{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ade4f5e9-de5f-4926-8e53-c98df98e107a",
   "metadata": {},
   "source": [
    "## 体测人员导入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "43e14491-bc5c-4e73-89f0-a3ea64a15772",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-10-24T03:11:51.050015Z",
     "iopub.status.busy": "2025-10-24T03:11:51.049715Z",
     "iopub.status.idle": "2025-10-24T03:11:51.064152Z",
     "shell.execute_reply": "2025-10-24T03:11:51.063565Z",
     "shell.execute_reply.started": "2025-10-24T03:11:51.049989Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok\n"
     ]
    }
   ],
   "source": [
    "import openpyxl\n",
    "import json\n",
    "\n",
    "\n",
    "wb = openpyxl.load_workbook('data/延庆区残联.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, 1).value)\n",
    "    person.setdefault(code, {})\n",
    "    dict1 = {}\n",
    "    dict1['name'] = sheet.cell(n, 2).value\n",
    "    dict1['sex'] = sheet.cell(n, 4).value\n",
    "    dict1['unit'] = ''\n",
    "    dict1['birth'] = sheet.cell(n,3).value\n",
    "    dict1['phone'] = sheet.cell(n,6).value\n",
    "    person[code] = dict1\n",
    "filename = 'data/延庆区残联.json'\n",
    "with open(filename, 'w') as fl:\n",
    "    json.dump(person, fl, ensure_ascii=False)\n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21a07528-d09b-4ff3-a7f5-584329e9b306",
   "metadata": {},
   "source": [
    "## 获取人员测试成绩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "227b85c8-aa2d-4e48-8204-119dffb082be",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-10-24T03:11:54.253047Z",
     "iopub.status.busy": "2025-10-24T03:11:54.252120Z",
     "iopub.status.idle": "2025-10-24T03:11:54.263734Z",
     "shell.execute_reply": "2025-10-24T03:11:54.262670Z",
     "shell.execute_reply.started": "2025-10-24T03:11:54.252976Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import datetime\n",
    "import csv\n",
    "from datetime import date\n",
    "import my_module as My\n",
    "\n",
    "filename = 'data/延庆区残联.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl) \n",
    "filename = 'data/marks_20251023.csv'\n",
    "re_ta = My.get_result(filename,dict1)\n",
    "\n",
    "\n",
    "filename = 'data/result_延庆区残联.json'\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": "2b52e655-f798-45bf-8d64-6c18ba490fc4",
   "metadata": {},
   "source": [
    "## 导入手工数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8249cc9b-e5e1-475b-891c-03075c74de91",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-10-24T03:11:57.248418Z",
     "iopub.status.busy": "2025-10-24T03:11:57.247688Z",
     "iopub.status.idle": "2025-10-24T03:11:57.267994Z",
     "shell.execute_reply": "2025-10-24T03:11:57.267091Z",
     "shell.execute_reply.started": "2025-10-24T03:11:57.248356Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok\n"
     ]
    }
   ],
   "source": [
    "import openpyxl\n",
    "import json\n",
    "\n",
    "\n",
    "wb = openpyxl.load_workbook('data/延庆区残联.xlsx')\n",
    "sheet = wb.active\n",
    "# sheets = wb.sheetnames\n",
    "filename = 'data/result_延庆区残联.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl) \n",
    "\n",
    "for n in range(2, sheet.max_row+1):\n",
    "    code = str(sheet.cell(n, 1).value)\n",
    "    dict1[code].setdefault('bmi',{})\n",
    "    dict1[code]['bmi']['成绩'] = sheet.cell(n,5).value\n",
    "filename = 'data/result_延庆区残联.json'\n",
    "with open(filename, 'w') as fl:\n",
    "    json.dump(dict1, fl, ensure_ascii=False)\n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6210fa76-1e82-40c1-8ec0-0f283e00b76f",
   "metadata": {},
   "source": [
    "## 生成测试得分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2c5d6b79-83ca-4d09-a312-e965c330b09b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-10-24T03:12:38.674877Z",
     "iopub.status.busy": "2025-10-24T03:12:38.674120Z",
     "iopub.status.idle": "2025-10-24T03:12:38.682034Z",
     "shell.execute_reply": "2025-10-24T03:12:38.681602Z",
     "shell.execute_reply.started": "2025-10-24T03:12:38.674822Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok!\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import time\n",
    "import my_module as My\n",
    "\n",
    "#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n",
    "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n",
    "filename = 'data/result_延庆区残联.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict2 = json.load(fl) \n",
    "for k, v in dict2.items():\n",
    "    #print(k)\n",
    "    if v['sex'] == '男':\n",
    "        sex = 'M'\n",
    "    else:\n",
    "        sex = 'F'            \n",
    "    if 'bmi' in v.keys():\n",
    "        #bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n",
    "        bmi_data = v['bmi']['成绩']\n",
    "        data1 = {'code':k,'sex':sex,'age':v['age'],'item':'HeightWeight','result':bmi_data}\n",
    "        dict2[k]['bmi'] = {}\n",
    "        dict2[k]['bmi']['成绩'] = bmi_data\n",
    "        dict2[k]['bmi']['score'] = My.cal_bmi(data1)\n",
    "    for item_en in list_item:\n",
    "        if item_en in v.keys():            \n",
    "            data1 = {'code':k,'sex':sex,'age':v['age'],'item':item_en,'result':float(v[item_en]['成绩'].split()[0])}\n",
    "            #print(k,v['name'])\n",
    "            dict2[k][item_en]['score'] = My.cal_score(data1)\n",
    "            #print(k,v[item_en]['成绩'],cal_score(data1))\n",
    "\n",
    "filename = f'data/result_延庆区残联.json'\n",
    "with open(filename,'w') as fl:\n",
    "    json.dump(dict2,fl , ensure_ascii=False) \n",
    "print('ok!')        "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2347ea7-faca-4e54-8516-fb724f575c61",
   "metadata": {},
   "source": [
    "## 获取问卷人员信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c1317e6c-870f-42e2-8161-e101e43dcd3c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-10-24T03:12:43.927986Z",
     "iopub.status.busy": "2025-10-24T03:12:43.927674Z",
     "iopub.status.idle": "2025-10-24T03:12:43.953550Z",
     "shell.execute_reply": "2025-10-24T03:12:43.952994Z",
     "shell.execute_reply.started": "2025-10-24T03:12:43.927961Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "209 ok\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import csv\n",
    "import openpyxl\n",
    "import time\n",
    "from datetime import date\n",
    "\n",
    "\n",
    "dict1 = {}\n",
    "list1 = []\n",
    "filename = 'data/sql_20251023.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",
    "        list1.append(line)\n",
    "\n",
    "nn = 0\n",
    "for item in list1:\n",
    "    dict2 = {}\n",
    "    name = item[1]\n",
    "    phone = str(item[2])[2:]\n",
    "    birth = str(item[4])\n",
    "    content = json.loads(item[0])\n",
    "    tcm = []\n",
    "    for i in range(0,60):\n",
    "        tcm.append(0)\n",
    "    for k, v in content.items():           \n",
    "        if 'tcm' not in k:\n",
    "            dict2[k] = v\n",
    "        else:\n",
    "            i = int(k[3:])\n",
    "            tcm[i-1] = int(v)\n",
    "    \n",
    "    code = phone\n",
    "    dict1.setdefault(code,{})\n",
    "    dict1[code]['name'] = dict2['name']\n",
    "    if dict2['gender'] == 'm':\n",
    "        dict1[code]['sex'] = '男'\n",
    "    else:\n",
    "        dict1[code]['sex'] = '女'\n",
    "    dict1[code]['birth'] = str(item[4])\n",
    "    \n",
    "    \n",
    "    dict1[code]['tcm'] = tcm\n",
    "filename = 'data/survey_延庆区残联.json'\n",
    "\n",
    "with open(filename,'w') as fl:\n",
    "    json.dump(dict1, fl, ensure_ascii=False)\n",
    "print(len(dict1),'ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4ad071e-286a-4516-9098-cd7f657cb403",
   "metadata": {},
   "source": [
    "## 导入问卷信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b4a2d6e5-5954-43c0-b744-f8e4a94b3447",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-10-24T03:12:46.927452Z",
     "iopub.status.busy": "2025-10-24T03:12:46.927194Z",
     "iopub.status.idle": "2025-10-24T03:12:46.935712Z",
     "shell.execute_reply": "2025-10-24T03:12:46.935211Z",
     "shell.execute_reply.started": "2025-10-24T03:12:46.927431Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok!\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import openpyxl\n",
    "\n",
    "\n",
    "filename = 'data/survey_延庆区残联.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "\n",
    "filename = 'data/result_延庆区残联.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict2 = json.load(fl)\n",
    "\n",
    "for k, v in dict2.items():\n",
    "    phone = str(v['phone'])\n",
    "    if phone in dict1.keys():\n",
    "        dict2[k]['tcm'] = dict1[phone]['tcm']\n",
    "filename = f'data/result_延庆区残联.json'\n",
    "with open(filename,'w') as fl:\n",
    "    json.dump(dict2,fl , ensure_ascii=False) \n",
    "print('ok!')        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1168c2a9-128a-4252-8ab9-961eae0c0500",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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