import operator
import os
import re
import pandas as pd
from fastapi import APIRouter, Depends, Request, File, UploadFile
from motor.motor_asyncio import AsyncIOMotorDatabase

from utils.dingding import get_redis_alluid, send_dates
from utils.jianli import get_resume
import crud, schemas
from datetime import datetime
from core.configuration import *
from db import get_database
from db.ckdb import get_ck_db, CKDrive

from models.interview_zsgc import InterviewDo
from utils import get_time, qujian_time, Download_xlsx, send_str_mail

router = APIRouter()


# 候选人质量报表
@router.post("/man_mass_form")
async def interview_find(
        request: Request,
        interview: InterviewDo = Depends(InterviewDo),
        db: CKDrive = Depends(get_ck_db),
) -> schemas.Msg:
    """ interview面试数据查询 """
    await interview.init()
    res = interview.get_man_mass_form_sql()
    sql = res['sql']
    data = await db.execute(sql)
    school_985 = ['清华大学', '北京大学', '中国人民大学', '北京理工大学', '北京航空航天大学', '中央民族大学', '北京师范大学',
                  '中国农业大学', '天津大学', '南开大学', '复旦大学', '上海交通大学', '同济大学', '华东师范大学', '重庆大学', '四川大学',
                  '电子科技大学', '湖南大学', '国防科技大学', '中南大学', '厦门大学']

    school_211 = ['上海外国语大学', '东华大学', '上海财经大学', '华东理工大学', '上海大学', '天津医科大学', '吉林大学', '东北师范大学',
                  '延边大学', '哈尔滨工业大学', '哈尔滨工程大学', '东北农业大学', '东北林业大学', '南京大学', '东南大学', '苏州大学',
                  '中国矿业大学', '中国药科大学', '河海大学', '南京航空航天大学', '江南大学', '南京农业大学', '南京理工大学', '浙江大学',
                  '中国科技大学', '安徽大学', '合肥工业大学', '福州大学', '南昌大学', '山东大学', '中国海洋大学', '石油大学',
                  '湖南师范大学', '广西大学', '中山大学', '暨南大学', '华南理工大学', '华南师范大学', '广州中医药大学', '武汉大学',
                  '华中科技大学', '中国地质大学', '武汉理工大学', '华中师范大学', '华中农业大学', '中南财经政法大学']
    # 性别
    gander = {
        '男': [],
        '女': []
    }
    # 年龄
    age = {
        '20-29': [],
        '30-39': [],
        '40-49': [],
        '50-59': [],
        '60-100': [],
    }
    # 学历
    education = {
        '大专': [],
        '本科': [],
        '研究生': [],
        '博士': [],
        '硕士': []
    }
    # 工作经验
    work_exp = {
        '0-2': [],
        '3-6': [],
        '6-10': [],
        '10-20': [],
        '20-40': []
    }
    # 所在地
    account = {
    }
    # 毕业院校
    school = {
    }
    # 就职公司
    work_for = {
    }
    # 渠道
    owner_name = {
        '前程无忧': [],
        '人才库': [],
        '智联招聘': [],
        'Boss直聘': [],
        '58同城': []
    }
    # 职位
    job_name = {
    }
    # 学校类型
    school_type = {
        '985': [],
        '211': [],
        '其他': [],
    }
    if not data:
        return schemas.Msg(code=-9, msg='无数据', data=None)

    # 处理数据
    for interview_data in data.values():
        i_name = interview_data.get('name', '默认名字')

        i_gander = interview_data.get('gander', '男')
        if i_gander == '男':
            gander['男'].append(i_name)
        else:
            gander['女'].append(i_name)

        i_age = interview_data.get('age', 20)
        if i_age <= 29:
            age['20-29'].append(i_name)
        elif 30 <= i_age <= 39:
            age['30-39'].append(i_name)
        elif 40 <= i_age <= 49:
            age['40-49'].append(i_name)
        elif 50 <= i_age <= 59:
            age['50-59'].append(i_name)
        else:
            age['60-100'].append(i_name)

        i_education = interview_data.get('education', 1)
        if i_education == 1:
            education['大专'].append(i_name)
        elif i_education == 2:
            education['本科'].append(i_name)
        elif i_education == 3:
            education['研究生'].append(i_name)
        elif i_education == 4:
            education['博士'].append(i_name)
        else:
            education['硕士'].append(i_name)

        i_owner_name = interview_data.get('owner_name', 2)
        if i_owner_name == 1:
            owner_name['前程无忧'].append(i_name)
        elif i_owner_name == 2:
            owner_name['人才库'].append(i_name)
        elif i_owner_name == 3:
            owner_name['智联招聘'].append(i_name)
        elif i_owner_name == 4:
            owner_name['Boss直聘'].append(i_name)
        else:
            owner_name['58同城'].append(i_name)

        i_school = interview_data.get('school', '')
        if i_school:
            if i_school in school:
                school[i_school].append(i_name)
            else:
                school[i_school] = [i_name]
            if i_school in school_985:
                school_type['985'].append(i_name)
                school_type['211'].append(i_name)
            elif i_school in school_211:
                school_type['211'].append(i_name)
            else:
                school_type['其他'].append(i_name)

        i_work_exp = interview_data.get('work_exp', 1)
        if i_work_exp <= 2:
            work_exp['0-2'].append(i_name)
        elif 3 <= i_work_exp < 6:
            work_exp['3-6'].append(i_name)
        elif 6 <= i_work_exp < 10:
            work_exp['6-10'].append(i_name)
        elif 10 <= i_work_exp < 20:
            work_exp['10-20'].append(i_name)
        else:
            work_exp['20-40'].append(i_name)

        i_job_name = interview_data.get('job_name', '')
        if i_job_name:
            if i_job_name in account:
                job_name[i_job_name].append(i_name)
            else:
                job_name[i_job_name] = [i_name]

        i_account = interview_data.get('account', '')
        if i_account:
            if i_account in account:
                account[i_account].append(i_name)
            else:
                account[i_account] = [i_name]

        i_work_list = interview_data.get('work_list', '')
    res_msg = {
        'gander': gander,
        'age': age,
        'education': education,
        'work_exp': work_exp,
        'account': account,
        'school': school,
        'work_for': work_for,
        'owner_name': owner_name,
        'job_name': job_name,
        'school_type': school_type
    }

    return schemas.Msg(code=200, msg='ok', data=res_msg)