{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "04524c85-988e-4dbf-86eb-939a9db7aa28",
   "metadata": {},
   "source": [
    "\n",
    "## 体测人员导入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bbba6efc-73cd-4db6-bae7-014724fee731",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-03T14:01:30.065117Z",
     "iopub.status.busy": "2024-01-03T14:01:30.064639Z",
     "iopub.status.idle": "2024-01-03T14:01:30.153986Z",
     "shell.execute_reply": "2024-01-03T14:01:30.153535Z",
     "shell.execute_reply.started": "2024-01-03T14:01:30.065060Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok\n"
     ]
    }
   ],
   "source": [
    "import openpyxl\n",
    "import json\n",
    "\n",
    "\n",
    "wb = openpyxl.load_workbook('data/中国石化化工销售员工花名册（20231128）.xlsx')\n",
    "sheet = wb.active\n",
    "# sheets = wb.sheetnames\n",
    "person = {}\n",
    "\n",
    "for n in range(2, sheet.max_row+1):\n",
    "    if sheet.cell(n, 1).value is not None:\n",
    "        code = int(sheet.cell(n, 1).value)\n",
    "        person.setdefault(code, {})\n",
    "        dict1 = {}\n",
    "        dict1['name'] = sheet.cell(n, 2).value\n",
    "        dict1['sex'] = sheet.cell(n, 3).value\n",
    "        dict1['unit'] = sheet.cell(n, 4).value\n",
    "        dict1['id'] = sheet.cell(n,5).value\n",
    "        id = str(sheet.cell(n,5).value)\n",
    "        birth = id[6:10]+'-'+ id[10:12]+'-' +id[12:14]\n",
    "        dict1['birth'] = sheet.cell(n,9).value\n",
    "        person[code] = dict1\n",
    "filename = 'data/中国石化化工销售.json'\n",
    "with open(filename, 'w') as fl:\n",
    "    json.dump(person, fl, ensure_ascii=False)\n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "048a95aa-1691-45f6-b933-6eaf95ae1d30",
   "metadata": {},
   "source": [
    "## 生成读卡系统文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ce406710-6b7d-4c51-98ec-78883bd3ce5f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-28T02:32:36.887442Z",
     "iopub.status.busy": "2023-11-28T02:32:36.887196Z",
     "iopub.status.idle": "2023-11-28T02:32:36.893879Z",
     "shell.execute_reply": "2023-11-28T02:32:36.893384Z",
     "shell.execute_reply.started": "2023-11-28T02:32:36.887424Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "\n",
    "filename = 'data/中国石化化工销售.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "list1 = []\n",
    "for k, v in dict1.items():\n",
    "    dict2 = {}\n",
    "    #if dict1['sex'] =='男':\n",
    "    #    sex = 1\n",
    "    \n",
    "    dict2 = {'id':k,'name':v['name'],'gender':v['sex'],'birth':v['birth'],'unit':v['unit']}\n",
    "    list1.append(dict2)\n",
    "json_data = json.dumps(list1,ensure_ascii=False, indent=4)  \n",
    "\n",
    "# 将 json 数据写入文件\n",
    "with open(\"data/data_中国石化化工销售.json\", \"w\",encoding = 'utf-8') as file:\n",
    "    file.write(json_data)   \n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bcd45c2-10af-4d5f-9e0b-5cd1df4f7a7f",
   "metadata": {},
   "source": [
    "## 获取人员测试成绩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "970e171e-1360-448f-a28c-520ccb8f314a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-10-18T02:17:23.733390Z",
     "iopub.status.busy": "2023-10-18T02:17:23.733131Z",
     "iopub.status.idle": "2023-10-18T02:17:23.758353Z",
     "shell.execute_reply": "2023-10-18T02:17:23.757550Z",
     "shell.execute_reply.started": "2023-10-18T02:17:23.733366Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "141\n",
      "141\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import time\n",
    "import csv\n",
    "\n",
    "filename = '../item.json'\n",
    "item = {}\n",
    "unit = {}\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl) \n",
    "for k,v in dict1.items():\n",
    "    item[k] = v\n",
    "re_ta = {}\n",
    "dict1 = {}\n",
    "list1 = []\n",
    "filename = 'data/北京党校.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl) \n",
    "\n",
    "filename = 'data/places_result_20231018.csv'\n",
    "with open(filename,'r',newline='') as csv_file:\n",
    "    fl = csv.reader(csv_file,delimiter=',')\n",
    "    header = next(fl)    \n",
    "    for line in fl:\n",
    "        #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
    "        list1.append(line)\n",
    "#print(list1)\n",
    "for result in list1:\n",
    "    user = str(result[2])\n",
    "    if user in dict1.keys():        \n",
    "        m_item = str(result[3])    \n",
    "        re_ta.setdefault(user,{})    \n",
    "        re_ta[user]['name'] = dict1[user]['name']\n",
    "        re_ta[user]['sex'] = dict1[user]['sex'] \n",
    "        re_ta[user]['unit'] = dict1[user]['unit']\n",
    "        item_name = item[m_item]['name']\n",
    "        re_ta[user].setdefault(item_name,{})  \n",
    "        score = int(result[4])/item[m_item]['divisor']    \n",
    "        re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
    "print(len(re_ta))\n",
    "filename = 'data/result_北京党校.json'\n",
    "\n",
    "with open(filename,'w') as fl:\n",
    "    json.dump(re_ta, fl, ensure_ascii=False) \n",
    "print(len(re_ta))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d034a61d-1fbd-417b-99bd-277e43ebb678",
   "metadata": {},
   "source": [
    "## 导出测试人员信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "867ad6b0-9e9d-48bc-a10a-3b9cb6125890",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import openpyxl\n",
    "\n",
    "items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
    "title = ['编号','姓名','性别','单位','部门','身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
    "\n",
    "filename = 'data/result_北京党校.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "\n",
    "filename = 'data/北京党校.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict2 = json.load(fl)\n",
    "    \n",
    "list1 = []\n",
    "for k, v in dict1.items():\n",
    "    list2 = []\n",
    "    list2.append(str(k).rjust(5,'0'))\n",
    "    list2.append(v['name'])    \n",
    "    list2.append(dict2[k]['sex'])\n",
    "    list2.append(dict2[k]['unit'])\n",
    "    for item in items:\n",
    "        if item in v.keys():\n",
    "            list2.append(v[item]['成绩']) \n",
    "        elif item =='name':\n",
    "            list2.append(v[item])\n",
    "        else:\n",
    "            list2.append('') \n",
    "    list1.append(list2)\n",
    "filename = 'data/北京党校.xlsx'\n",
    "wb = openpyxl.Workbook()\n",
    "sheet = wb.active\n",
    "sheet.append(title)\n",
    "for row in list1:\n",
    "    sheet.append(row)\n",
    "    \n",
    "wb.save(filename)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "699c6a40-a6ae-4300-9646-708cb85aa5e8",
   "metadata": {},
   "source": [
    "## 手工数据导入数据库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "def3f47a-24ef-4815-b63b-2a16b79b4c15",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import openpyxl\n",
    "import json\n",
    "\n",
    "filename = 'data/北京党校.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict2 = json.load(fl)\n",
    "wb = openpyxl.load_workbook('data/北京党校手工数据.xlsx')\n",
    "sheet = wb.active\n",
    "# sheets = wb.sheetnames\n",
    "dict1 = {}\n",
    "dict3 = {1:10,2:11,3:7,4:2,5:6,6:3,7:1}\n",
    "sheet = wb.active\n",
    "data1 =list(sheet.values)\n",
    "del data1[0]\n",
    "list1 = []\n",
    "for item in data1:\n",
    "    code = int(item[0])\n",
    "    list1.append((496534,code,item[2],item[1],'2023-10-15','2023-10-15 14:00:00'))\n",
    "print(list1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "67e63f07-3f20-4e0e-9c07-7bf6024eeb4b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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