DataFrame:
        """
        读取文件并返回DataFrame
        支持Excel和CSV文件
        
        Args:
            file_path (str): 文件路径
            header_row (int, optional): 表头所在行号，从0开始计数. Defaults to 0.
        """
        try:
            if file_path.endswith('.csv'):
                df = pd.read_csv(file_path, header=header_row)
                logger.info(f"成功读取CSV文件: {file_path}, 表头行: {header_row}")
            else:
                # 对于Excel文件，指定engine参数
                df = pd.read_excel(file_path, engine='openpyxl', header=header_row)
                # 打印表头行
                logger.info(f"成功读取Excel文件: {file_path}, 表头行: {header_row}")
            logger.info(f"表头行: {df.columns.tolist()}")
            return df
        except Exception as e:
            logger.error(f"读取文件失败: {file_path}, 错误: {str(e)}")
            raise

    def save_file(self, df: pd.DataFrame, output_path: str) -> None:
        """
        将DataFrame保存为文件
        支持Excel和CSV格式
        """
        try:
            if output_path.endswith('.csv'):
                df.to_csv(output_path, index=False)
                logger.info(f"成功保存CSV文件: {output_path}")
            else:
                # 对于Excel文件，指定engine参数
                df.to_excel(output_path, index=False, engine='openpyxl')
                logger.info(f"成功保存Excel文件: {output_path}")
        except Exception as e:
            logger.error(f"保存文件失败: {output_path}, 错误: {str(e)}")
            raise

    def insert_column(self, ref_column: str, new_column_name: str, position: str = 'right') -> pd.DataFrame:
        """
        在指定列旁边插入空列
        
        Args:
            ref_column (str): 参考列名或Excel列字母（如'A', 'B'）
            new_column_name (str): 新列名
            position (str): 插入位置，'left'或'right'，默认为'right'
            
        Returns:
            pd.DataFrame: 包含新列的DataFrame
        """
        df = self.df
        try:
            # 如果ref_column是字母，转换为列索引
            if ref_column.isalpha():
                col_index = self._column_letter_to_index(ref_column)
                ref_column = df.columns[col_index]
            
            # 获取参考列的位置
            ref_index = df.columns.get_loc(ref_column)
            
            # 计算插入位置
            insert_index = ref_index + 1 if position == 'right' else ref_index
            
            # 插入新列
            df.insert(insert_index, new_column_name, '')
            
            logger.info(f"成功在列 '{ref_column}' 的 '{position}' 插入新列 '{new_column_name}' ")
            return df
            
        except Exception as e:
            logger.error(f"插入列失败: {str(e)}")
            raise

if __name__ == '__main__':
    # 测试代码
    processor = ExcelProcessor('/home/mrh/code/excel_tool/temp/测试_process.csv')
    # 测试CSV文件
    processor.insert_column('B', '翻译结果')
    
    # 测试搜索表头
    matches = processor.search_headers(['名称', '描述'])
    print(f"找到的匹配列: {matches}")
    
    # processor.save_file(df, '/home/mrh/code/excel_tool/temp/测试_process.csv')