{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ae533fe9-e20e-4e44-b9bb-030c4fa4e714",
   "metadata": {},
   "source": [
    "## 体测人员导入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1144aaac-92a0-4bcf-aba7-096f7dd3ad3b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import openpyxl\n",
    "import json\n",
    "\n",
    "\n",
    "wb = openpyxl.load_workbook('data/天津石化员工检测花名册 （20221014）.xlsx')\n",
    "sheet = wb.active\n",
    "# sheets = wb.sheetnames\n",
    "person = {}\n",
    "\n",
    "for n in range(2, sheet.max_row+1):\n",
    "    code = int(sheet.cell(n, 6).value)\n",
    "    person.setdefault(code, {})\n",
    "    dict1 = {}\n",
    "    dict1['name'] = sheet.cell(n, 3).value\n",
    "    dict1['sex'] = sheet.cell(n, 4).value\n",
    "    dict1['unit'] = sheet.cell(n, 1).value\n",
    "    dict1['sub_unit'] = sheet.cell(n, 2).value\n",
    "    if sheet.cell(n,5).value is not None:\n",
    "        dict1['id_num'] = sheet.cell(n,5).value\n",
    "    person[code] = dict1\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename, 'w') as fl:\n",
    "    json.dump(person, fl, ensure_ascii=False)\n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e648b69-40bf-4494-9079-e4e2b6ab8866",
   "metadata": {},
   "source": [
    "## 获取人员测试成绩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a57ebb22-543c-4804-8d44-89984058ec1d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "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",
    "#SQL语句为：\n",
    "#SELECT a.item_id,a.performance,a.score,a.date AS DATE1,a.avatar_id,b.unit,b.name,a.date_joined FROM places_result AS a,_tianjin AS b WHERE a.place_id=134 AND a.avatar_id=b.id\n",
    "\n",
    "re_ta = {}\n",
    "dict1 = {}\n",
    "list1 = []\n",
    "#print(\"\\n运动项目信息：\")\n",
    "filename = 'data/134_2210.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[4])\n",
    "    m_item = str(result[0])    \n",
    "    re_ta.setdefault(user,{})    \n",
    "    re_ta[user]['name'] = str(result[6])\n",
    "    re_ta[user]['unit'] = str(result[5])    \n",
    "    item_name = item[m_item]['name']\n",
    "    re_ta[user].setdefault(item_name,{})  \n",
    "    score = int(result[1])/item[m_item]['divisor']    \n",
    "    re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
    "    re_ta[user][item_name]['得分'] =result[2]\n",
    "filename = 'data/result_天津.json'\n",
    "with open(filename,'w') as fl:\n",
    "    json.dump(re_ta, fl) \n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55d961e5-a512-44b2-808e-7c55d7000d52",
   "metadata": {},
   "source": [
    "## 导出测试成绩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "38397ad4-2bb3-4b5e-8ece-9ea11e801890",
   "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','车间/科室','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",
    "filename = 'data/result_天津.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "\n",
    "filename = 'data/天津石化人员名单.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(8,'0'))\n",
    "    list2.append(v['name'])    \n",
    "    list2.append(dict2[k]['sex'])\n",
    "    list2.append(dict2[k]['unit'])\n",
    "    list2.append(dict2[k]['sub_unit'])\n",
    "    \n",
    "    for item in items:\n",
    "        if item in v.keys():\n",
    "            list2.append(v[item]['成绩'])\n",
    "            \n",
    "        elif item =='name':\n",
    "            list2.append(v[item])\n",
    "        else:\n",
    "            list2.append('') \n",
    "            \n",
    "    list1.append(list2)\n",
    "filename = 'data/天津石化体测情况表（截至20221122）.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": "239ceb76-f690-4dae-991c-62c38d617c85",
   "metadata": {},
   "source": [
    "## 导出测试成绩(带得分)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "27529013-f3de-4e23-980d-f62203e4df88",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-30T10:12:53.515296Z",
     "iopub.status.busy": "2022-11-30T10:12:53.514432Z",
     "iopub.status.idle": "2022-11-30T10:12:55.337907Z",
     "shell.execute_reply": "2022-11-30T10:12:55.337125Z",
     "shell.execute_reply.started": "2022-11-30T10:12:53.515185Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok\n"
     ]
    }
   ],
   "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','车间/科室','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",
    "filename = 'data/result_天津.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict2 = json.load(fl)\n",
    "    \n",
    "list1 = []\n",
    "for k, v in dict1.items():\n",
    "    #print(k,dict2[str(k)]['name'])\n",
    "    list2 = []\n",
    "    list2.append(str(k).rjust(5,'0'))\n",
    "    list2.append(dict2[k]['name'])    \n",
    "    list2.append(dict2[k]['sex'])\n",
    "    list2.append(dict2[k]['unit'])    \n",
    "    list2.append(dict2[k]['sub_unit']) \n",
    "    for item in items:\n",
    "        if item in dict1[k].keys():\n",
    "            list2.append(dict1[k][item]['成绩'])\n",
    "            list2.append(dict1[k][item]['得分'])   \n",
    "        elif item =='name':\n",
    "            list2.append(dict1[k][item])\n",
    "        else:\n",
    "            list2.append('') \n",
    "            list2.append('') \n",
    "    list1.append(list2)\n",
    "filename = 'data/天津石化体测情况表.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)\n",
    "print('ok')    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c7b219f-43cd-4bf0-971f-2c398f8db8ed",
   "metadata": {},
   "source": [
    "## 按照日期进行报告分类"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d57ff66-69c3-4c13-811b-f1e13b404077",
   "metadata": {},
   "source": [
    "### 按照体测明细分类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29c0f15b-1345-4b46-ac1d-b45ddede9641",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import time\n",
    "import csv\n",
    "import os,sys,shutil\n",
    "import glob\n",
    "\n",
    "dict1 = {}\n",
    "list1 = []\n",
    "filename = 'data/134_2210.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",
    "for result in list1:\n",
    "    user = str(result[4])\n",
    "    dict1.setdefault(user,'2022-10-01')\n",
    "    m_date = result[7]\n",
    "    if m_date> dict1[user]:\n",
    "        dict1[user] = m_date\n",
    "\n",
    "m_path = 'file/134'\n",
    "\n",
    "fls = glob.glob(f'file/new/*.pdf')\n",
    "for fn in fls:\n",
    "    #old = os.path.basename(fn).split('.')[0].rjust(8,'0') \n",
    "    old = os.path.basename(fn).split('.')[0]\n",
    "    mrq = str(dict1[old]).split(' ')[0].replace('-', '', 2)\n",
    "    if not os.path.exists(m_path + '/new/' + mrq):\n",
    "        os.mkdir(m_path + '/new/' + mrq)\n",
    "    n_name = f'{m_path}/new/{mrq}/{str(old).rjust(8,\"0\")}_{mrq}.pdf'\n",
    "    if not os.path.exists(n_name):\n",
    "        shutil.copyfile(fn,n_name)\n",
    "print('ok!')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae2b17bd-38b9-4809-affb-01441a5581eb",
   "metadata": {},
   "source": [
    "### 按照报告生成日期分类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb24c1be-b5d3-4e61-a432-854a887746d4",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import time\n",
    "import csv\n",
    "import os,sys,shutil\n",
    "import glob\n",
    "\n",
    "dict1 = {}\n",
    "list1 = []\n",
    "\n",
    "m_path = 'file/134'\n",
    "mrq = '20221028'\n",
    "if not os.path.exists(m_path + '/' + mrq):\n",
    "    os.mkdir(m_path + '/' + mrq)\n",
    "fls = glob.glob(f'file/new/*.pdf')\n",
    "for fn in fls:\n",
    "    #old = os.path.basename(fn).split('.')[0].rjust(8,'0') \n",
    "    old = os.path.basename(fn).split('.')[0]    \n",
    "    n_name = f'{m_path}/{mrq}/{str(old).rjust(8,\"0\")}_{mrq}.pdf'\n",
    "    if not os.path.exists(n_name):\n",
    "        shutil.copyfile(fn,n_name)\n",
    "print('ok!')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9061d26-b09b-4bff-af24-a14adda3d83f",
   "metadata": {},
   "source": [
    "## 按照部门报告分组"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7ea2541f-461f-4eb5-860d-4b56d6be74ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os,sys,shutil\n",
    "import json\n",
    "import math\n",
    "import glob\n",
    "from pathlib import Path\n",
    "\n",
    "fi_path = './file'\n",
    "old = []\n",
    "dict2 = {}\n",
    "\n",
    "\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "\n",
    "for k, v in dict1.items():\n",
    "    m_name = v['name']\n",
    "    m_depart = v['unit']    \n",
    "    dict2[int(k)] = [m_name,m_depart]\n",
    "\n",
    "\n",
    "\n",
    "fls = glob.glob(f'./file/*.pdf')\n",
    "\n",
    "for fn in fls:\n",
    "    old.append(os.path.basename(fn).split('.')[0])\n",
    "    #print(fn)\n",
    "\n",
    "\n",
    "for n in old:    \n",
    "    o_name = f'{fi_path}/{n}.pdf'\n",
    "    if not os.path.exists(f'{fi_path}/new/{dict2[int(n)][1]}'):\n",
    "        os.mkdir(f'{fi_path}/new/{dict2[int(n)][1]}') \n",
    "    n_name = f'{fi_path}/new/{dict2[int(n)][1]}/{str(n).rjust(5,\"0\")}-{dict2[int(n)][0]}.pdf'\n",
    "    if not os.path.exists(n_name):\n",
    "        shutil.copyfile(o_name,n_name)\n",
    "        print(n_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63eb8a23-4876-4be6-8800-1a67df8773ff",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os,sys,shutil\n",
    "import json\n",
    "import math\n",
    "import glob\n",
    "from pathlib import Path\n",
    "\n",
    "fi_path = './file'\n",
    "old = []\n",
    "dict2 = {}\n",
    "\n",
    "\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "\n",
    "for k, v in dict1.items():\n",
    "    m_name = v['name']\n",
    "    m_depart = v['unit']    \n",
    "    dict2[int(k)] = [m_name,m_depart]\n",
    "\n",
    "\n",
    "\n",
    "fls = glob.glob(f'./file/*.pdf')\n",
    "\n",
    "for fn in fls:\n",
    "    old.append(os.path.basename(fn).split('.')[0])\n",
    "\n",
    "for n in old:    \n",
    "    o_name = f'{fi_path}/{n}.pdf'\n",
    "    new_path = Path('file/new',dict1[n]['unit'],dict1[n]['sub_unit'])\n",
    "    new_path.mkdir(parents = True, exist_ok = True)\n",
    "    n_name = Path(new_path,f'{str(n).rjust(7,\"0\")}-{dict2[int(n)][0]}.pdf')\n",
    "    if not os.path.exists(n_name):\n",
    "        shutil.copyfile(o_name,n_name)\n",
    "        print(n_name)\n",
    "    \n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4590323-6645-450a-8055-756a5bf35b34",
   "metadata": {},
   "source": [
    "## 统计报告人员信息表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ed681a0d-4ee8-48ec-ab05-23da7156a44e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-26T18:05:46.062534Z",
     "iopub.status.busy": "2022-11-26T18:05:46.062001Z",
     "iopub.status.idle": "2022-11-26T18:05:46.353459Z",
     "shell.execute_reply": "2022-11-26T18:05:46.352749Z",
     "shell.execute_reply.started": "2022-11-26T18:05:46.062456Z"
    }
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import openpyxl\n",
    "import os\n",
    "import glob\n",
    "\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "m_path ='./file'\n",
    "fls = glob.glob(f'file/*.pdf')\n",
    "list1 = []\n",
    "for fn in fls:\n",
    "    list2 = []\n",
    "    code = os.path.basename(fn).split('.')[0]\n",
    "    list2 = [code.rjust(7,\"0\"),dict1[code]['name'],dict1[code]['unit'],dict1[code]['sub_unit']]\n",
    "    list1.append(list2)\n",
    "title = ['编号','姓名','单位/部门','车间/科室',]    \n",
    "filename = 'data/天津石化体测情况表.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": "838ec7d3-137c-4ccd-9f16-7b6312d1ffa6",
   "metadata": {},
   "source": [
    "## PDF文件压缩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a6ab0943-b018-4dd6-9176-85a762f9f60c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import fitz\n",
    "from pdf2image import convert_from_path, convert_from_bytes\n",
    "import os,sys\n",
    "import tempfile\n",
    "from pdf2image.exceptions import (\n",
    "    PDFInfoNotInstalledError,\n",
    "    PDFPageCountError,\n",
    "    PDFSyntaxError\n",
    ")\n",
    "import img2pdf  \n",
    "import glob\n",
    "import shutil\n",
    "\n",
    "def covert2pic(old_fn):\n",
    "    if os.path.exists('.pdf'):       # 临时文件，需为空\n",
    "         shutil.rmtree('.pdf')\n",
    "    os.mkdir('.pdf')\n",
    "    with tempfile.TemporaryDirectory() as path:\n",
    "        images_from_path = convert_from_path(old_fn, dpi=100,fmt='jpg', output_folder='.pdf')\n",
    "\n",
    "def pic2pdf(new_fn):\n",
    "    fl1=glob.glob('.pdf/*.jpg')\n",
    "    fl1.sort()\n",
    "    a4inpt = (img2pdf.mm_to_pt(210),img2pdf.mm_to_pt(297))\n",
    "    layout_fun = img2pdf.get_layout_fun(a4inpt)\n",
    "    with open(new_fn,\"wb\") as f:\n",
    "        f.write(img2pdf.convert(fl1,layout_fun=layout_fun))\n",
    "    print(f'{new_fn}转换成功！')\n",
    "    \n",
    "\n",
    "\n",
    "def pdfz(sor, obj, zoom):    \n",
    "    covert2pic(zoom)\n",
    "    pic2pdf(obj)\n",
    "    \n",
    "fi_path = 'file/134/20221122/'\n",
    "fl = glob.glob(f'{fi_path}*.pdf')\n",
    "\n",
    "for fn in fl:\n",
    "    new_fn = fi_path+'new/'+os.path.basename(fn)\n",
    "    covert2pic(fn)\n",
    "    pic2pdf(new_fn)\n",
    "    shutil.rmtree('.pdf')\n",
    "print('ok!')\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0cc9662-4171-4c2a-828d-f58c327ec8c1",
   "metadata": {},
   "source": [
    "## 统计未测试人员名单"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "daef91be-1b58-4fb1-b182-64f43c07c90f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import openpyxl\n",
    "\n",
    "title = ['编号','姓名','性别','单位/部门','车间/科室']\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "filename = 'data/result_天津.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",
    "    if k not in dict2.keys():        \n",
    "        list2 = [k,dict1[k]['name'],dict1[k]['sex'],dict1[k]['unit'],dict1[k]['sub_unit'],] \n",
    "        list1.append(list2)\n",
    "filename = 'data/天津石化未参加体测人数统计表.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)\n",
    "print('ok!')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72c693e1-dd7c-40fa-8948-4fd6fbea8ddc",
   "metadata": {},
   "source": [
    "## 区分新文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9d06d4f0-364b-438c-844b-7d5badaf3496",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os,sys,shutil\n",
    "import glob\n",
    "import time\n",
    "\n",
    "fi_path = 'file/'\n",
    "fls = glob.glob(f'{fi_path}*.pdf')\n",
    "m_date = time.strptime('2022-10-28','%Y-%m-%d')\n",
    "for fn in fls:\n",
    "    c_time = time.gmtime(os.path.getctime(fn))\n",
    "    if c_time > m_date:\n",
    "        n_name = f'{fi_path}new/{os.path.basename(fn)}'\n",
    "        if not os.path.exists(n_name):\n",
    "            shutil.copyfile(fn,n_name)\n",
    "        print(n_name)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32b61559-4495-4fbe-8eb6-2614e6225b5c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import openpyxl\n",
    "\n",
    "title = ['编号','姓名','性别','单位/部门','车间/科室']\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "filename = 'data/result_天津.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict2 = json.load(fl)\n",
    "print(len(dict2),len(dict1),)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47015abe-4cb8-436b-afa5-9ffd78d4a628",
   "metadata": {},
   "source": [
    "## 心理测试情况统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c21efc40-2639-4b22-851f-925cd3f12d3a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-02T01:57:12.001357Z",
     "iopub.status.busy": "2022-12-02T01:57:12.001077Z",
     "iopub.status.idle": "2022-12-02T01:57:12.883178Z",
     "shell.execute_reply": "2022-12-02T01:57:12.882427Z",
     "shell.execute_reply.started": "2022-12-02T01:57:12.001330Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok!\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import openpyxl\n",
    "\n",
    "title = ['编号','姓名','性别','单位/部门','车间/科室']\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "filename = 'data/134_xinli.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[4])\n",
    "list3 = []\n",
    "for k, v in dict1.items():\n",
    "    list2 = []\n",
    "    if k not in list1:        \n",
    "        list2 = [k,dict1[k]['name'],dict1[k]['sex'],dict1[k]['unit'],dict1[k]['sub_unit'],] \n",
    "        list3.append(list2)\n",
    "filename = 'data/天津石化未参加心理测试人数统计表.xlsx'\n",
    "wb = openpyxl.Workbook()\n",
    "sheet = wb.active\n",
    "sheet.append(title)\n",
    "for row in list3:\n",
    "    sheet.append(row)\n",
    "    \n",
    "wb.save(filename)\n",
    "print('ok!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6b8ae75d-71a3-4cbe-a216-03c28d78156c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-12-02T01:52:28.990631Z",
     "iopub.status.busy": "2022-12-02T01:52:28.990331Z",
     "iopub.status.idle": "2022-12-02T01:52:29.019041Z",
     "shell.execute_reply": "2022-12-02T01:52:29.018243Z",
     "shell.execute_reply.started": "2022-12-02T01:52:28.990609Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1731990\n",
      "1730445\n",
      "1733543\n",
      "3402384\n",
      "1732997\n",
      "1737697\n",
      "1730575\n",
      "1730370\n",
      "1739948\n",
      "3442741\n",
      "1730359\n",
      "3362198\n",
      "3417263\n",
      "1730439\n",
      "1733749\n",
      "3440898\n",
      "1730989\n",
      "1730356\n",
      "1735371\n",
      "1732814\n",
      "1730913\n",
      "1736882\n",
      "1733497\n",
      "3362212\n",
      "1731589\n",
      "1739001\n",
      "1731819\n",
      "1732459\n",
      "3125774\n",
      "1730902\n",
      "3362662\n",
      "1731856\n",
      "1737990\n",
      "3125699\n",
      "3317857\n",
      "1730219\n",
      "1732471\n",
      "3317863\n",
      "1734383\n",
      "3499245\n",
      "1739589\n",
      "1733813\n",
      "3499240\n",
      "1734246\n",
      "3125710\n",
      "3499237\n",
      "3499243\n",
      "3499253\n",
      "1739362\n",
      "3428692\n",
      "1739050\n",
      "1737160\n",
      "1732665\n",
      "3287806\n",
      "1731058\n",
      "1733868\n",
      "1733867\n",
      "1731561\n",
      "3374924\n",
      "3167516\n",
      "3287818\n",
      "3422008\n",
      "1734221\n",
      "1733715\n",
      "3428694\n",
      "1734188\n",
      "1536861\n",
      "3125698\n",
      "1730538\n",
      "3428695\n",
      "3499244\n",
      "1732461\n",
      "1739419\n",
      "3499257\n",
      "1735528\n",
      "3252962\n",
      "1534670\n",
      "3125708\n",
      "1736685\n",
      "3317910\n",
      "3287811\n",
      "3499250\n",
      "3499252\n",
      "1733962\n",
      "1732064\n",
      "1532672\n",
      "1735489\n",
      "1732061\n",
      "1736599\n",
      "1736711\n",
      "1738767\n",
      "1739302\n",
      "1733200\n",
      "1733921\n",
      "1739427\n",
      "1730169\n",
      "1739308\n",
      "1535224\n",
      "3145487\n",
      "3452129\n",
      "3391160\n",
      "1532563\n",
      "1730119\n",
      "1732176\n",
      "3362572\n",
      "3394990\n",
      "1739239\n",
      "1730527\n",
      "3145535\n",
      "3362148\n",
      "3417105\n",
      "1735004\n",
      "1730099\n",
      "1738145\n",
      "3417344\n",
      "3391150\n",
      "1735011\n",
      "1739366\n",
      "1733562\n",
      "1736119\n",
      "3468164\n",
      "1735730\n",
      "3286619\n",
      "1738273\n",
      "3440494\n",
      "1736766\n",
      "1738693\n",
      "3440490\n",
      "1738688\n",
      "1736104\n",
      "1730461\n",
      "3499700\n",
      "1739760\n",
      "1121028\n",
      "1731513\n",
      "1732257\n",
      "1731552\n",
      "1122144\n",
      "1738750\n",
      "1737455\n",
      "3499719\n",
      "1736319\n",
      "1736146\n",
      "1736909\n",
      "3499696\n",
      "1731467\n",
      "1732266\n",
      "1732170\n",
      "1731539\n",
      "3362183\n",
      "3499712\n",
      "1731534\n",
      "1731510\n",
      "1731532\n",
      "1731442\n",
      "1739826\n",
      "1731524\n",
      "3318695\n",
      "1731469\n",
      "1736750\n",
      "3499705\n",
      "1731444\n",
      "3468014\n",
      "3499693\n",
      "1731476\n",
      "3499702\n",
      "3440472\n",
      "1731514\n",
      "3499691\n",
      "1730766\n",
      "1731487\n",
      "1733004\n",
      "1732263\n",
      "1732815\n",
      "1088006\n",
      "1731509\n",
      "1734184\n",
      "1731511\n",
      "1731443\n",
      "3499708\n",
      "1730580\n",
      "1731540\n",
      "1731449\n",
      "3286600\n",
      "3468152\n",
      "3468033\n",
      "1731535\n",
      "1731520\n",
      "3145577\n",
      "1731545\n",
      "1732809\n",
      "3440496\n",
      "1733354\n",
      "1731461\n",
      "1733157\n",
      "3442666\n",
      "3499720\n",
      "1731472\n",
      "1732805\n",
      "1737993\n",
      "1731500\n",
      "1739223\n",
      "3499710\n",
      "3499718\n",
      "1731496\n",
      "1732808\n",
      "1730648\n",
      "1731459\n",
      "3499689\n",
      "1731529\n",
      "1731956\n",
      "1731457\n",
      "1731471\n",
      "1738961\n",
      "1731502\n",
      "1739835\n",
      "1732803\n",
      "1736917\n",
      "1731386\n",
      "1731935\n",
      "1738682\n",
      "3468160\n",
      "1732253\n",
      "3168143\n",
      "3318687\n",
      "1737044\n",
      "1731489\n",
      "1730524\n",
      "1739289\n",
      "1730599\n",
      "1731477\n",
      "3468147\n",
      "3468012\n",
      "1736728\n",
      "1731497\n",
      "1731773\n",
      "1731468\n",
      "3287821\n",
      "1732921\n",
      "1731463\n",
      "1736129\n",
      "1121117\n",
      "1730586\n",
      "1730522\n",
      "1736757\n",
      "1730550\n",
      "3499711\n",
      "3468183\n",
      "1731486\n",
      "1738690\n",
      "1730470\n",
      "1730593\n",
      "1731464\n",
      "1738669\n",
      "1736743\n",
      "3499715\n",
      "1738641\n",
      "1732807\n",
      "1736794\n",
      "1736798\n",
      "1731465\n",
      "1738668\n",
      "1732269\n",
      "1730468\n",
      "3145776\n",
      "1730649\n",
      "1730612\n",
      "1739417\n",
      "1732802\n",
      "1736729\n",
      "3468010\n",
      "1736755\n",
      "1730639\n",
      "1731479\n",
      "1738245\n",
      "1731538\n",
      "3499695\n",
      "1731491\n",
      "1739006\n",
      "1730962\n",
      "3440495\n",
      "1730616\n",
      "1731537\n",
      "1730430\n",
      "1730163\n",
      "1732804\n",
      "1731518\n",
      "1733541\n",
      "1731221\n",
      "1731478\n",
      "1731840\n",
      "1737054\n",
      "1738505\n",
      "1730052\n",
      "3391167\n",
      "3440899\n",
      "1088010\n",
      "1730578\n",
      "3468015\n",
      "1731482\n",
      "1732252\n",
      "1738654\n",
      "1730230\n",
      "1730267\n",
      "1732164\n",
      "1731875\n",
      "1730519\n",
      "1733549\n",
      "1739010\n",
      "1739125\n",
      "1738942\n",
      "1737065\n",
      "1732810\n",
      "3468042\n",
      "1730244\n",
      "1730256\n",
      "1736505\n",
      "3145483\n",
      "1731951\n",
      "1739918\n",
      "1733503\n",
      "1738877\n",
      "1738999\n",
      "1731536\n",
      "1739924\n",
      "1732784\n",
      "1738890\n",
      "1738673\n",
      "1736841\n",
      "1732682\n",
      "1738542\n",
      "1739011\n",
      "1733733\n",
      "1740092\n",
      "1734764\n",
      "1739014\n",
      "1739812\n",
      "1735318\n",
      "1730650\n",
      "1738495\n",
      "1740086\n",
      "1730656\n",
      "1738891\n",
      "3499698\n",
      "1730657\n",
      "1739242\n",
      "1730584\n",
      "1730651\n",
      "1730581\n",
      "1731525\n",
      "3499703\n",
      "1730592\n",
      "1739005\n",
      "1738876\n",
      "1730630\n",
      "1730108\n",
      "3145594\n",
      "1730589\n",
      "1730611\n",
      "1733725\n",
      "1736884\n",
      "3468184\n",
      "3362172\n",
      "3362657\n",
      "1737052\n",
      "1738861\n",
      "1735247\n",
      "3362161\n",
      "1738700\n",
      "1733559\n",
      "1730239\n",
      "1739007\n",
      "3442721\n",
      "1738885\n",
      "1857524\n",
      "1731662\n",
      "1733782\n",
      "1736720\n",
      "1738998\n",
      "1730658\n",
      "1731475\n",
      "1738888\n",
      "1738889\n",
      "1730266\n",
      "3145554\n",
      "1732778\n",
      "1730467\n",
      "3499706\n",
      "3499694\n",
      "1737420\n",
      "1731904\n",
      "1740109\n",
      "1739647\n",
      "1739761\n",
      "1738835\n",
      "3468162\n",
      "1738865\n",
      "1738902\n",
      "1738915\n",
      "1735380\n",
      "1738867\n",
      "1730306\n",
      "1739810\n",
      "3145529\n",
      "1736754\n",
      "1121100\n",
      "1731531\n",
      "1738911\n",
      "1731473\n",
      "1731553\n",
      "1738538\n",
      "1730628\n",
      "1738991\n",
      "1732206\n",
      "1733427\n",
      "3499249\n",
      "1730582\n",
      "1737562\n",
      "1737618\n",
      "1738958\n",
      "1737345\n",
      "1736762\n",
      "1738968\n",
      "1739198\n",
      "1738884\n",
      "1739763\n",
      "1739161\n",
      "1738643\n",
      "1735007\n",
      "3145482\n",
      "3068728\n",
      "3499688\n",
      "1738684\n",
      "1738646\n",
      "1736320\n",
      "1738680\n",
      "1730771\n",
      "3499704\n",
      "1733518\n",
      "1738631\n",
      "1738914\n",
      "1735375\n",
      "3362186\n",
      "1738857\n",
      "3499251\n",
      "1730005\n",
      "1739121\n",
      "1730585\n",
      "3452130\n",
      "3362163\n",
      "3417166\n",
      "3467827\n",
      "1730383\n",
      "1738519\n",
      "1737605\n",
      "3417279\n",
      "1732991\n",
      "3468100\n",
      "1732698\n",
      "3442764\n",
      "1730167\n",
      "1732265\n",
      "1738869\n",
      "1737176\n",
      "1121078\n",
      "3145495\n",
      "1737454\n",
      "1738834\n",
      "3442659\n",
      "1738938\n",
      "1738937\n",
      "3145484\n",
      "3442703\n",
      "1738969\n",
      "1731523\n",
      "1738527\n",
      "3467917\n",
      "1733724\n",
      "1732002\n",
      "1731076\n",
      "1739002\n",
      "1731235\n",
      "1732144\n",
      "3318680\n",
      "1738517\n",
      "1730394\n",
      "1738903\n",
      "1731111\n",
      "1739128\n",
      "1732850\n",
      "1733502\n",
      "1733498\n",
      "1738677\n",
      "1739235\n",
      "3417267\n",
      "1732864\n",
      "1732169\n",
      "1733703\n",
      "1738882\n",
      "1732889\n",
      "1735641\n",
      "1733380\n",
      "1739944\n",
      "1731422\n",
      "1732254\n",
      "3449693\n",
      "1736753\n",
      "1733740\n",
      "1730406\n",
      "1737424\n",
      "1730621\n",
      "1737364\n",
      "1736723\n",
      "3468166\n",
      "1731289\n",
      "1738841\n",
      "1733756\n",
      "1730405\n",
      "1731501\n",
      "1739855\n",
      "1730254\n",
      "1739806\n",
      "3286601\n",
      "1733257\n",
      "1733699\n",
      "3145498\n",
      "1735003\n",
      "1733721\n",
      "31215\n",
      "1732156\n",
      "1733256\n",
      "3467834\n",
      "1731665\n",
      "3145605\n",
      "1739061\n",
      "1733146\n",
      "1055173\n",
      "1731680\n",
      "1736134\n",
      "1736160\n",
      "3442807\n",
      "1732873\n",
      "1730788\n",
      "1732871\n",
      "3442791\n",
      "3442753\n",
      "3145569\n",
      "1733493\n",
      "1732166\n",
      "1739015\n",
      "1088005\n",
      "1739220\n",
      "3145488\n",
      "3145556\n",
      "3442762\n",
      "1732904\n",
      "1088001\n",
      "1733531\n",
      "1305017\n",
      "1730653\n",
      "3468804\n",
      "3499669\n",
      "1732267\n",
      "1735436\n",
      "1736588\n",
      "1103009\n",
      "1529378\n",
      "52781\n",
      "3145452\n",
      "1730080\n",
      "3505717\n",
      "1736872\n",
      "1733742\n",
      "1736764\n",
      "1735650\n",
      "1736721\n",
      "1736585\n",
      "3499690\n",
      "3499607\n",
      "1735299\n",
      "53058\n",
      "1730386\n",
      "1738943\n",
      "3467868\n",
      "1739915\n",
      "3452127\n",
      "1736565\n",
      "1736551\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import openpyxl\n",
    "\n",
    "title = ['编号','姓名','性别','单位/部门','车间/科室']\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "list1 = []\n",
    "filename = 'data/134_xinli.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",
    "        print(line[4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5d53a23c-3fbd-4b57-926b-bc7f61a12be2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}