{
 "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 FROM places_result AS a,_zgshhgxs AS b WHERE a.place_id=135 AND a.avatar_id=b.id AND a.avatar_id < 4999\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20221103）.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": "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": "838ec7d3-137c-4ccd-9f16-7b6312d1ffa6",
   "metadata": {},
   "source": [
    "### PDF文件压缩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a6ab0943-b018-4dd6-9176-85a762f9f60c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-06T12:41:01.250512Z",
     "iopub.status.busy": "2022-11-06T12:41:01.250217Z",
     "iopub.status.idle": "2022-11-06T12:47:50.596165Z",
     "shell.execute_reply": "2022-11-06T12:47:50.595493Z",
     "shell.execute_reply.started": "2022-11-06T12:41:01.250488Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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     ]
    }
   ],
   "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/134/20221101/'\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",
    "\n",
    "\n"
   ]
  },
  {
   "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": {},
   "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
}