693 lines
21 KiB
Plaintext
693 lines
21 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",
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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 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/党建出版社2025.xlsx')\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, 1).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, 2).value\n",
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" dict1['sex'] = sheet.cell(n, 4).value\n",
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" dict1['unit'] = '党建出版社'\n",
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" dict1['birth'] = sheet.cell(n,3).value\n",
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" dict1['phone'] = sheet.cell(n,5).value\n",
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" person[code] = dict1\n",
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"filename = 'data/党建出版社2025.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('ok')"
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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": "9448933d-527c-410d-ba55-4ce1819a8c1e",
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"metadata": {},
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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/通用卡.xlsx')\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, 1).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, 2).value\n",
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" dict1['sex'] = sheet.cell(n, 4).value\n",
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" dict1['birth'] = sheet.cell(n,3).value\n",
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" person[code] = dict1\n",
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"filename = 'data/通用卡.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('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/通用卡.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':'编号卡'}\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_编号卡.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/党建出版社2025.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_20250530.csv'\n",
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"re_ta = My.get_result(filename,dict1)\n",
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"\n",
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"filename = 'data/result_党建出版社2025.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": "699c6a40-a6ae-4300-9646-708cb85aa5e8",
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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": "def3f47a-24ef-4815-b63b-2a16b79b4c15",
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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 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_党建出版社2025.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_党建出版社2025.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": "67e63f07-3f20-4e0e-9c07-7bf6024eeb4b",
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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 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','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_党建出版社2025.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/党建出版社2025.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/党建出版社测试情况表2025.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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{
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"cell_type": "markdown",
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"id": "b1c9377b-0da3-481a-9334-b85aa0487374",
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"metadata": {},
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"source": [
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"## 导入问卷信息"
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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": 21,
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"id": "e454f645-e593-4619-9fce-eabe0fa9f2a9",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-06-05T06:49:32.523392Z",
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"iopub.status.busy": "2025-06-05T06:49:32.522703Z",
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"iopub.status.idle": "2025-06-05T06:49:32.550951Z",
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"shell.execute_reply": "2025-06-05T06:49:32.550460Z",
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"shell.execute_reply.started": "2025-06-05T06:49:32.523324Z"
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}
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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 csv\n",
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"import openpyxl\n",
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"import time\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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"dict1 = {}\n",
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"filename = 'data/result_党建出版社2025.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/党建出版社2025.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict3 = json.load(fl)\n",
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"\n",
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"phone = {}\n",
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"for k,v in dict3.items():\n",
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" if 'phone' in v.keys():\n",
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" phone[str(v['phone'])] = k\n",
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"\n",
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"list1 = []\n",
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"filename = 'data/survey_records_20250605.csv'\n",
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"with open(filename,'r',newline='') as csv_file:\n",
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" fl = csv.reader(csv_file,delimiter=',')\n",
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" header = next(fl) \n",
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" for line in fl:\n",
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" list1.append(line)\n",
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"#print(list1)\n",
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"dict2 = {}\n",
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"psy =[]\n",
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"tcm = []\n",
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"spine = []\n",
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"for i in range(0,57):\n",
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" psy.append(0)\n",
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"\n",
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"for i in range(0,60):\n",
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" tcm.append(0)\n",
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"for i in range(0,26):\n",
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" spine.append(0)\n",
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"i= 1\n",
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"for item in list1:\n",
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" if item[3] in phone.keys():\n",
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" psy =[]\n",
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" tcm = []\n",
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" spine = []\n",
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" for i in range(0,57):\n",
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" psy.append(0)\n",
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" #psy[44] = []\n",
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" for i in range(0,60):\n",
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" tcm.append(0)\n",
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" for i in range(0,26):\n",
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" spine.append(0)\n",
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" \n",
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" content = json.loads(item[4])\n",
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" if phone[item[3]] not in dict1.keys():\n",
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" dict1[phone[item[3]]] = dict3[phone[item[3]]]\n",
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" rq = date.fromisoformat(item[5].replace('/','-').split(' ')[0])\n",
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" #dict1[phone[item[2]]]['rq'] = date.fromisoformat(item[6].replace('/','-').split(' ')[0])\n",
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" else:\n",
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" rq = date.fromisoformat('2025-05-30')\n",
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" for k, v in content.items():\n",
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" if 'psy' in k:\n",
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" i = int(k[3:])\n",
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" psy[i-1] = int(v)\n",
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" if 'tcm' in k:\n",
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" i = int(k[3:])\n",
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" tcm[i-1] = int(v)\n",
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" if 'spine' in k:\n",
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" i = int(k[5:])\n",
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" spine[i-1] = int(v)\n",
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" if 'psy' in item[4]:\n",
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" #for i in range(5,26):\n",
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" # new_valve = 5-psy[i]\n",
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" # psy[i] = new_valve\n",
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" \n",
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" \n",
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" dict1[phone[item[3]]]['psy57'] = psy\n",
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" if 'tcm' in item[4]:\n",
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" dict1[phone[item[3]]]['tcm'] = tcm\n",
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" if 'spine' in item[4]:\n",
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" dict1[phone[item[3]]]['spine'] = spine\n",
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" birth = date.fromisoformat(dict3[phone[item[3]]]['birth'].replace('/','-'))\n",
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" \n",
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" days = (rq-birth).days \n",
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" dict1[phone[item[3]]]['age'] = int(days/365)\n",
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" dict1[phone[item[3]]]['month'] = int(days/365*12)\n",
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" \n",
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"\n",
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"filename = 'data/result_党建出版社2025-1.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(dict1, fl, ensure_ascii=False)\n",
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"#print(data1[1])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "41a8ef94-57a1-4697-b99b-cb546adb09e5",
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"metadata": {},
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"source": [
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"## 统计参加问卷人员"
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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": 20,
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"id": "2ea13ff2-a675-41b2-b104-0f5cd1c9a0b5",
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"metadata": {
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"execution": {
|
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"iopub.execute_input": "2025-06-05T01:06:25.708014Z",
|
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"iopub.status.busy": "2025-06-05T01:06:25.707173Z",
|
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"iopub.status.idle": "2025-06-05T01:06:25.734176Z",
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"shell.execute_reply": "2025-06-05T01:06:25.733170Z",
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"shell.execute_reply.started": "2025-06-05T01:06:25.707934Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"85\n"
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]
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}
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],
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"source": [
|
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"import json\n",
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"import csv\n",
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"import openpyxl\n",
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"import time\n",
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"from datetime import date\n",
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"\n",
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"\n",
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"filename = 'data/党建出版社2025.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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"phone1 = set()\n",
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"phone2 = set()\n",
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"for k,v in dict1.items():\n",
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" phone1.add(v['phone'])\n",
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"list1 = []\n",
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"filename = 'data/survey_records_20250605.csv'\n",
|
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"with open(filename,'r',newline='') as csv_file:\n",
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" fl = csv.reader(csv_file,delimiter=',')\n",
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" header = next(fl) \n",
|
|
" for line in fl:\n",
|
|
" list1.append(line)\n",
|
|
"print(len(phone1))\n",
|
|
"i =1\n",
|
|
"list2 = []\n",
|
|
"for item in list1:\n",
|
|
" code = int(item[3])\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/党建出版社问卷情况表2025.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": "7c2ef41d-bba9-4776-9a0e-71e14cd7d3fe",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import csv\n",
|
|
"import openpyxl\n",
|
|
"import time\n",
|
|
"from datetime import date\n",
|
|
"\n",
|
|
"\n",
|
|
"filename = 'data/党建出版社2025.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_20250605.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",
|
|
"print(len(phone1))\n",
|
|
"i =1\n",
|
|
"list2 = []\n",
|
|
"for item in list1:\n",
|
|
" code = int(item[3])\n",
|
|
" if code not in phone1:\n",
|
|
" print(code)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ffb387e1-41b5-4a4d-a9ca-89e1c5650880",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 生成报告"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"id": "462bc4e8-1659-43a0-9cbf-a87a4dfc5376",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2025-06-05T06:50:13.169871Z",
|
|
"iopub.status.busy": "2025-06-05T06:50:13.168552Z",
|
|
"iopub.status.idle": "2025-06-05T06:50:51.648786Z",
|
|
"shell.execute_reply": "2025-06-05T06:50:51.647689Z",
|
|
"shell.execute_reply.started": "2025-06-05T06:50:13.169789Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"65\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_党建出版社2025-1.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"list1 = []\n",
|
|
"file_path ='./党建出版社2025/'\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'] = '党建读物出版社'\n",
|
|
" mydata['subtitle'] = ' '\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": "f28bb6dd-c8de-4761-a8a1-83b65a504a7d",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算中医体质"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 24,
|
|
"id": "0f393c7d-26b2-4bb2-8f18-702f5ee52abf",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2025-06-05T06:59:54.308502Z",
|
|
"iopub.status.busy": "2025-06-05T06:59:54.307891Z",
|
|
"iopub.status.idle": "2025-06-05T06:59:54.340029Z",
|
|
"shell.execute_reply": "2025-06-05T06:59:54.339248Z",
|
|
"shell.execute_reply.started": "2025-06-05T06:59:54.308441Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"ename": "NameError",
|
|
"evalue": "name 'tcm_calc' is not defined",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
|
"Cell \u001b[0;32mIn[24], line 15\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m item \u001b[38;5;129;01min\u001b[39;00m tcm:\n\u001b[1;32m 14\u001b[0m list1\u001b[38;5;241m.\u001b[39mappend(item)\n\u001b[0;32m---> 15\u001b[0m score \u001b[38;5;241m=\u001b[39m \u001b[43mtcm_calc\u001b[49m(list1)\n\u001b[1;32m 17\u001b[0m result \u001b[38;5;241m=\u001b[39m tcm_kind(score)\n\u001b[1;32m 18\u001b[0m kind \u001b[38;5;241m=\u001b[39m result[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mkind\u001b[39m\u001b[38;5;124m'\u001b[39m]\n",
|
|
"\u001b[0;31mNameError\u001b[0m: name 'tcm_calc' is not defined"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import openpyxl\n",
|
|
"import my_module as My\n",
|
|
"\n",
|
|
"filename = 'data/result_党建出版社2025-1.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(kinds[kind])\n",
|
|
" list3.append(near)\n",
|
|
" for item in score:\n",
|
|
" list3.append(item)\n",
|
|
" list2.append(list3)\n",
|
|
"print(list2)\n",
|
|
"filename = 'data/党建出版社中医情况明细表2025.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": "code",
|
|
"execution_count": null,
|
|
"id": "02057c2d-f2e5-4c09-8c2d-508bedb95817",
|
|
"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
|
|
}
|