import asyncio
import json

import pandas as pd
from tornado.httpclient import HTTPResponse, HTTPRequest

from dock.govc import govc_api
import models
from models.govc_task_history import GovcTaskHistory
from paste.util import udict
from paste.core.logging import echo_log


async def get_history_order_request(cguid: str):
    """
    获取市12345的工单的历史工单信息，请求响应是单条工单的数据

    :param cguid: 工单列表请求返回的cguid
    """
    api_url = '/rest/sztaskworkordercommonrest/getHistoryWorkOrder'
    headers = {
        'Referer': f'{govc_api.ApiUrl}/rest/sztaskworkordercommonrest/getHistoryWorkOrder'
    }
    request_body = {
        'caseguid': cguid
    }
    # 构造 API 请求
    return await govc_api.new_api_request(api_url, request_body, headers=headers, method='GET')


async def after_history_order_request(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
    """
    任务请求响应后的处理程序。

    :param response: 响应对象
    :param retry_queue: 重试队列
    """
    response_body = response.body.decode()
    response_data = json.loads(response_body)
    history_order_list = udict.get_by_path(response_data, 'params.list')
    if history_order_list:
        mapped_df = pd.DataFrame(history_order_list)
        # 更换映射方向，用于将源数据列名改为与数据库表对应
        forward_mapping = {dict_f: table_f for table_f, dict_f in GovcTaskHistory.FieldMapping.items()}
        mapped_df = mapped_df.rename(columns=forward_mapping)
        # 这里把空数据都换成 None，以便存入数据库时是 null
        mapped_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, None, inplace=True)
        task_id = getattr(response.request, GovcTaskHistory.task_id.key)
        mapped_df[GovcTaskHistory.task_id.key] = task_id
        # 筛选数据状态
        _created, _updated = await GovcTaskHistory.save_batch(mapped_df)
        echo_log(f"成功创建历史工单信息：{_created}条，更新：{_updated}条.")
    else:
        echo_log('未获取到历史工单信息')
    if retry_queue:
        echo_log(f"历史工单信息重试队列中有：{retry_queue.qsize()} 个请求在等待.")