1338 lines
42 KiB
Plaintext
1338 lines
42 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "04524c85-988e-4dbf-86eb-939a9db7aa28",
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"metadata": {},
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"source": [
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"## 体测人员导入"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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||
"id": "bbba6efc-73cd-4db6-bae7-014724fee731",
|
||
"metadata": {
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||
"tags": []
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},
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||
"outputs": [],
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"source": [
|
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"import openpyxl\n",
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"import json\n",
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"\n",
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"\n",
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"wb = openpyxl.load_workbook('data/南化人员信息表.xlsx',data_only=True)\n",
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"sheet = wb.active\n",
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"# sheets = wb.sheetnames\n",
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"person = {}\n",
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"\n",
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"for n in range(2, sheet.max_row+1):\n",
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" code = int(sheet.cell(n, 4).value)\n",
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" person.setdefault(code, {})\n",
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" dict1 = {}\n",
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" dict1['name'] = sheet.cell(n, 3).value\n",
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" dict1['sex'] = sheet.cell(n, 5).value\n",
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" dict1['unit'] = sheet.cell(n, 2).value \n",
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" dict1['birth'] = str(sheet.cell(n, 6).value).replace('/','-').split(' ')[0]\n",
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" dict1['phone'] = sheet.cell(n, 12).value \n",
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" person[code] = dict1\n",
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"filename = 'data/南京化工人员.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(person, fl, ensure_ascii=False)\n",
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"print(len(person),'ok')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "048a95aa-1691-45f6-b933-6eaf95ae1d30",
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"metadata": {},
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"source": [
|
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"## 生成读卡系统文件"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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||
"id": "ce406710-6b7d-4c51-98ec-78883bd3ce5f",
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||
"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import json\n",
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"\n",
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"filename = 'data/南京化工人员.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl)\n",
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"list1 = []\n",
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"for k, v in dict1.items():\n",
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" dict2 = {}\n",
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" #if dict1['sex'] =='男':\n",
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" # sex = 1\n",
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" \n",
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" dict2 = {'id':k,'name':v['name'],'gender':v['sex'],'birth':v['birth'],'unit':v['unit']}\n",
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" list1.append(dict2)\n",
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"json_data = json.dumps(list1,ensure_ascii=False, indent=4) \n",
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"\n",
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"# 将 json 数据写入文件\n",
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"with open(\"data/data_南京化工人员.json\", \"w\",encoding = 'utf-8') as file:\n",
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" file.write(json_data) \n",
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"print('ok')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6bcd45c2-10af-4d5f-9e0b-5cd1df4f7a7f",
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"metadata": {},
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"source": [
|
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"## 获取人员测试成绩"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "970e171e-1360-448f-a28c-520ccb8f314a",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import datetime\n",
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"import csv\n",
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"from datetime import date\n",
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"import my_module as My\n",
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"\n",
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"filename = 'data/南京化工人员.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl) \n",
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"filename = 'data/marks_20250703.csv'\n",
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"re_ta = My.get_result(filename,dict1)\n",
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"\n",
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"\n",
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"filename = 'data/result_南京化工.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(re_ta, fl, ensure_ascii=False) \n",
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"print(len(re_ta))"
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]
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},
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{
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||
"cell_type": "markdown",
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||
"id": "6d381859-6d21-45d2-8313-55ebbabf8bd4",
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||
"metadata": {},
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"source": [
|
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"## 生成测试得分"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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||
"id": "0905ad6a-f7e4-43ed-ae29-c4850deb946b",
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||
"metadata": {},
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||
"outputs": [],
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||
"source": [
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"import json\n",
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"import time\n",
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"import my_module as My\n",
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"\n",
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"#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n",
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"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n",
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"filename = 'data/result_南京化工.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl) \n",
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"for k, v in dict2.items():\n",
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" #print(k)\n",
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" if v['sex'] == '男':\n",
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" sex = 'M'\n",
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" else:\n",
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" sex = 'F' \n",
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" if 'bmi' in v.keys():\n",
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" #bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n",
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" bmi_data = v['bmi']['成绩']\n",
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" data1 = {'code':k,'sex':sex,'age':v['age'],'item':'HeightWeight','result':bmi_data}\n",
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" dict2[k]['bmi'] = {}\n",
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" dict2[k]['bmi']['成绩'] = bmi_data\n",
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" dict2[k]['bmi']['score'] = My.cal_bmi(data1)\n",
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" for item_en in list_item:\n",
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" if item_en in v.keys(): \n",
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" data1 = {'code':k,'sex':sex,'age':v['age'],'item':item_en,'result':float(v[item_en]['成绩'].split()[0])}\n",
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" #print(k,v['name'])\n",
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" dict2[k][item_en]['score'] = My.cal_score(data1)\n",
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" #print(k,v[item_en]['成绩'],cal_score(data1))\n",
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"\n",
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"filename = f'data/result_南京化工.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(dict2,fl , ensure_ascii=False) \n",
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"print('ok!') "
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]
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},
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||
{
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||
"cell_type": "markdown",
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||
"id": "d034a61d-1fbd-417b-99bd-277e43ebb678",
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||
"metadata": {},
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||
"source": [
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||
"## 导出测试人员信息"
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]
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},
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||
{
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||
"cell_type": "code",
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||
"execution_count": null,
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||
"id": "867ad6b0-9e9d-48bc-a10a-3b9cb6125890",
|
||
"metadata": {
|
||
"tags": []
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||
},
|
||
"outputs": [],
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||
"source": [
|
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"import json\n",
|
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"import openpyxl\n",
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"\n",
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"items = ['lung','grip','flexion','jump','pushup','situp','balance','reaction','step']\n",
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"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",
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"\n",
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"filename = 'data/result_南京化工.json'\n",
|
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl)\n",
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"\n",
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"filename = 'data/南京化工人员.json'\n",
|
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl)\n",
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" \n",
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"list1 = []\n",
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"for k, v in dict1.items():\n",
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" list2 = []\n",
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" list2.append(str(k).rjust(5,'0'))\n",
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" list2.append(v['name']) \n",
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" list2.append(dict2[k]['sex'])\n",
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" list2.append(dict2[k]['unit'])\n",
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" if 'bmi' in v.keys():\n",
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" height = v['bmi']['成绩'].split(',')[0]\n",
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" weight = v['bmi']['成绩'].split(',')[1]\n",
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" list2.append(height)\n",
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" list2.append(weight)\n",
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" else:\n",
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" list2.append('')\n",
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" list2.append('')\n",
|
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" for item in items:\n",
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" if item in v.keys():\n",
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" list2.append(v[item]['成绩']) \n",
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" elif item =='name':\n",
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" list2.append(v[item])\n",
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" else:\n",
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" list2.append('')\n",
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" \n",
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" list1.append(list2)\n",
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"filename = 'data/南京化工测试情况明细表（截至20250630）.xlsx'\n",
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"wb = openpyxl.Workbook()\n",
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"sheet = wb.active\n",
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"sheet.append(title)\n",
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"for row in list1:\n",
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" sheet.append(row)\n",
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" \n",
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"wb.save(filename)"
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]
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},
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||
{
|
||
"cell_type": "markdown",
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||
"id": "699c6a40-a6ae-4300-9646-708cb85aa5e8",
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||
"metadata": {},
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||
"source": [
|
||
"## 统计问卷人员情况"
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]
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||
},
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||
{
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||
"cell_type": "code",
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||
"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",
|
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"\n",
|
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"i =1\n",
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"list2 = []\n",
|
||
"for item in list1:\n",
|
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" content = json.loads(item[4])\n",
|
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" code = int(content['phone'])\n",
|
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" for k, v in dict1.items():\n",
|
||
" list3 = []\n",
|
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" if v['phone'] == code: \n",
|
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" list3.append(k)\n",
|
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" list3.append(v['name'])\n",
|
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" list3.append(v['sex'])\n",
|
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" list3.append(v['unit'])\n",
|
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" list3.append(code)\n",
|
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" list2.append(list3)\n",
|
||
"filename = 'data/南化问卷情况表（第二批）.xlsx'\n",
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"wb = openpyxl.Workbook()\n",
|
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"sheet = wb.active\n",
|
||
"#sheet.append(title)\n",
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"for row in list2:\n",
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" sheet.append(row)\n",
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" \n",
|
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"wb.save(filename) "
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]
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},
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||
{
|
||
"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",
|
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"\n",
|
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"\n",
|
||
"filename = 'data/survey_records_20250813.csv'\n",
|
||
"with open(filename,'r',newline='') as csv_file:\n",
|
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" fl = csv.reader(csv_file,delimiter=',')\n",
|
||
" header = next(fl) \n",
|
||
" for line in fl:\n",
|
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" list1.append(line)\n",
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"\n",
|
||
"i =1\n",
|
||
"list2 = []\n",
|
||
"for item in list1:\n",
|
||
" list3 = []\n",
|
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" content = json.loads(item[4])\n",
|
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" phone = int(content['phone'])\n",
|
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" name = content['name']\n",
|
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" sex = content['gender']\n",
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" list3.append(name)\n",
|
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" list3.append(sex)\n",
|
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" list3.append(phone)\n",
|
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" list2.append(list3)\n",
|
||
"filename = 'data/南化问卷情况表（第二批）.xlsx'\n",
|
||
"wb = openpyxl.Workbook()\n",
|
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"sheet = wb.active\n",
|
||
"#sheet.append(title)\n",
|
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"for row in list2:\n",
|
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" sheet.append(row)\n",
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" \n",
|
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"wb.save(filename) "
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]
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||
},
|
||
{
|
||
"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": null,
|
||
"id": "9b801085-ca98-4958-8dcc-bcd9985fcd4b",
|
||
"metadata": {},
|
||
"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",
|
||
" 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": "acfc1736-9185-4217-bd05-a83b7e292725",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 导入问卷信息(20251027)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"id": "4b6cf9bc-fe84-4cf6-b762-8c30f8dd7953",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2025-10-28T02:58:31.746734Z",
|
||
"iopub.status.busy": "2025-10-28T02:58:31.746060Z",
|
||
"iopub.status.idle": "2025-10-28T02:58:31.786856Z",
|
||
"shell.execute_reply": "2025-10-28T02:58:31.786112Z",
|
||
"shell.execute_reply.started": "2025-10-28T02:58:31.746685Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"81\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_20251028.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",
|
||
"nn = 0\n",
|
||
"for item in list1:\n",
|
||
" dict2 = {}\n",
|
||
" \n",
|
||
" phone = str(item[0])[2:]\n",
|
||
" content = json.loads(json.loads(item[1]))\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 = dict2['code']\n",
|
||
" dict1.setdefault(code,{})\n",
|
||
" dict1[code]['name'] = dict2['name']\n",
|
||
" if dict2['gender'] == 'male':\n",
|
||
" dict1[code]['sex'] = '男'\n",
|
||
" else:\n",
|
||
" dict1[code]['sex'] = '女'\n",
|
||
" dict1[code]['birth'] = str(dict2['birth'])+'-01'\n",
|
||
" dict1[code]['unit'] = '南京化工'\n",
|
||
" dict1[code]['phone'] = phone\n",
|
||
" dict1[code]['weight'] = dict2['weight']\n",
|
||
" dict1[code]['waist'] = dict2['waist']\n",
|
||
" dict1[code]['hip'] = dict2['hip']\n",
|
||
" dict1[code]['tcm'] = tcm\n",
|
||
"filename = 'data/result_南京化工-3.json'\n",
|
||
"\n",
|
||
"with open(filename,'w') as fl:\n",
|
||
" json.dump(dict1, fl, ensure_ascii=False)\n",
|
||
"print(len(dict1))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "7392d5bf-c6a8-4cdf-8653-0fb4961f1405",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"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_20251027.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",
|
||
"nn = 0\n",
|
||
"for item in list1:\n",
|
||
" dict2 = {}\n",
|
||
" \n",
|
||
" phone = str(item[0])[2:]\n",
|
||
" content = json.loads(item[1])\n",
|
||
" print(type(json.loads(content)))"
|
||
]
|
||
},
|
||
{
|
||
"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": 24,
|
||
"id": "e233e6c3-9c3f-42c7-8057-012bbcfe8b26",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2025-10-28T02:58:52.451889Z",
|
||
"iopub.status.busy": "2025-10-28T02:58:52.451452Z",
|
||
"iopub.status.idle": "2025-10-28T02:58:52.546239Z",
|
||
"shell.execute_reply": "2025-10-28T02:58:52.545487Z",
|
||
"shell.execute_reply.started": "2025-10-28T02:58:52.451850Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ok\n"
|
||
]
|
||
}
|
||
],
|
||
"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-3.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['phone'])\n",
|
||
" list3.append(v['weight'])\n",
|
||
" list3.append(v['waist'])\n",
|
||
" list3.append(v['hip'])\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/南化第三次问卷明细表（截至20251028）.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": 18,
|
||
"id": "23ffd115-72a3-4f90-9e64-ffa6420df8a4",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2025-10-27T06:11:24.661422Z",
|
||
"iopub.status.busy": "2025-10-27T06:11:24.660908Z",
|
||
"iopub.status.idle": "2025-10-27T06:11:24.977141Z",
|
||
"shell.execute_reply": "2025-10-27T06:11:24.975637Z",
|
||
"shell.execute_reply.started": "2025-10-27T06:11:24.661386Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"ename": "KeyError",
|
||
"evalue": "'month'",
|
||
"output_type": "error",
|
||
"traceback": [
|
||
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
||
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
|
||
"Cell \u001b[0;32mIn[18], line 32\u001b[0m\n\u001b[1;32m 29\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 30\u001b[0m mydata[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgender\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfemale\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m---> 32\u001b[0m mydata[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmonth\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[43mv\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mmonth\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 33\u001b[0m mydata[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfits\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m {}\n\u001b[1;32m 34\u001b[0m survey_list \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtcm\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpsy57\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mspine\u001b[39m\u001b[38;5;124m'\u001b[39m]\n",
|
||
"\u001b[0;31mKeyError\u001b[0m: 'month'"
|
||
]
|
||
}
|
||
],
|
||
"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-3.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"list1 = []\n",
|
||
"file_path ='./南京化工第三批问卷（251021）/'\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": 19,
|
||
"id": "fc2bfab2-7f56-4abf-b2c4-0fb49a0da563",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2025-10-27T06:12:04.742517Z",
|
||
"iopub.status.busy": "2025-10-27T06:12:04.738837Z",
|
||
"iopub.status.idle": "2025-10-27T06:12:30.134155Z",
|
||
"shell.execute_reply": "2025-10-27T06:12:30.133408Z",
|
||
"shell.execute_reply.started": "2025-10-27T06:12:04.742463Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"72\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-3.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"list1 = []\n",
|
||
"file_path ='./南京化工第三批问卷/'\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
|
||
}
|