import asyncio
import json
from typing import Union

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

import dock
import models
from dock.govs import govs_api
from models.govs_order_master import GovsOrderMaster
from paste.core.logging import echo_log
from paste.util import udict
from paste.web import requests


async def get_task_request(order_id: Union[str, int] = '', dept_page_tag: int = 1,
                           current_page: int = 1, num_per_page: int = 200):
    """
    获取省12345任务列表数据。
    通过 POST 请求向省12345的任务列表接口提交表单数据，获取任务分页数据。

    Args:
        order_id (int): 任务列表类型 ID，默认为企业待办：600058
        dept_page_tag (int): 分页标志
        current_page (int): 当前页码
        num_per_page (int): 每页显示数据量，默认 200
    """
    api_url = f"/orderhandler/taskQuery/getDeptAllToDoOrderProcess"
    request_body = {
        "data": {
            "deptPageTag": dept_page_tag,
            "orderId": f"{order_id}",
            "keyWord": "",
            "andOrFlag": "0",
            "serviceObjectType": [],
            "callNumber": "",
            "orderSource": [],
            "orderSourceDetailList": [],
            "signedStatus": [],
            "firstOrderStatus": [],
            "secordOrderStatus": [],
            "status": [],
            "overDue": "",
            "existQuotoInfo": [],
            "isSupervise": [],
            "planFinishTime": "",
            "caseIsUrgent": [],
            "areaCodeCity": "",
            "areaCodeArea": "",
            "areaCodeStreet": "",
            "addressDetail": "",
            "infoProtect": [],
            "firstLevelAffiliations": [],
            "secondLevelAffiliations": [],
            "thirdLevelAffiliations": [],
            "fourthLevelAffiliations": [],
            "fifthLevelAffiliations": [],
            "caseAccordTypeOneNames": [],
            "caseAccordTypeTwoNames": [],
            "caseAccordTypeThreeNames": [],
            "caseAccordTypeFourNames": [],
            "caseAccordTypeFiveNames": [],
            "creatorId": "",
            "assigneeUserId": "",
            "callTimeEnd": "",
            "callTimeFrom": "",
            "caseLabels": [],
            "contactNumber": "",
            "createBy": "",
            "deptName": "",
            "deptType": "",
            "fileExist": [],
            "hotspot": [],
            "claimStatus": "",
            "orderSourceDetail": "",
            "orderType": [],
            "orgName": [],
            "sortField": "",
            "sortRule": "",
            "actionName": "",
            "returnReasonNameList": [],
            "createDateFrom": "",
            "createDateEnd": "",
            "planBackTimeStart": "",
            "planBackTimeEnd": "",
            "planFinishTimeStart": "",
            "planFinishTimeEnd": ""
        },
        "pageSize": num_per_page,
        "pageNum": current_page
    }
    # 构造 API 请求
    return await govs_api.new_api_request(api_url, request_body)


async def after_task_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)
    list_data: list[dict] = udict.get_by_path(response_data, 'data.list')
    order_master_list: list[dict] = []
    for d in list_data:
        order_master_dto = d.get('orderMasterDTO')
        order_master_dto['nextTaskId'] = d.get('nextTaskId')
        order_master_dto['claimStatus'] = d.get('claimStatus')
        order_master_list.append(order_master_dto)
    if order_master_list:
        mapped_df = pd.DataFrame(order_master_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 GovsOrderMaster.FieldMapping.items()}
        mapped_df = mapped_df.rename(columns=forward_mapping)
        # 把数组转换为 JSON 字符串
        mapped_df[GovsOrderMaster.attachment_list.key] = mapped_df[GovsOrderMaster.attachment_list.key].apply(
            lambda x: json.dumps(x, ensure_ascii=False) if x is not None else None
        )
        mapped_df[GovsOrderMaster.back_count.key] = mapped_df[GovsOrderMaster.back_count.key].apply(
            lambda x: json.dumps(x, ensure_ascii=False) if x is not None else None
        )
        # 根据claim_status字段，更新govs_sign字段
        mapped_df[GovsOrderMaster.govs_sign.key] = np.where(
            mapped_df[GovsOrderMaster.claim_status.key] == '已签收', 1, 0
        )
        # 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)
        # 筛选数据状态
        _created, _updated = await GovsOrderMaster.save_batch(mapped_df)
        echo_log(f"成功创建企业待办：{_created}条，更新：{_updated}条.")
    else:
        echo_log('未获取到企业待办数据')
    if retry_queue:
        echo_log(f"企业待办重试队列中有：{retry_queue.qsize()} 个请求在等待.")


if __name__ == "__main__":
    from paste.core import aio_pool


    async def scrape():
        task_request = await get_task_request(dept_page_tag=0, order_id='DH058726052903006')
        request_queue = asyncio.Queue()
        await request_queue.put(task_request)
        await requests.async_concurrency(
            request_queue, retry=dock.MAX_RETRY_COUNT,
            after_request=after_task_request
        )


    _runner = aio_pool.get_aio_runner()
    _runner(scrape())