diff --git a/体测单位/体质检测数据处理.ipynb b/体测单位/体质检测数据处理.ipynb
index 31f4472..79afeb0 100644
--- a/体测单位/体质检测数据处理.ipynb
+++ b/体测单位/体质检测数据处理.ipynb
@@ -2376,15 +2376,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "id": "6f9768ce-2ef5-4253-9fc6-49dbdcf00a19",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-09-16T02:05:51.668240Z",
-     "iopub.status.busy": "2025-09-16T02:05:51.667590Z",
-     "iopub.status.idle": "2025-09-16T02:05:51.678339Z",
-     "shell.execute_reply": "2025-09-16T02:05:51.677348Z",
-     "shell.execute_reply.started": "2025-09-16T02:05:51.668169Z"
+     "iopub.execute_input": "2025-09-22T12:52:59.350814Z",
+     "iopub.status.busy": "2025-09-22T12:52:59.350137Z",
+     "iopub.status.idle": "2025-09-22T12:52:59.367870Z",
+     "shell.execute_reply": "2025-09-22T12:52:59.366720Z",
+     "shell.execute_reply.started": "2025-09-22T12:52:59.350750Z"
     }
    },
    "outputs": [],
@@ -2752,15 +2752,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "id": "9ecd3ad8-c8af-4f3e-90e5-1618fea905a4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-09-16T02:06:01.244917Z",
-     "iopub.status.busy": "2025-09-16T02:06:01.244267Z",
-     "iopub.status.idle": "2025-09-16T02:06:01.629798Z",
-     "shell.execute_reply": "2025-09-16T02:06:01.629334Z",
-     "shell.execute_reply.started": "2025-09-16T02:06:01.244858Z"
+     "iopub.execute_input": "2025-09-22T12:54:30.458387Z",
+     "iopub.status.busy": "2025-09-22T12:54:30.457853Z",
+     "iopub.status.idle": "2025-09-22T12:54:30.653511Z",
+     "shell.execute_reply": "2025-09-22T12:54:30.653048Z",
+     "shell.execute_reply.started": "2025-09-22T12:54:30.458336Z"
     }
    },
    "outputs": [],
@@ -2768,7 +2768,7 @@
     "import openpyxl\n",
     "\n",
     "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n",
-    "filename = 'data/result_北海炼化2023.json'\n",
+    "filename = 'data/result_通用技术中国医药-1.json'\n",
     "with open(filename,'r') as fl:\n",
     "    dict1 = json.load(fl) \n",
     "data_list = []\n",
@@ -2850,7 +2850,7 @@
     "            list6.append('')\n",
     "            i+=1\n",
     "    data_list.append(list6)\n",
-    "filename = 'data/北海炼化测试情况表2023.xlsx'\n",
+    "filename = 'data/通用技术中国医药.xlsx'\n",
     "wb = openpyxl.Workbook()\n",
     "sheet = wb.active\n",
     "#sheet.append(title)\n",
diff --git a/体测单位/南京化工.ipynb b/体测单位/南京化工.ipynb
index 3874abd..693e1ec 100644
--- a/体测单位/南京化工.ipynb
+++ b/体测单位/南京化工.ipynb
@@ -10,33 +10,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "bbba6efc-73cd-4db6-bae7-014724fee731",
    "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T02:05:09.966940Z",
+     "iopub.status.busy": "2025-10-21T02:05:09.966195Z",
+     "iopub.status.idle": "2025-10-21T02:05:10.249499Z",
+     "shell.execute_reply": "2025-10-21T02:05:10.248277Z",
+     "shell.execute_reply.started": "2025-10-21T02:05:09.966870Z"
+    },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "270 ok\n"
+     ]
+    }
+   ],
    "source": [
     "import openpyxl\n",
     "import json\n",
     "\n",
     "\n",
-    "wb = openpyxl.load_workbook('data/南化人员信息表.xlsx',data_only=True)\n",
+    "wb = openpyxl.load_workbook('data/胜利采油厂人员名单.xlsx',data_only=True)\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, 4).value)\n",
+    "    code = int(sheet.cell(n, 2).value)\n",
     "    person.setdefault(code, {})\n",
     "    dict1 = {}\n",
-    "    dict1['name'] = sheet.cell(n, 3).value\n",
+    "    dict1['name'] = sheet.cell(n, 4).value\n",
     "    dict1['sex'] = sheet.cell(n, 5).value\n",
-    "    dict1['unit'] = sheet.cell(n, 2).value    \n",
+    "    dict1['unit'] = sheet.cell(n, 3).value    \n",
     "    dict1['birth'] = str(sheet.cell(n, 6).value).replace('/','-').split(' ')[0]\n",
-    "    dict1['phone'] = sheet.cell(n, 12).value \n",
+    "    #dict1['phone'] = sheet.cell(n, 12).value \n",
     "    person[code] = dict1\n",
-    "filename = 'data/南京化工人员.json'\n",
+    "filename = 'data/胜利采油厂人员.json'\n",
     "with open(filename, 'w') as fl:\n",
     "    json.dump(person, fl, ensure_ascii=False)\n",
     "print(len(person),'ok')"
@@ -52,16 +67,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "ce406710-6b7d-4c51-98ec-78883bd3ce5f",
    "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-21T02:05:49.362922Z",
+     "iopub.status.busy": "2025-10-21T02:05:49.362143Z",
+     "iopub.status.idle": "2025-10-21T02:05:49.376741Z",
+     "shell.execute_reply": "2025-10-21T02:05:49.375761Z",
+     "shell.execute_reply.started": "2025-10-21T02:05:49.362862Z"
+    },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ok\n"
+     ]
+    }
+   ],
    "source": [
     "import json\n",
     "\n",
-    "filename = 'data/南京化工人员.json'\n",
+    "filename = 'data/胜利采油厂人员.json'\n",
     "with open(filename,'r') as fl:\n",
     "    dict1 = json.load(fl)\n",
     "list1 = []\n",
@@ -75,7 +105,7 @@
     "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_南京化工人员.json\", \"w\",encoding = 'utf-8') as file:\n",
+    "with open(\"data/data_胜利采油厂人员.json\", \"w\",encoding = 'utf-8') as file:\n",
     "    file.write(json_data)   \n",
     "print('ok')"
    ]
diff --git a/体测单位/宁夏能化.ipynb b/体测单位/宁夏能化.ipynb
index 2351867..b7f007d 100644
--- a/体测单位/宁夏能化.ipynb
+++ b/体测单位/宁夏能化.ipynb
@@ -1,5 +1,13 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a3a2e21f-e62e-465b-818d-8acea289434f",
+   "metadata": {},
+   "source": [
+    "# 体质检测"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "04524c85-988e-4dbf-86eb-939a9db7aa28",
@@ -10,27 +18,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "bbba6efc-73cd-4db6-bae7-014724fee731",
    "metadata": {
-    "execution": {
-     "iopub.execute_input": "2025-08-14T12:48:54.906761Z",
-     "iopub.status.busy": "2025-08-14T12:48:54.906261Z",
-     "iopub.status.idle": "2025-08-14T12:48:55.181497Z",
-     "shell.execute_reply": "2025-08-14T12:48:55.180926Z",
-     "shell.execute_reply.started": "2025-08-14T12:48:54.906723Z"
-    },
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "1698 ok\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import openpyxl\n",
     "import json\n",
@@ -342,17 +335,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "75b98b19-ab32-414a-b3f2-6efd58e1f9a9",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2025-08-28T09:16:02.802494Z",
-     "iopub.status.busy": "2025-08-28T09:16:02.801898Z",
-     "iopub.status.idle": "2025-08-28T09:16:02.994884Z",
-     "shell.execute_reply": "2025-08-28T09:16:02.994340Z",
-     "shell.execute_reply.started": "2025-08-28T09:16:02.802438Z"
-    }
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import json\n",
@@ -557,26 +542,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "d31020be-c9c0-404f-8e0b-f8f507385f48",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2025-08-14T12:28:32.225197Z",
-     "iopub.status.busy": "2025-08-14T12:28:32.224475Z",
-     "iopub.status.idle": "2025-08-14T12:28:32.933373Z",
-     "shell.execute_reply": "2025-08-14T12:28:32.932821Z",
-     "shell.execute_reply.started": "2025-08-14T12:28:32.225127Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "ok\n"
-     ]
-    }
-   ],
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import json\n",
     "import openpyxl\n",
@@ -877,17 +846,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "360831b7-e204-4801-9f72-879e338ed962",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2025-08-13T11:53:04.589116Z",
-     "iopub.status.busy": "2025-08-13T11:53:04.588495Z",
-     "iopub.status.idle": "2025-08-13T11:53:04.762457Z",
-     "shell.execute_reply": "2025-08-13T11:53:04.761877Z",
-     "shell.execute_reply.started": "2025-08-13T11:53:04.589057Z"
-    }
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import json\n",
@@ -963,17 +924,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "e3117237-b921-41fe-9b65-4918c5b2a165",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2025-08-13T08:52:05.672800Z",
-     "iopub.status.busy": "2025-08-13T08:52:05.672283Z",
-     "iopub.status.idle": "2025-08-13T08:52:05.820901Z",
-     "shell.execute_reply": "2025-08-13T08:52:05.820357Z",
-     "shell.execute_reply.started": "2025-08-13T08:52:05.672751Z"
-    }
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import json\n",
@@ -1004,10 +957,260 @@
     "    "
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "fabb8138-ad15-43a0-abf5-c5ff73318333",
+   "metadata": {},
+   "source": [
+    "# 高危风险干预"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5b5fcb90-e60e-4edd-929a-702fe93bd0e7",
+   "metadata": {},
+   "source": [
+    "## 导入干预人员名单"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "396e64b8-c306-4613-9848-f0f183052b78",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-10T02:18:51.157197Z",
+     "iopub.status.busy": "2025-10-10T02:18:51.156880Z",
+     "iopub.status.idle": "2025-10-10T02:18:51.211412Z",
+     "shell.execute_reply": "2025-10-10T02:18:51.210755Z",
+     "shell.execute_reply.started": "2025-10-10T02:18:51.157161Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "210 ok\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "import csv\n",
+    "import openpyxl\n",
+    "import time\n",
+    "from datetime import date\n",
+    "\n",
+    "wb = openpyxl.load_workbook('data/宁夏能化高危风险人群最终干预人员名单.xlsx',data_only=True)\n",
+    "sheet = wb.active\n",
+    "# sheets = wb.sheetnames\n",
+    "person = {}\n",
+    "for n in range(2, sheet.max_row+1):\n",
+    "    code = int(sheet.cell(n, 2).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, 6).value\n",
+    "    \n",
+    "    \n",
+    "    dict1['age'] = int(sheet.cell(n, 5).value)\n",
+    "    person[code] = dict1\n",
+    "filename = 'data/宁夏能化干预人员.json'\n",
+    "with open(filename, 'w') as fl:\n",
+    "    json.dump(person, fl, ensure_ascii=False)\n",
+    "print(len(person),'ok')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "952544fd-0fc6-4365-a43b-a12cab537bb2",
+   "metadata": {},
+   "source": [
+    "## 获取问卷人员信息"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "f60e8194-7ef6-49d8-8538-9b79f35bb64d",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-10T02:09:50.365387Z",
+     "iopub.status.busy": "2025-10-10T02:09:50.364816Z",
+     "iopub.status.idle": "2025-10-10T02:09:50.391653Z",
+     "shell.execute_reply": "2025-10-10T02:09:50.391205Z",
+     "shell.execute_reply.started": "2025-10-10T02:09:50.365335Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "145 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_20251009.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 = int(dict2['code'])\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",
+    "    dict1[code]['unit'] = dict2['unit']\n",
+    "    dict1[code]['phone'] = phone\n",
+    "    dict1[code]['waist'] = dict2['waist']\n",
+    "    dict1[code]['hip'] = dict2['hip']\n",
+    "    dict1[code]['tcm'] = tcm\n",
+    "filename = 'data/survey_宁夏能化干预人员.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": "93a9b31e-49ea-45cd-bb0b-5c3db19bbb54",
+   "metadata": {},
+   "source": [
+    "## 导出问卷人员信息"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "f0853629-e971-492b-88c8-4e9521b4b017",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-10T02:16:14.316496Z",
+     "iopub.status.busy": "2025-10-10T02:16:14.315869Z",
+     "iopub.status.idle": "2025-10-10T02:16:14.344471Z",
+     "shell.execute_reply": "2025-10-10T02:16:14.343924Z",
+     "shell.execute_reply.started": "2025-10-10T02:16:14.316435Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import openpyxl\n",
+    "\n",
+    "\n",
+    "title = ['员工编号','姓名','性别','部门']\n",
+    "\n",
+    "filename = 'data/survey_宁夏能化干预人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "\n",
+    "filename = 'data/宁夏能化干预人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict2 = json.load(fl)\n",
+    "    \n",
+    "list1 = []\n",
+    "for k, v in dict2.items():\n",
+    "    \n",
+    "    if str(k) not in dict1.keys():\n",
+    "        list2 = []\n",
+    "        list2 = [k,v['name'],v['sex'],v['unit']]      \n",
+    "        list1.append(list2)\n",
+    "filename = 'data/宁夏能化干预人员未参加问卷人员（20251010）.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": "code",
+   "execution_count": 29,
+   "id": "22be8f39-afbb-448a-8ae6-c825c7d38757",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-10-10T02:18:10.620552Z",
+     "iopub.status.busy": "2025-10-10T02:18:10.619865Z",
+     "iopub.status.idle": "2025-10-10T02:18:10.652211Z",
+     "shell.execute_reply": "2025-10-10T02:18:10.651710Z",
+     "shell.execute_reply.started": "2025-10-10T02:18:10.620490Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import openpyxl\n",
+    "\n",
+    "\n",
+    "title = ['员工编号','姓名','性别','部门','手机号码']\n",
+    "\n",
+    "filename = 'data/survey_宁夏能化干预人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "\n",
+    "filename = 'data/宁夏能化干预人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict2 = json.load(fl)\n",
+    "    \n",
+    "list1 = []\n",
+    "for k, v in dict2.items():\n",
+    "    \n",
+    "    if str(k) in dict1.keys():\n",
+    "        list2 = []\n",
+    "        list2 = [k,v['name'],v['sex'],v['unit'],dict1[k]['phone']]      \n",
+    "        list1.append(list2)\n",
+    "filename = 'data/宁夏能化干预人员参加问卷人员（20251010）.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": "code",
    "execution_count": null,
-   "id": "6133f0d5-75aa-41c0-a624-b354d89b5ba3",
+   "id": "f32288ee-167c-4e2a-9679-5d927db34950",
    "metadata": {},
    "outputs": [],
    "source": []
diff --git a/体测单位/胜利采油厂.ipynb b/体测单位/胜利采油厂.ipynb
new file mode 100644
index 0000000..3874abd
--- /dev/null
+++ b/体测单位/胜利采油厂.ipynb
@@ -0,0 +1,1202 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "04524c85-988e-4dbf-86eb-939a9db7aa28",
+   "metadata": {},
+   "source": [
+    "## 体测人员导入"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bbba6efc-73cd-4db6-bae7-014724fee731",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import openpyxl\n",
+    "import json\n",
+    "\n",
+    "\n",
+    "wb = openpyxl.load_workbook('data/南化人员信息表.xlsx',data_only=True)\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, 4).value)\n",
+    "    person.setdefault(code, {})\n",
+    "    dict1 = {}\n",
+    "    dict1['name'] = sheet.cell(n, 3).value\n",
+    "    dict1['sex'] = sheet.cell(n, 5).value\n",
+    "    dict1['unit'] = sheet.cell(n, 2).value    \n",
+    "    dict1['birth'] = str(sheet.cell(n, 6).value).replace('/','-').split(' ')[0]\n",
+    "    dict1['phone'] = sheet.cell(n, 12).value \n",
+    "    person[code] = dict1\n",
+    "filename = 'data/南京化工人员.json'\n",
+    "with open(filename, 'w') as fl:\n",
+    "    json.dump(person, fl, ensure_ascii=False)\n",
+    "print(len(person),'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": null,
+   "id": "ce406710-6b7d-4c51-98ec-78883bd3ce5f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "\n",
+    "filename = 'data/南京化工人员.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_南京化工人员.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": null,
+   "id": "970e171e-1360-448f-a28c-520ccb8f314a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import datetime\n",
+    "import csv\n",
+    "from datetime import date\n",
+    "import my_module as My\n",
+    "\n",
+    "filename = 'data/南京化工人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl) \n",
+    "filename = 'data/marks_20250703.csv'\n",
+    "re_ta = My.get_result(filename,dict1)\n",
+    "\n",
+    "\n",
+    "filename = 'data/result_南京化工.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": "6d381859-6d21-45d2-8313-55ebbabf8bd4",
+   "metadata": {},
+   "source": [
+    "## 生成测试得分"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0905ad6a-f7e4-43ed-ae29-c4850deb946b",
+   "metadata": {},
+   "outputs": [],
+   "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_南京化工.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_南京化工.json'\n",
+    "with open(filename,'w') as fl:\n",
+    "    json.dump(dict2,fl , ensure_ascii=False) \n",
+    "print('ok!')        "
+   ]
+  },
+  {
+   "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 = ['lung','grip','flexion','jump','pushup','situp','balance','reaction','step']\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_南京化工.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "\n",
+    "filename = 'data/南京化工人员.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",
+    "    if 'bmi' in v.keys():\n",
+    "        height = v['bmi']['成绩'].split(',')[0]\n",
+    "        weight = v['bmi']['成绩'].split(',')[1]\n",
+    "        list2.append(height)\n",
+    "        list2.append(weight)\n",
+    "    else:\n",
+    "        list2.append('')\n",
+    "        list2.append('')\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",
+    "    \n",
+    "    list1.append(list2)\n",
+    "filename = 'data/南京化工测试情况明细表（截至20250630）.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": [
+    "## 统计问卷人员情况"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "def3f47a-24ef-4815-b63b-2a16b79b4c15",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import csv\n",
+    "import openpyxl\n",
+    "import time\n",
+    "from datetime import date\n",
+    "\n",
+    "\n",
+    "filename = 'data/南京化工人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "\n",
+    "phone1 =  set()\n",
+    "phone2 = set()\n",
+    "for k,v in dict1.items():\n",
+    "    phone1.add(v['phone'])\n",
+    "list1 = []\n",
+    "filename = 'data/survey_records_20250813.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",
+    "i =1\n",
+    "list2 = []\n",
+    "for item in list1:\n",
+    "    content = json.loads(item[4])\n",
+    "    code = int(content['phone'])\n",
+    "    for k, v in dict1.items():\n",
+    "        list3 = []\n",
+    "        if v['phone'] == code:            \n",
+    "            list3.append(k)\n",
+    "            list3.append(v['name'])\n",
+    "            list3.append(v['sex'])\n",
+    "            list3.append(v['unit'])\n",
+    "            list3.append(code)\n",
+    "            list2.append(list3)\n",
+    "filename = 'data/南化问卷情况表（第二批）.xlsx'\n",
+    "wb = openpyxl.Workbook()\n",
+    "sheet = wb.active\n",
+    "#sheet.append(title)\n",
+    "for row in list2:\n",
+    "    sheet.append(row)\n",
+    "    \n",
+    "wb.save(filename)  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8b7c0528-17b6-4469-b15f-3c4b794e286e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import csv\n",
+    "import openpyxl\n",
+    "import time\n",
+    "from datetime import date\n",
+    "\n",
+    "\n",
+    "\n",
+    "filename = 'data/survey_records_20250813.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",
+    "i =1\n",
+    "list2 = []\n",
+    "for item in list1:\n",
+    "    list3 = []\n",
+    "    content = json.loads(item[4])\n",
+    "    phone = int(content['phone'])\n",
+    "    name = content['name']\n",
+    "    sex = content['gender']\n",
+    "    list3.append(name)\n",
+    "    list3.append(sex)\n",
+    "    list3.append(phone)\n",
+    "    list2.append(list3)\n",
+    "filename = 'data/南化问卷情况表（第二批）.xlsx'\n",
+    "wb = openpyxl.Workbook()\n",
+    "sheet = wb.active\n",
+    "#sheet.append(title)\n",
+    "for row in list2:\n",
+    "    sheet.append(row)\n",
+    "    \n",
+    "wb.save(filename)  "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "797717d5-47b9-4d47-be6c-8d54bede67d4",
+   "metadata": {},
+   "source": [
+    "## 导入问卷信息"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9d9dd574-9fbf-4d0a-96fd-9b55d98021d2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import csv\n",
+    "import openpyxl\n",
+    "import time\n",
+    "from datetime import date\n",
+    "\n",
+    "dict1 = {}\n",
+    "\n",
+    "filename = 'data/result_南京化工.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "filename = 'data/南京化工人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict3 = json.load(fl)\n",
+    "\n",
+    "phone =  {}\n",
+    "for k,v in dict3.items():\n",
+    "    if 'phone' in v.keys():\n",
+    "        phone[v['phone']] = k\n",
+    "\n",
+    "list1 = []\n",
+    "filename = 'data/survey_records_20250812.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",
+    "\n",
+    "\n",
+    "nn = 0\n",
+    "for item in list1:\n",
+    "     if int(item[3]) in phone.keys():        \n",
+    "        tcm = []\n",
+    "        code = phone[int(item[3])]\n",
+    "        \n",
+    "        for i in range(0,60):\n",
+    "            tcm.append(0)\n",
+    "        \n",
+    "       \n",
+    "        content = json.loads(item[4])\n",
+    "        if code not in dict1.keys():\n",
+    "            dict1[code] = dict3[code]\n",
+    "            rq = date.fromisoformat(item[5].replace('/','-').split(' ')[0])\n",
+    "            dict1[code]['rq'] = str(date.fromisoformat(item[5].replace('/','-').split(' ')[0]))\n",
+    "            #dict1[code]['rq'] = item[5].replace('/','-').split(' ')[0]\n",
+    "        else:\n",
+    "            rq=date.fromisoformat('2025-07-01')\n",
+    "            dict1[code]['rq'] = '2025-07-01'\n",
+    "        for k, v in content.items():\n",
+    "           \n",
+    "            if 'tcm' in k:\n",
+    "                i = int(k[3:])\n",
+    "                tcm[i-1] = int(v)           \n",
+    "        \n",
+    "        if 'tcm' in item[4]:            \n",
+    "            dict1[code]['tcm'] = tcm\n",
+    "       \n",
+    "        birth = date.fromisoformat(dict3[code]['birth'].replace('/','-'))\n",
+    "        \n",
+    "        days =  (rq-birth).days          \n",
+    "        dict1[code]['age'] = int(days/365)\n",
+    "        dict1[code]['month'] = int(days/365*12)\n",
+    "        #print(phone[item[2]])\n",
+    "        nn+=1\n",
+    "filename = 'data/result_南京化工-2.json'\n",
+    "\n",
+    "with open(filename,'w') as fl:\n",
+    "    json.dump(dict1, fl, ensure_ascii=False)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4930b4cb-2114-4432-a8ae-e6d2cde69b5c",
+   "metadata": {},
+   "source": [
+    "## 导入问卷信息(新)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "9b801085-ca98-4958-8dcc-bcd9985fcd4b",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-09-01T07:20:37.177771Z",
+     "iopub.status.busy": "2025-09-01T07:20:37.177055Z",
+     "iopub.status.idle": "2025-09-01T07:20:37.198841Z",
+     "shell.execute_reply": "2025-09-01T07:20:37.198253Z",
+     "shell.execute_reply.started": "2025-09-01T07:20:37.177707Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "83\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "import csv\n",
+    "import openpyxl\n",
+    "import time\n",
+    "from datetime import date\n",
+    "\n",
+    "\n",
+    "filename = 'data/南京化工人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict3 = json.load(fl)\n",
+    "\n",
+    "\n",
+    "list1 = []\n",
+    "filename = 'data/survey_records_20250901.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",
+    "\n",
+    "dict1 = {}\n",
+    "nn = 0\n",
+    "for item in list1:             \n",
+    "    tcm = []    \n",
+    "    for i in range(0,60):\n",
+    "        tcm.append(0)\n",
+    "       \n",
+    "    content = json.loads(item[4])   \n",
+    "    phone = content['phone']\n",
+    "    name = content['name']\n",
+    "    for k,v in dict3.items():\n",
+    "        if name == v['name']:\n",
+    "            code = k\n",
+    "            unit = v['unit']\n",
+    "            sex = v['sex']\n",
+    "    dict1.setdefault(code,{})\n",
+    "    \n",
+    "    #rq = date.fromisoformat(item[5].replace('/','-').split(' ')[0])\n",
+    "    #dict1[phone]['rq'] = str(date.fromisoformat(item[5].replace('/','-').split(' ')[0]))\n",
+    "     \n",
+    "    for k, v in content.items():       \n",
+    "        if 'tcm' in k:\n",
+    "            i = int(k[3:])\n",
+    "            tcm[i-1] = int(v)           \n",
+    "    \n",
+    "    if 'tcm' in item[4]:            \n",
+    "        dict1[code]['tcm'] = tcm\n",
+    "   \n",
+    "    dict1[code]['name'] = content['name']\n",
+    "    dict1[code]['unit'] = unit\n",
+    "    dict1[code]['sex'] = sex\n",
+    "    dict1[code]['weight'] = content['weight']\n",
+    "    dict1[code]['tun'] = content['hip']\n",
+    "    dict1[code]['yao'] = content['waist']\n",
+    "    #print(phone[item[2]])\n",
+    "    nn+=1\n",
+    "filename = 'data/result_南京化工-2.json'\n",
+    "\n",
+    "with open(filename,'w') as fl:\n",
+    "    json.dump(dict1, fl, ensure_ascii=False)\n",
+    "print(len(dict1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "89689b86-3fae-402e-a456-a646f0c7201f",
+   "metadata": {},
+   "source": [
+    "## 导入腰臀数据"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4a0678c6-0c64-4314-bb03-24b10a3d695a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import csv\n",
+    "import openpyxl\n",
+    "import time\n",
+    "from datetime import date\n",
+    "\n",
+    "dict1 = {}\n",
+    "\n",
+    "filename = 'data/result_南京化工-1.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "wb = openpyxl.load_workbook('data/南化腰臀数据.xlsx',data_only=True)\n",
+    "sheet = wb.active\n",
+    "# sheets = wb.sheetnames\n",
+    "person = {}\n",
+    "\n",
+    "for n in range(2, sheet.max_row+1):\n",
+    "    code = str(sheet.cell(n, 1).value)\n",
+    "    if code in dict1.keys():\n",
+    "        yao = str(sheet.cell(n, 2).value)\n",
+    "        tun = str(sheet.cell(n, 3).value)\n",
+    "        dict1[code]['腰臀比'] = yao+','+tun\n",
+    "filename = 'data/result_南京化工-1.json'\n",
+    "\n",
+    "with open(filename,'w') as fl:\n",
+    "    json.dump(dict1, fl, ensure_ascii=False)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "19c6e8b6-2663-447d-884b-a22af3944c71",
+   "metadata": {},
+   "source": [
+    "## 计算中医体质并导出"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e233e6c3-9c3f-42c7-8057-012bbcfe8b26",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import openpyxl\n",
+    "import json\n",
+    "\n",
+    "questions = [\n",
+    "  [1],\n",
+    "  [-1, 2],\n",
+    "  [-1, 2],\n",
+    "  [-1, 8],\n",
+    "  [-1, 3],\n",
+    "  [1],\n",
+    "  [-1],\n",
+    "  [-1, 7],\n",
+    "  [2],\n",
+    "  [2],\n",
+    "  [2],\n",
+    "  [2, 3],\n",
+    "  [2],\n",
+    "  [2],\n",
+    "  [3],\n",
+    "  [3],\n",
+    "  [3],\n",
+    "  [3],\n",
+    "  [3],\n",
+    "  [4],\n",
+    "  [4],\n",
+    "  [4],\n",
+    "  [4],\n",
+    "  [4],\n",
+    "  [4],\n",
+    "  [4],\n",
+    "  [4],\n",
+    "  [5],\n",
+    "  [5],\n",
+    "  [5],\n",
+    "  [5],\n",
+    "  [5],\n",
+    "  [5],\n",
+    "  [5],\n",
+    "  [5],\n",
+    "  [6],\n",
+    "  [6],\n",
+    "  [6],\n",
+    "  [6],\n",
+    "  [6],\n",
+    "  [6],\n",
+    "  [7],\n",
+    "  [7],\n",
+    "  [7],\n",
+    "  [7],\n",
+    "  [7],\n",
+    "  [7],\n",
+    "  [8],\n",
+    "  [8],\n",
+    "  [8],\n",
+    "  [8],\n",
+    "  [8],\n",
+    "  [8],\n",
+    "  [9],\n",
+    "  [9],\n",
+    "  [9],\n",
+    "  [9],\n",
+    "  [9],\n",
+    "  [9],\n",
+    "  [9]\n",
+    "]\n",
+    "\n",
+    "kinds = [\n",
+    "  '平和',\n",
+    "  '气虚',\n",
+    "  '阳虚',\n",
+    "  '阴虚',\n",
+    "  '痰湿',\n",
+    "  '湿热',\n",
+    "  '血瘀',\n",
+    "  '气郁',\n",
+    "  '特禀'\n",
+    "]\n",
+    "\n",
+    "def tcm_calc(arr):\n",
+    "  qa = [8, 8, 7, 8, 8, 6, 7, 7, 7]\n",
+    "  # 成绩数组\n",
+    "  s = [0] * 9\n",
+    "  # 遍历五进制\n",
+    "  for i in range(len(questions)):\n",
+    "    m = arr[i] - 1\n",
+    "    for v in questions[i]:\n",
+    "      if v < 0:\n",
+    "        s[-v - 1] += 4 - m\n",
+    "      else:\n",
+    "        s[v - 1] += m\n",
+    "  return [int((v / qa[i]) * 25) for i, v in enumerate(s)]\n",
+    "\n",
+    "def tcm_kind(score):\n",
+    "  kind = 0\n",
+    "  near = False\n",
+    "  max_kind = 0\n",
+    "  max_score = 0\n",
+    "  for i in range(1, 9):\n",
+    "    if score[i] > max_score:\n",
+    "      max_kind = i\n",
+    "      max_score = score[i]\n",
+    "  if score[0] >= 60 and max_score < 40:\n",
+    "    if max_score >= 30:\n",
+    "      near = True\n",
+    "      kind = max_kind\n",
+    "  else:\n",
+    "    kind = max_kind\n",
+    "  return {\n",
+    "    \"kind\": kind,\n",
+    "    \"near\": near\n",
+    "  }\n",
+    "\n",
+    "\n",
+    "filename = 'data/result_南京化工-2.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl) \n",
+    "i = 1\n",
+    "list2 = []\n",
+    "for k, v in dict1.items():\n",
+    "    if 'tcm' in v.keys():\n",
+    "        list1 = []\n",
+    "        tcm =v['tcm']\n",
+    "        for item in tcm:\n",
+    "            list1.append(item)\n",
+    "        score = tcm_calc(list1)\n",
+    "\n",
+    "        result = tcm_kind(score)\n",
+    "        kind = result['kind']\n",
+    "        near = result['near']\n",
+    "        #print(i,k,kinds[kind], near, score)\n",
+    "        #i+=1\n",
+    "        list3 = []\n",
+    "        list3.append(k)\n",
+    "        list3.append(v['name'])\n",
+    "        list3.append(v['sex'])\n",
+    "        list3.append(v['weight'])\n",
+    "        list3.append(v['yao'])\n",
+    "        list3.append(v['tun'])\n",
+    "        list3.append(kinds[kind])\n",
+    "        list3.append(near)\n",
+    "        for item in score:\n",
+    "            list3.append(item)\n",
+    "        list2.append(list3)\n",
+    "\n",
+    "filename = 'data/南化第二次问卷明细表（截至20250831）.xlsx'\n",
+    "wb = openpyxl.Workbook()\n",
+    "sheet = wb.active\n",
+    "\n",
+    "for row in list2:\n",
+    "    sheet.append(row)\n",
+    "    \n",
+    "wb.save(filename)\n",
+    "print('ok')       "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "caf77c95-3090-4fa1-bcec-c9e8a38d4ca9",
+   "metadata": {},
+   "source": [
+    "## 体检报告汇总"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b815a478-d178-4b87-9080-a779d397d945",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "import json\n",
+    "import shutil\n",
+    "\n",
+    "\n",
+    "target_directory = Path('./file/南化体重')\n",
+    "new_path = './file/南化体重/new'\n",
+    "filename = 'data/南京化工人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "# 遍历目标目录及其子目录获取所有文件\n",
+    "\n",
+    "for fl in target_directory.rglob('*.pdf'):\n",
+    "    if fl.is_file():\n",
+    "        fl_name = fl.stem\n",
+    "        name = fl_name[12:]        \n",
+    "        for k, v in dict1.items():            \n",
+    "            if name == v['name']:\n",
+    "                n_name = Path(new_path,str(k)+'-'+name+'.pdf')\n",
+    "                shutil.copyfile(fl,n_name)\n",
+    "                print(n_name)\n",
+    "                \n",
+    "                "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4f192b79-5dc7-4517-b7f3-409e30d60dad",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "import json\n",
+    "import shutil\n",
+    "import pymupdf4llm\n",
+    "#md_text = pymupdf4llm.to_markdown(\"data/1782596-唐荣.pdf\")\n",
+    "llama_reader = pymupdf4llm.LlamaMarkdownReader()\n",
+    "#llama_docs = llama_reader.load_data(\"data/1782596-唐荣.pdf\")\n",
+    "\n",
+    "\n",
+    "target_directory = Path('./file/北海体检报告')\n",
+    "new_path = './file/北海体检报告/md'\n",
+    "\n",
+    "\n",
+    "for fl in target_directory.rglob('*.pdf'):\n",
+    "    if fl.is_file():\n",
+    "        fl_name = fl.stem\n",
+    "        llama_lists = pymupdf4llm.to_markdown(fl,page_chunks=True)\n",
+    "        list1 = []\n",
+    "        for item in llama_lists:\n",
+    "            list1.append(item['text'])\n",
+    "        llama_docs = '\\n'.join(list1)\n",
+    "        Path(new_path,fl_name+'.md').write_bytes(llama_docs.encode())\n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e5863760-0d11-45b0-acb3-1a38c78d4fc7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "import json\n",
+    "import shutil\n",
+    "import pymupdf4llm\n",
+    "#md_text = pymupdf4llm.to_markdown(\"data/1782596-唐荣.pdf\")\n",
+    "llama_reader = pymupdf4llm.LlamaMarkdownReader()\n",
+    "llama_docs = llama_reader.load_data(\"data/1782596-唐荣.pdf\",page_chunks=True)\n",
+    "print(llama_docs)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8d5f4103-0d1e-4711-b324-ece360f8dcd3",
+   "metadata": {},
+   "source": [
+    "## 生成报告"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "23ffd115-72a3-4f90-9e64-ffa6420df8a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "import json\n",
+    "import openpyxl\n",
+    "\n",
+    "\n",
+    "headers = {\n",
+    "    \"Content-Type\": \"application/json; charset=UTF-8\"\n",
+    "    }\n",
+    "filename = 'data/result_南京化工-2.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "list1 = []\n",
+    "file_path ='./南京化工第二批问卷/'\n",
+    "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
+    "i=0\n",
+    "list2 = []\n",
+    "for  k, v in dict1.items():\n",
+    "    list1 = []\n",
+    "    mydata = {}\n",
+    "    \n",
+    "    id = str(k).rjust(4,\"0\")\n",
+    "    mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
+    "    mydata['title'] = '南化公司'\n",
+    "    mydata['subtitle'] = ''#v['unit']\n",
+    "    mydata['id'] = id\n",
+    "    mydata['name'] = v['name']\n",
+    "    if v['sex'] == '男':\n",
+    "        mydata['gender'] = 'male'\n",
+    "    else:\n",
+    "        mydata['gender'] = 'female'\n",
+    "    \n",
+    "    mydata['month'] = v['month']\n",
+    "    mydata['fits'] = {}\n",
+    "    survey_list = ['tcm','psy57','spine']\n",
+    "    for item in survey_list:\n",
+    "        if item in  v.keys():\n",
+    "            mydata.setdefault('surveys',{})\n",
+    "            mydata['surveys'][item] = v[item]\n",
+    "            \n",
+    "    \n",
+    "    #mydata['fits'] = {}\n",
+    "    for item in list_item:\n",
+    "        if item in v.keys():\n",
+    "            mydata.setdefault('fits',{})\n",
+    "            if item in ['lung','pushup','step','situp']:\n",
+    "                mark = v[item]['成绩'].split()[0].split('.')[0]\n",
+    "            else:\n",
+    "                mark = v[item]['成绩'].split()[0]\n",
+    "            mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n",
+    "    if len(mydata['fits']) >2 or len(mydata['surveys']) >0:\n",
+    "    #if len(mydata['fits']) >2 :    \n",
+    "        list1.append(mydata)\n",
+    "        list2.append([k,v['name']])\n",
+    "        i+=1\n",
+    "        x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n",
+    "        #print(id,v['name'],x.text)\n",
+    "        #print(mydata)\n",
+    "        #x.close()\n",
+    "print(i)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "007a67c3-3590-47d9-a6d3-9080574a7940",
+   "metadata": {},
+   "source": [
+    "### 生成报告(单问卷)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "fc2bfab2-7f56-4abf-b2c4-0fb49a0da563",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-09-01T07:20:49.606201Z",
+     "iopub.status.busy": "2025-09-01T07:20:49.605939Z",
+     "iopub.status.idle": "2025-09-01T07:21:08.746449Z",
+     "shell.execute_reply": "2025-09-01T07:21:08.745281Z",
+     "shell.execute_reply.started": "2025-09-01T07:20:49.606179Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "83\n"
+     ]
+    }
+   ],
+   "source": [
+    "import requests\n",
+    "import json\n",
+    "import openpyxl\n",
+    "\n",
+    "\n",
+    "headers = {\n",
+    "    \"Content-Type\": \"application/json; charset=UTF-8\"\n",
+    "    }\n",
+    "filename = 'data/result_南京化工-2.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "list1 = []\n",
+    "file_path ='./南京化工第二批问卷/'\n",
+    "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
+    "i=0\n",
+    "list2 = []\n",
+    "for  k, v in dict1.items():\n",
+    "    list1 = []\n",
+    "    mydata = {}\n",
+    "    \n",
+    "    id = str(k)\n",
+    "    mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
+    "    mydata['title'] = '南化公司'\n",
+    "    mydata['subtitle'] = v['unit']\n",
+    "    mydata['id'] = id\n",
+    "    mydata['name'] = v['name']\n",
+    "    if v['sex'] == 'm':\n",
+    "        mydata['gender'] = 'male'\n",
+    "    else:\n",
+    "        mydata['gender'] = 'female'\n",
+    "    \n",
+    "    #mydata['month'] = v['month']\n",
+    "    #mydata['fits'] = {}\n",
+    "    survey_list = ['tcm','psy57','spine']\n",
+    "    for item in survey_list:\n",
+    "        if item in  v.keys():\n",
+    "            mydata.setdefault('surveys',{})\n",
+    "            mydata['surveys'][item] = v[item]\n",
+    "            \n",
+    "    \n",
+    "    #mydata['fits'] = {}\n",
+    "    \n",
+    "    if len(mydata['surveys']) >0:\n",
+    "    #if len(mydata['fits']) >2 :    \n",
+    "        list1.append(mydata)\n",
+    "        list2.append([k,v['name']])\n",
+    "        i+=1\n",
+    "        x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n",
+    "        #print(id,v['name'],x.text)\n",
+    "        #print(mydata)\n",
+    "        #x.close()\n",
+    "print(i)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "42f1a67c-756a-4cf0-bd53-d71fb9c95aa6",
+   "metadata": {},
+   "source": [
+    "## 导入体检报告数据"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c2fb2c7c-6541-4c41-ba38-0e1fee29aa97",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "import json\n",
+    "import shutil\n",
+    "\n",
+    "\n",
+    "target_directory = Path('./data/json')\n",
+    "filename = 'data/南京化工人员.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "# 遍历目标目录及其子目录获取所有文件\n",
+    "dict2 = {}\n",
+    "list2 =  ['总胆固醇','甘油三酯','尿微量白蛋白']\n",
+    "for fl in target_directory.glob('*.json'):\n",
+    "    if fl.is_file():\n",
+    "        code = fl.stem\n",
+    "        dict2.setdefault(code,{})\n",
+    "        dict2[code] = dict1[code]\n",
+    "        with open(fl,'r') as fl1:\n",
+    "            dict3 = json.load(fl1)\n",
+    "        for k, v in dict3.items():\n",
+    "            if k =='血压情况' and len(v)>0:\n",
+    "                dict2[code].setdefault('血压',{})\n",
+    "                list1 = [] \n",
+    "                for item in v:\n",
+    "                    \n",
+    "                    dict2[code]['血压'][item['项目']] = item['结果']\n",
+    "                    if '状态' in item.keys():\n",
+    "                        list1.append(item['项目']+item['状态'])\n",
+    "                if len(list1)>0:\n",
+    "                    dict2[code]['血压']['状态'] = ','.join(list1)\n",
+    "                \n",
+    "            if k in list2:\n",
+    "                dict2[code].setdefault(k,{})\n",
+    "                dict2[code][k]['结果'] = v['结果']\n",
+    "                dict2[code][k]['参考值'] = v['参考值']\n",
+    "                if '状态' in v.keys():\n",
+    "                    dict2[code][k]['状态'] = v['状态']\n",
+    "            if k in ['空腹血糖','糖化血红蛋白']:\n",
+    "                dict2[code].setdefault(k,{})\n",
+    "                if '结果' in v.keys():\n",
+    "                    dict2[code][k]['结果'] = v['结果']\n",
+    "                    dict2[code][k]['参考值'] = v['参考值']\n",
+    "                if '状态' in v.keys():\n",
+    "                    dict2[code][k]['状态'] = v['状态']\n",
+    "            if k in ['ALT、AST、GGT','TSH、FT3、FT4']:\n",
+    "                for item in v:\n",
+    "                    xm = item['项目']\n",
+    "                    dict2[code].setdefault(xm,{})\n",
+    "                    if '结果' in item.keys():\n",
+    "                        dict2[code][xm]['结果'] = item['结果']\n",
+    "                    if '参考值' in item.keys():\n",
+    "                        dict2[code][xm]['参考值'] = item['参考值']\n",
+    "                    if '状态' in item.keys():\n",
+    "                        dict2[code][xm]['状态'] = item['状态']\n",
+    "            if k =='肾功能与尿微量白蛋白':\n",
+    "                for item in v['肾功能']:\n",
+    "                    xm = item['项目']\n",
+    "                    dict2[code].setdefault(xm,{})\n",
+    "                    if '结果' in item.keys():\n",
+    "                        dict2[code][xm]['结果'] = item['结果']\n",
+    "                    if '参考值' in item.keys():\n",
+    "                        dict2[code][xm]['参考值'] = item['参考值']\n",
+    "                    if '状态' in item.keys():\n",
+    "                        dict2[code][xm]['状态'] = item['状态']                \n",
+    "                dict2[code].setdefault('尿微量白蛋白',{})\n",
+    "                xm = v['尿微量白蛋白']\n",
+    "                if '结果' in xm.keys() and len(xm['结果'])>0:\n",
+    "                    dict2[code]['尿微量白蛋白']['结果'] = xm['结果']\n",
+    "                if '参考值' in xm.keys() and len(xm['参考值'])>0:\n",
+    "                    dict2[code]['尿微量白蛋白']['参考值'] = xm['参考值']\n",
+    "                if '状态' in xm.keys():\n",
+    "                    dict2[code]['尿微量白蛋白']['状态'] = xm['状态']    \n",
+    "                \n",
+    "            \n",
+    "\n",
+    "filename = 'data/南京化工体检情况.json'\n",
+    "\n",
+    "with open(filename,'w') as fl:\n",
+    "    json.dump(dict2, fl, ensure_ascii=False)                "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da43ceef-4215-4187-a76d-4e1434e50043",
+   "metadata": {},
+   "source": [
+    "## 导出体检报告数据"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "daa1b36e-1b62-49ee-9539-84c2d286fefe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import csv\n",
+    "import openpyxl\n",
+    "\n",
+    "filename = 'data/南京化工体检情况.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "\n",
+    "list1 = [\"总胆固醇\",\"甘油三酯\",\"空腹血糖\",\"糖化血红蛋白\",\"谷丙转氨酶 (ALT)\",\"谷草转氨酶 (AST)\",\"γ- 谷氨酰转肽酶 (GGT)\",\"促甲状腺激素 (TSH)\",\"游离三碘甲状腺原氨酸 (FT3)\",\"游离甲状腺素 (FT4)\",\"肌酐\",\"尿素氮\",\"尿酸\",\"尿微量白蛋白\"]\n",
+    "title = ['编号','姓名','性别','血压','状态']\n",
+    "for item in list1:\n",
+    "    title.append(item)\n",
+    "    title.append('状态')\n",
+    "list3 = []\n",
+    "for k, v in dict1.items():\n",
+    "    list2 = []\n",
+    "    list2.append(k)\n",
+    "    list2.append(v['name'])\n",
+    "    list2.append(v['sex'])\n",
+    "    if '血压' in v.keys():\n",
+    "        xueya = v['血压']['舒张压']+'/'+v['血压']['收缩压']\n",
+    "        if '状态' in v['血压'].keys():\n",
+    "            zt = v['血压']['状态']\n",
+    "        else:\n",
+    "            zt = ''\n",
+    "    else:\n",
+    "        xueya = ''\n",
+    "        zt = ''\n",
+    "    \n",
+    "    list2.append(xueya)\n",
+    "    list2.append(zt)\n",
+    "    for item in list1:\n",
+    "        if item in v.keys() and '结果' in v[item]:\n",
+    "            list2.append(v[item]['结果'])\n",
+    "            if '状态' in v[item]:\n",
+    "                list2.append(v[item]['状态'])\n",
+    "            else:\n",
+    "                list2.append('')\n",
+    "        else:\n",
+    "            list2.append('')\n",
+    "            list2.append('')  \n",
+    "    list3.append(list2)\n",
+    "\n",
+    "filename = 'data/南京化工体检相关数据明细.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)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "221b35dc-3a17-4950-993c-b634ee9a53cf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from spire.pdf.common import *\n",
+    "from spire.pdf import *\n",
+    "\n",
+    "# 创建PdfDocument类的实例\n",
+    "pdf = PdfDocument()\n",
+    "\n",
+    "# 加载PDF文档\n",
+    "pdf.LoadFromFile(\"file/北海体检报告/2405280074.pdf\")\n",
+    "\n",
+    "# 将PDF转换为Markdown文件\n",
+    "pdf.SaveToFile(\"PDF转Markdown.md\", FileFormat.Markdown)\n",
+    "pdf.Close()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1b9d4042-5e73-44e3-8079-eee2c5be1858",
+   "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": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/体测单位/通用技术中国医药.ipynb b/体测单位/通用技术中国医药.ipynb
index 869fadb..5c5702b 100644
--- a/体测单位/通用技术中国医药.ipynb
+++ b/体测单位/通用技术中国医药.ipynb
@@ -10,15 +10,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 8,
    "id": "d6449ec6-54af-4f68-8c32-69372e390acf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-09-22T03:30:37.564857Z",
-     "iopub.status.busy": "2025-09-22T03:30:37.564250Z",
-     "iopub.status.idle": "2025-09-22T03:30:37.781384Z",
-     "shell.execute_reply": "2025-09-22T03:30:37.780531Z",
-     "shell.execute_reply.started": "2025-09-22T03:30:37.564798Z"
+     "iopub.execute_input": "2025-09-22T12:07:43.029162Z",
+     "iopub.status.busy": "2025-09-22T12:07:43.028847Z",
+     "iopub.status.idle": "2025-09-22T12:07:43.046141Z",
+     "shell.execute_reply": "2025-09-22T12:07:43.045652Z",
+     "shell.execute_reply.started": "2025-09-22T12:07:43.029136Z"
     }
    },
    "outputs": [
@@ -45,7 +45,7 @@
     "    person.setdefault(code, {})\n",
     "    dict1 = {}\n",
     "    dict1['name'] = sheet.cell(n, 2).value\n",
-    "    #dict1['sex'] = sheet.cell(n, 5).value\n",
+    "    dict1['sex'] = sheet.cell(n, 6).value\n",
     "    dict1['unit'] = sheet.cell(n, 4).value    \n",
     "    dict1['birth'] = str(sheet.cell(n, 3).value).replace('/','-').split(' ')[0]\n",
     "    dict1['phone'] = sheet.cell(n, 5).value \n",
@@ -66,15 +66,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 15,
    "id": "c24c957e-6cc5-4cab-81e2-cec86a7498c7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-09-22T03:48:21.444109Z",
-     "iopub.status.busy": "2025-09-22T03:48:21.443422Z",
-     "iopub.status.idle": "2025-09-22T03:48:21.472961Z",
-     "shell.execute_reply": "2025-09-22T03:48:21.472454Z",
-     "shell.execute_reply.started": "2025-09-22T03:48:21.444045Z"
+     "iopub.execute_input": "2025-09-22T12:49:46.218013Z",
+     "iopub.status.busy": "2025-09-22T12:49:46.217356Z",
+     "iopub.status.idle": "2025-09-22T12:49:46.243578Z",
+     "shell.execute_reply": "2025-09-22T12:49:46.242996Z",
+     "shell.execute_reply.started": "2025-09-22T12:49:46.217955Z"
     }
    },
    "outputs": [
@@ -82,7 +82,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "33\n"
+      "31\n"
      ]
     }
    ],
@@ -144,11 +144,61 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "id": "a64ad6b7-b1dd-42ca-9619-3adcb8e0674e",
-   "metadata": {},
-   "outputs": [],
-   "source": []
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-09-22T12:49:52.460408Z",
+     "iopub.status.busy": "2025-09-22T12:49:52.459655Z",
+     "iopub.status.idle": "2025-09-22T12:49:52.470790Z",
+     "shell.execute_reply": "2025-09-22T12:49:52.469571Z",
+     "shell.execute_reply.started": "2025-09-22T12:49:52.460338Z"
+    }
+   },
+   "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_通用技术中国医药.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(str(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_通用技术中国医药.json'\n",
+    "with open(filename,'w') as fl:\n",
+    "    json.dump(dict2,fl , ensure_ascii=False) \n",
+    "print('ok!')        "
+   ]
   },
   {
    "cell_type": "markdown",
@@ -160,15 +210,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 17,
    "id": "020be101-938b-427e-918d-faf2e74b5b7e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-09-22T03:57:31.502714Z",
-     "iopub.status.busy": "2025-09-22T03:57:31.501987Z",
-     "iopub.status.idle": "2025-09-22T03:57:31.516781Z",
-     "shell.execute_reply": "2025-09-22T03:57:31.515780Z",
-     "shell.execute_reply.started": "2025-09-22T03:57:31.502649Z"
+     "iopub.execute_input": "2025-09-22T12:49:55.871938Z",
+     "iopub.status.busy": "2025-09-22T12:49:55.871204Z",
+     "iopub.status.idle": "2025-09-22T12:49:55.886755Z",
+     "shell.execute_reply": "2025-09-22T12:49:55.885950Z",
+     "shell.execute_reply.started": "2025-09-22T12:49:55.871866Z"
     }
    },
    "outputs": [],
@@ -244,10 +294,103 @@
     "    json.dump(dict1, fl, ensure_ascii=False)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "7ec62459-2938-4c0c-b35a-f4341630f1c6",
+   "metadata": {},
+   "source": [
+    "## 生成报告"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "17dd5667-d970-46d2-b241-27338dbba4bb",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-09-22T12:51:00.278870Z",
+     "iopub.status.busy": "2025-09-22T12:51:00.278200Z",
+     "iopub.status.idle": "2025-09-22T12:51:14.234951Z",
+     "shell.execute_reply": "2025-09-22T12:51:14.233971Z",
+     "shell.execute_reply.started": "2025-09-22T12:51:00.278810Z"
+    },
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "31\n"
+     ]
+    }
+   ],
+   "source": [
+    "import requests\n",
+    "import json\n",
+    "import openpyxl\n",
+    "\n",
+    "\n",
+    "headers = {\n",
+    "    \"Content-Type\": \"application/json; charset=UTF-8\"\n",
+    "    }\n",
+    "filename = 'data/result_通用技术中国医药-1.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dict1 = json.load(fl)\n",
+    "list1 = []\n",
+    "file_path ='./中国医药/'\n",
+    "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
+    "i=0\n",
+    "list2 = []\n",
+    "for  k, v in dict1.items():\n",
+    "    list1 = []\n",
+    "    mydata = {}\n",
+    "    \n",
+    "    id = str(k).rjust(4,\"0\")\n",
+    "    mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
+    "    mydata['title'] = '中国医药'\n",
+    "    mydata['subtitle'] = v['unit']\n",
+    "    mydata['id'] = id\n",
+    "    mydata['name'] = v['name']\n",
+    "    if v['sex'] == '男':\n",
+    "        mydata['gender'] = 'male'\n",
+    "    else:\n",
+    "        mydata['gender'] = 'female'\n",
+    "    \n",
+    "    mydata['month'] = v['month']\n",
+    "    mydata['fits'] = {}\n",
+    "    survey_list = ['tcm','psy57','spine']\n",
+    "    for item in survey_list:\n",
+    "        if item in  v.keys():\n",
+    "            mydata.setdefault('surveys',{})\n",
+    "            mydata['surveys'][item] = v[item]\n",
+    "            \n",
+    "    \n",
+    "    #mydata['fits'] = {}\n",
+    "    for item in list_item:\n",
+    "        if item in v.keys():\n",
+    "            mydata.setdefault('fits',{})\n",
+    "            if item in ['lung','pushup','step','situp']:\n",
+    "                mark = str(v[item]['成绩']).split()[0].split('.')[0]\n",
+    "            else:\n",
+    "                mark = str(v[item]['成绩']).split()[0]\n",
+    "            mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n",
+    "    if len(mydata['fits']) >2 or len(mydata['surveys']) >0:\n",
+    "    #if len(mydata['fits']) >2 :    \n",
+    "        list1.append(mydata)\n",
+    "        list2.append([k,v['name']])\n",
+    "        i+=1\n",
+    "        x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n",
+    "        #print(id,v['name'],x.text)\n",
+    "        #print(mydata)\n",
+    "        #x.close()\n",
+    "print(i)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9560d0ca-4d39-400b-b054-214e243ca4e5",
+   "id": "4297b542-206e-4f0e-9339-ba88e712443e",
    "metadata": {},
    "outputs": [],
    "source": []
diff --git a/文件管理.ipynb b/文件管理.ipynb
index 6409c47..b6cec13 100644
--- a/文件管理.ipynb
+++ b/文件管理.ipynb
@@ -114,40 +114,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "11ff2c59-5815-42c9-abaf-71c8c2a3b7da",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os,sys,shutil\n",
-    "from pathlib import Path\n",
-    "\n",
-    "fi_path = 'file/北海/未参加体测人员报告'\n",
-    "new_path = 'file/北海/new/未参加体测人员'\n",
-    "pdf_files = list(fi_path.glob('**/*.pdf'))\n",
-    "\n",
-    "for fn in fls:\n",
-    "    fi_name =Path(fn).stem.split('-')[0]\n",
-    "    code = int(fi_name)    \n",
-    "    unit_path = Path(new_path,dict1[str(code)]['unit'])\n",
-    "    unit_path.mkdir(parents = True, exist_ok = True)\n",
-    "    n_name = Path(unit_path,Path(fn).stem+'.pdf')\n",
-    "    #if not os.path.exists(n_name):\n",
-    "    shutil.copyfile(fn,n_name)\n",
-    "    print(fn)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "id": "62ff063a-5380-4e08-b115-acd967441ca4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-09-16T02:36:40.592582Z",
-     "iopub.status.busy": "2025-09-16T02:36:40.591749Z",
-     "iopub.status.idle": "2025-09-16T02:36:40.635821Z",
-     "shell.execute_reply": "2025-09-16T02:36:40.635329Z",
-     "shell.execute_reply.started": "2025-09-16T02:36:40.592518Z"
+     "iopub.execute_input": "2025-09-17T00:08:50.471131Z",
+     "iopub.status.busy": "2025-09-17T00:08:50.470548Z",
+     "iopub.status.idle": "2025-09-17T00:08:51.110490Z",
+     "shell.execute_reply": "2025-09-17T00:08:51.109925Z",
+     "shell.execute_reply.started": "2025-09-17T00:08:50.471076Z"
     }
    },
    "outputs": [],
@@ -155,8 +130,9 @@
     "import os,sys,shutil\n",
     "from pathlib import Path\n",
     "\n",
-    "fi_path =Path('file/北海/未参加体测人员报告')\n",
-    "new_path = 'file/北海/new/未参加体测人员'\n",
+    "fi_path = Path('file/北海/2022年')\n",
+    "new_path = 'file/北海/new/2022年'\n",
+    "pdf_files = list(fi_path.glob('**/*.pdf'))\n",
     "fls = list(fi_path.glob('**/*.pdf'))\n",
     "for fn in fls:\n",
     "    fi_name =Path(fn).name\n",