# coding:utf-8

from docs.config import ai2config
from tables.ai.table_field_category import TableFieldCategoryModel
from tables.ai import fields_ner
from util.info_preprocess import Preprocess
from util.fs_client import FileServeClient
import re
from util.mogodb_helper import MongoDBInterface

# 初始化
fsc = FileServeClient()   # oss客户端
preprocess = Preprocess()  # 文本预处理程序（html,attach）
tfc_object = TableFieldCategoryModel(ai2config["table_field_config"])  # 表格字段识别模型实例


class CatchContentObject(object):
    """
    缓存
    """

    def __init__(self):
        self.catch = {}

    def public_attachment_catch(self, content, platform, document_id):
        if document_id in self.catch:
            return self.catch[document_id]
        contents = preprocess.get_preprocess(platform).preprocess(content)
        contents=contents.replace("(","（").replace(")","）")
        contents = contents.split("\n")
        contents = [c for c in contents if c.strip()]
        self.catch[document_id] = contents
        return contents

    def initialize(self):
        self.catch = {}


def match_company_index(companies: list, content: str):
    """
    获取公司所在文本位置
    :param companies:公司列表
    :param content:文本
    :return:
    """
    companies.sort(key=lambda x: len(x), reverse=True)
    match_index = []
    pattern = r"|".join(companies)
    repatten = pattern.replace(")", "\)").replace("(", "\(").replace(".", "\.").replace("*", "\*")
    for company in re.finditer(repatten, content):
        start_index = company.start()
        company_name = company.group()
        end_index = company.end()
        match_index.append((start_index, end_index, company_name))  # （start_index,company_name）
    return match_index


def key_value_header(content):
    """
    获取content中的键值
    :param content:文本
    :return:
    """
    head = []
    ret = fields_ner(text=content)
    result = ret.get("result", [])
    if result:
        head = result[0].get("HEAD", [])
    return head


def clear_spacing(data_list):
    '''
    清理二维列表中的空值、空格
    :param data_list: 待处理的二维列表
    :return: 处理后的二维列表
    '''
    new_data_list = []
    # 遍历原始列表的每一行
    for row in data_list:
        new_row = []
        for elem in row:
            # 如果元素为None，则将其转换为空字符串
            new_row.append("") if not elem else new_row.append(elem.replace(" ", ""))
        new_data_list.append(new_row)
    return new_data_list

if __name__ == '__main__':
    ret = match_company_index("中标单位：xxxx公司")
    print(ret)