1986 lines
59 KiB
Plaintext
1986 lines
59 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "4626da6c-d228-4270-8d8d-c98784a106ad",
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"metadata": {
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"jp-MarkdownHeadingCollapsed": true,
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"tags": [],
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"toc-hr-collapsed": true
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},
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"source": [
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"# 第一次体测"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ba2deee7-9c63-4115-bcee-ad341175fc02",
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"metadata": {},
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"source": [
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"## 人员信息导入"
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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": "dea5e486-6927-469f-aa57-e5efac4670be",
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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/农业银行测试名单.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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" if sheet.cell(n,1).value is not None:\n",
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" code = int(sheet.cell(n, 2).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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" if sheet.cell(n, 4).value ==1:\n",
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" sex = '男'\n",
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" else:\n",
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" sex = '女'\n",
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" dict1['sex'] = sex\n",
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" birth = str(sheet.cell(n, 5).value).split()[0]\n",
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" dict1['birth'] = birth\n",
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" dict1['unit'] = sheet.cell(n, 1).value\n",
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" if sheet.cell(n,10).value is not None:\n",
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" dict1['phone'] = sheet.cell(n, 10).value \n",
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" person[code] = dict1\n",
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"\n",
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"filename = 'data/北京农行人员名单.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": "1c00e1e4-101a-4e9f-a7ed-9c65200d19df",
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"metadata": {},
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"source": [
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"## 成绩导入"
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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": "fd73b8be-d3fe-49aa-99d2-3cc6df4a3eb0",
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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 csv\n",
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"\n",
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"filename = '../item.json'\n",
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"item = {}\n",
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"unit = {}\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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"for k,v in dict1.items():\n",
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" item[k] = v\n",
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"re_ta = {}\n",
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"dict1 = {}\n",
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"list1 = []\n",
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"filename = 'data/北京农行人员名单all.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/places_result_20230918.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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" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
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" list1.append(line)\n",
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"#print(list1)\n",
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"for result in list1:\n",
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" user = str(result[2])\n",
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" if user in dict1.keys(): \n",
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" m_item = str(result[3]) \n",
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" re_ta.setdefault(user,{}) \n",
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" re_ta[user]['name'] = dict1[user]['name']\n",
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" re_ta[user]['sex'] = dict1[user]['sex'] \n",
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" re_ta[user]['unit'] = dict1[user]['unit']\n",
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" item_name = item[m_item]['name']\n",
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" re_ta[user].setdefault(item_name,{}) \n",
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" score = int(result[4])/item[m_item]['divisor'] \n",
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" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
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" re_ta[user][item_name]['得分'] = result[5]\n",
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"print(len(re_ta))\n",
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"filename = 'data/result_北京农行.json'\n",
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"\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": "928790e6-d8a4-4b2b-852a-3c323380a80f",
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"metadata": {},
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"source": [
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"## 成绩导出"
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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": "b870bd6e-f972-4073-b13d-5fda8cc92bb7",
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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 openpyxl\n",
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"\n",
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"items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
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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_北京农行.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/北京农行人员名单all.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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" 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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" list2.append(v[item]['得分']) \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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" list2.append('') \n",
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" list1.append(list2)\n",
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"filename = 'data/北京农行体测情况.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": "dd2034ca-fe8b-4322-b06d-8c5eaf96373d",
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"metadata": {},
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"source": [
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"## 报告按部门分类更名"
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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": "04967ec6-b9a0-4097-9e1f-8beaf8a9e75f",
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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 os,sys,shutil\n",
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"import json\n",
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"import math\n",
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"import glob\n",
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"from pathlib import Path\n",
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"\n",
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"fi_path = 'file/2023-05-23'\n",
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"old = []\n",
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"dict2 = {}\n",
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"\n",
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"filename = 'data/result_北京农行.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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"for k, v in dict1.items():\n",
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" m_name = v['name']\n",
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" m_depart = v['unit'] \n",
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" dict2[int(k)] = [m_name,m_depart]\n",
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"\n",
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"fls = glob.glob(f'{fi_path}/*.pdf')\n",
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"\n",
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"for fn in fls:\n",
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" old.append(os.path.basename(fn).split('.')[0])\n",
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"\n",
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"for n in old: \n",
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" o_name = f'{fi_path}/{n}.pdf'\n",
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" new_path = Path(fi_path,'new',dict1[n]['unit'])\n",
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" new_path.mkdir(parents = True, exist_ok = True)\n",
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" n_name = Path(new_path,f'{str(n).rjust(5,\"0\")}-{dict2[int(n)][0]}.pdf')\n",
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" if not os.path.exists(n_name):\n",
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" shutil.copyfile(o_name,n_name)\n",
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" print(n_name)\n",
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" \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": "515bc854-5745-4c38-8633-f56a078ea9a8",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-05-25T09:28:28.615647Z",
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"iopub.status.busy": "2023-05-25T09:28:28.614774Z",
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"iopub.status.idle": "2023-05-25T09:28:28.619865Z",
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"shell.execute_reply": "2023-05-25T09:28:28.618821Z",
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"shell.execute_reply.started": "2023-05-25T09:28:28.615607Z"
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}
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},
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"source": [
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"## 生成人员电话信息表"
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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": "c925d850-ff06-4be5-bf9f-31f4385c37c0",
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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 openpyxl\n",
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"wb = openpyxl.load_workbook('data/农业银行测试手机号码统计表.xlsx')\n",
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"sheet = wb.active\n",
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"# sheets = wb.sheetnames\n",
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"dict1 = {}\n",
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"\n",
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"for n in range(2, sheet.max_row+1):\n",
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" if sheet.cell(n,5).value is not None:\n",
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" phone = str(sheet.cell(n, 5).value)\n",
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" dict1.setdefault(phone,{})\n",
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" code = str(sheet.cell(n, 2).value)\n",
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" unit = sheet.cell(n, 1).value\n",
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" name = sheet.cell(n, 3).value\n",
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" sex = sheet.cell(n, 4).value\n",
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" dict1[phone]['code'] = code\n",
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" dict1[phone]['name'] = name\n",
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" #dict1[phone]['unit'] = unit\n",
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" #dict1[phone]['sex'] = sex\n",
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"filename = 'data/农业银行测试手机号码.json'\n",
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"\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(len(dict1))\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0f13e837-15d9-4dc6-b356-78b79bbb5b17",
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"metadata": {},
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"source": [
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"## 生成验证码"
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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": "a87384c6-dc46-4d09-b757-b42462ed818d",
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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 random\n",
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"import json\n",
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"\n",
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"code_list = []\n",
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"for i in range(10): # 0~9\n",
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" code_list.append(str(i))\n",
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" \n",
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"list1 = []\n",
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"#print(code_num)\n",
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"i = 1\n",
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"while i < 165:\n",
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" code = random.sample(code_list,6) #随机取6位数\n",
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" code_num = ''.join(code)\n",
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" if code_num not in list1:\n",
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" list1.append(code_num)\n",
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" i +=1\n",
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"print(len(list1))\n",
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"print(list1)\n",
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"i = 0\n",
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"filename = 'data/农业银行测试手机号码.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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"for k, v in dict1.items():\n",
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" dict1[k]['yzm'] = list1[i]\n",
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" i +=1\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(dict1, fl, ensure_ascii=False) "
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]
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},
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{
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"cell_type": "markdown",
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"id": "6efc1c2b-7af1-49ec-9b48-8930a8dd2801",
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"metadata": {},
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"source": [
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"## 生成下载链接"
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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": "10845b90-48b4-4418-9dac-dd4a6f0147c0",
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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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"filename = 'data/农业银行测试手机号码.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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"dict2 = {}\n",
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"for k, v in dict1.items():\n",
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" dict2.setdefault(v['yzm'],{})\n",
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" dict2[v['yzm']]['code'] = v['code']\n",
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" dict2[v['yzm']]['name'] = v['name']\n",
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"print(len(dict2))\n",
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"filename = 'data/yzm.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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]
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},
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{
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"cell_type": "markdown",
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"id": "fba0a0c4-edf2-45c2-9199-c6a86919f191",
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"metadata": {},
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"source": [
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"## 发送短信"
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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": "62733f52-62c1-43aa-964a-232eab8b5251",
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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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"from tencentcloud.common import credential\n",
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"from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException\n",
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"from tencentcloud.sms.v20210111 import sms_client, models\n",
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"from tencentcloud.common.profile.client_profile import ClientProfile\n",
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"from tencentcloud.common.profile.http_profile import HttpProfile\n",
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"try: \n",
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" secretId = \"AKID22rVyvSqbikXFFvav31ykc9YmqjN6KYc\"\n",
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" secretKey = \"51XVL1YxDKI6mJh8au6DDuTskS1RhwJX\"\n",
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" cred = credential.Credential(secretId, secretKey) \n",
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" httpProfile = HttpProfile()\n",
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" httpProfile.reqMethod = \"POST\" # post请求(默认为post请求)\n",
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" httpProfile.reqTimeout = 30 # 请求超时时间，单位为秒(默认60秒)\n",
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" httpProfile.endpoint = \"sms.tencentcloudapi.com\" # 指定接入地域域名(默认就近接入)\n",
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" clientProfile = ClientProfile()\n",
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" clientProfile.signMethod = \"TC3-HMAC-SHA256\" # 指定签名算法\n",
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" clientProfile.language = \"en-US\"\n",
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" clientProfile.httpProfile = httpProfile\n",
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" client = sms_client.SmsClient(cred, \"ap-guangzhou\", clientProfile)\n",
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" req = models.SendSmsRequest()\n",
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" req.SmsSdkAppId = \"1400140089\"\n",
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" req.SignName = \"坤铭教育\"\n",
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" req.TemplateId = \"1875765\" \n",
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" req.TemplateParamSet = [\"北京石油分公司体测者\",\"01740518\"]\n",
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" req.PhoneNumberSet = [\"+8613793180751\"]\n",
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" req.SessionContext = \"\"\n",
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" req.ExtendCode = \"\"\n",
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" req.SenderId = \"\"\n",
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" resp = client.SendSms(req)\n",
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" print(resp.to_json_string(indent=2))\n",
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"except TencentCloudSDKException as err:\n",
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" print(err)"
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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": "e924a0a9-65a5-49c4-bdf2-b9152d278ad5",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
|
|
"dict1 = json.loads(resp.to_json_string(indent=2))\n",
|
|
"print(dict1['SendStatusSet'][0][\"Message\"])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c55a8af0-4e4d-4bd4-b5b1-0a7d9170958c",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 批量发送短信（测试）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "910d1881-d090-48dc-ac87-685ccaaf9553",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"\n",
|
|
"from tencentcloud.common import credential\n",
|
|
"from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException\n",
|
|
"from tencentcloud.sms.v20210111 import sms_client, models\n",
|
|
"from tencentcloud.common.profile.client_profile import ClientProfile\n",
|
|
"from tencentcloud.common.profile.http_profile import HttpProfile\n",
|
|
"import json\n",
|
|
"\n",
|
|
"filename = 'data/短信测试手机号码.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"for k, v in dict1.items():\n",
|
|
" phone = '+86'+str(k)\n",
|
|
" yzm = v['yzm']\n",
|
|
" try: \n",
|
|
" secretId = \"AKID22rVyvSqbikXFFvav31ykc9YmqjN6KYc\"\n",
|
|
" secretKey = \"51XVL1YxDKI6mJh8au6DDuTskS1RhwJX\"\n",
|
|
" cred = credential.Credential(secretId, secretKey) \n",
|
|
" httpProfile = HttpProfile()\n",
|
|
" httpProfile.reqMethod = \"POST\" # post请求(默认为post请求)\n",
|
|
" httpProfile.reqTimeout = 30 # 请求超时时间，单位为秒(默认60秒)\n",
|
|
" httpProfile.endpoint = \"sms.tencentcloudapi.com\" # 指定接入地域域名(默认就近接入)\n",
|
|
" clientProfile = ClientProfile()\n",
|
|
" clientProfile.signMethod = \"TC3-HMAC-SHA256\" # 指定签名算法\n",
|
|
" clientProfile.language = \"en-US\"\n",
|
|
" clientProfile.httpProfile = httpProfile\n",
|
|
" client = sms_client.SmsClient(cred, \"ap-guangzhou\", clientProfile)\n",
|
|
" req = models.SendSmsRequest()\n",
|
|
" req.SmsSdkAppId = \"1400140089\"\n",
|
|
" req.SignName = \"坤铭教育\"\n",
|
|
" req.TemplateId = \"1808914\" \n",
|
|
" req.TemplateParamSet = [yzm]\n",
|
|
" req.PhoneNumberSet = [phone]\n",
|
|
" req.SessionContext = \"\"\n",
|
|
" req.ExtendCode = \"\"\n",
|
|
" req.SenderId = \"\"\n",
|
|
" #resp = client.SendSms(req)\n",
|
|
" dict2 = json.loads(resp.to_json_string(indent=2))\n",
|
|
"\n",
|
|
" print(v['name'],dict2['SendStatusSet'][0][\"Message\"])\n",
|
|
" except TencentCloudSDKException as err:\n",
|
|
" print(v['name'],err)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "59d38404-e097-4f08-a3fd-565e351f09bb",
|
|
"metadata": {
|
|
"tags": [],
|
|
"toc-hr-collapsed": true
|
|
},
|
|
"source": [
|
|
"# 第二次体测"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "deeb7606-5752-4337-9117-4ba9edc762e9",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 人员信息导入"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d803a2b2-4a61-42ba-84a3-e9846e3e9f5c",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import openpyxl\n",
|
|
"import json\n",
|
|
"\n",
|
|
"\n",
|
|
"wb = openpyxl.load_workbook('data/北京分行员工体质检测情况表.xlsx')\n",
|
|
"sheet = wb.active\n",
|
|
"# sheets = wb.sheetnames\n",
|
|
"person = {}\n",
|
|
"\n",
|
|
"for n in range(2, sheet.max_row+1):\n",
|
|
" if sheet.cell(n,1).value is not None:\n",
|
|
" code = int(sheet.cell(n, 1).value)\n",
|
|
" person.setdefault(code, {})\n",
|
|
" dict1 = {}\n",
|
|
" dict1['name'] = sheet.cell(n, 3).value\n",
|
|
" if sheet.cell(n, 4).value ==1:\n",
|
|
" sex = '男'\n",
|
|
" else:\n",
|
|
" sex = '女'\n",
|
|
" dict1['sex'] = sex\n",
|
|
" birth = str(sheet.cell(n, 5).value).split()[0]\n",
|
|
" dict1['birth'] = birth\n",
|
|
" dict1['unit'] = sheet.cell(n, 2).value\n",
|
|
" if sheet.cell(n,6).value is not None:\n",
|
|
" dict1['phone'] = sheet.cell(n, 6).value \n",
|
|
" person[code] = dict1\n",
|
|
"\n",
|
|
"filename = 'data/北京农行人员名单2308.json'\n",
|
|
"with open(filename, 'w') as fl:\n",
|
|
" json.dump(person, fl, ensure_ascii=False)\n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ff97823f-fd67-45ae-bd78-f209317be6b9",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 成绩导入"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "4adf86dd-addf-490a-9954-5dcac4693868",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import time\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"item = {}\n",
|
|
"unit = {}\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k,v in dict1.items():\n",
|
|
" item[k] = v\n",
|
|
"re_ta = {}\n",
|
|
"dict1 = {}\n",
|
|
"list1 = []\n",
|
|
"filename = 'data/北京农行人员名单2308.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"\n",
|
|
"filename = 'data/places_result_20230825.csv'\n",
|
|
"with open(filename,'r',newline='') as csv_file:\n",
|
|
" fl = csv.reader(csv_file,delimiter=',')\n",
|
|
" header = next(fl) \n",
|
|
" for line in fl:\n",
|
|
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
|
|
" list1.append(line)\n",
|
|
"#print(list1)\n",
|
|
"for result in list1:\n",
|
|
" user = str(result[2])\n",
|
|
" if user in dict1.keys(): \n",
|
|
" m_item = str(result[3]) \n",
|
|
" re_ta.setdefault(user,{}) \n",
|
|
" re_ta[user]['name'] = dict1[user]['name']\n",
|
|
" re_ta[user]['sex'] = dict1[user]['sex'] \n",
|
|
" re_ta[user]['unit'] = dict1[user]['unit']\n",
|
|
" item_name = item[m_item]['name']\n",
|
|
" re_ta[user].setdefault(item_name,{}) \n",
|
|
" score = int(result[4])/item[m_item]['divisor'] \n",
|
|
" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
|
|
"print(len(re_ta))\n",
|
|
"filename = 'data/result_北京农行0825.json'\n",
|
|
"\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(re_ta, fl, ensure_ascii=False) \n",
|
|
"print(len(re_ta))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "bb01b9a9-418d-4a1b-8ea9-1215af0b8285",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import time\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"item = {}\n",
|
|
"unit = {}\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k,v in dict1.items():\n",
|
|
" item[k] = v\n",
|
|
"re_ta = {}\n",
|
|
"dict1 = {}\n",
|
|
"list1 = []\n",
|
|
"filename = 'data/北京农行人员名单2308.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"\n",
|
|
"filename = 'data/places_result_20230825.csv'\n",
|
|
"with open(filename,'r',newline='') as csv_file:\n",
|
|
" fl = csv.reader(csv_file,delimiter=',')\n",
|
|
" header = next(fl) \n",
|
|
" for line in fl:\n",
|
|
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
|
|
" list1.append(line)\n",
|
|
"#print(list1)\n",
|
|
"for result in list1:\n",
|
|
" user = str(result[2])\n",
|
|
" if user in dict1.keys(): \n",
|
|
" m_item = str(result[3]) \n",
|
|
" re_ta.setdefault(user,{}) \n",
|
|
" re_ta[user]['name'] = dict1[user]['name']\n",
|
|
" re_ta[user]['sex'] = dict1[user]['sex'] \n",
|
|
" re_ta[user]['unit'] = dict1[user]['unit']\n",
|
|
" item_name = item[m_item]['name']\n",
|
|
" re_ta[user].setdefault(item_name,{}) \n",
|
|
" score = int(result[4])/item[m_item]['divisor'] \n",
|
|
" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
|
|
"print(len(re_ta))\n",
|
|
"filename = 'data/result_北京农行0825.json'\n",
|
|
"\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(re_ta, fl, ensure_ascii=False) \n",
|
|
"print(len(re_ta))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "4d2a0d63-4124-4063-96a7-a02478b9eabe",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 查看项目不足人员"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b26857af-5fa3-42d0-bf79-bc33d9f5e4a8",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import time\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"filename = 'data/result_北京农行0825.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"i= 0\n",
|
|
"for k, v in dict1.items():\n",
|
|
" if len(v.keys())< 8:\n",
|
|
" print(k,v['name'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1966307c-4161-4c5b-b19a-b8a143972223",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 导出测试人员信息"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "288e39fb-b7e3-4566-ac13-ba98d7e72edb",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"\n",
|
|
"filename = 'data/result_北京农行0825.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"list1 =[]\n",
|
|
"for k, v in dict1.items():\n",
|
|
" list2 = []\n",
|
|
" list2 = [k,v['name'],v['sex'],v['unit']]\n",
|
|
" list1.append(list2)\n",
|
|
"filename = 'data/北京农行测试人员202308.xlsx'\n",
|
|
"wb = openpyxl.Workbook()\n",
|
|
"sheet = wb.active\n",
|
|
"\n",
|
|
"for row in list1:\n",
|
|
" sheet.append(row)\n",
|
|
" \n",
|
|
"wb.save(filename)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "a42cb587-8673-4655-8943-3cbd63f22b73",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 检查性别"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6352b95c-0e19-4943-9e99-218138213060",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"\n",
|
|
"filename = 'data/result_北京农行0825.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"for k, v in dict1.items():\n",
|
|
" if v['sex'] == '男' and '一分钟仰卧起坐' in v.keys():\n",
|
|
" print(k,'应为女性！')\n",
|
|
" if v['sex'] == '女' and '俯卧撑' in v.keys():\n",
|
|
" print(k,'应为男性！')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "fddd68cd-b20c-4cf9-b503-5d59f52e3c1b",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 手工数据生成SQL"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "372294de-5370-41c0-9883-b18de9d8ef7e",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import openpyxl\n",
|
|
"import json\n",
|
|
"\n",
|
|
"\n",
|
|
"wb = openpyxl.load_workbook('data/北京农行测试人员202308.xlsx')\n",
|
|
"sheet = wb.active\n",
|
|
"# sheets = wb.sheetnames\n",
|
|
"dict1 = {}\n",
|
|
"\n",
|
|
"data1 =list(sheet.values)\n",
|
|
"del data1[0]\n",
|
|
"list1 = []\n",
|
|
"for item in data1:\n",
|
|
" code = int(item[0])\n",
|
|
" list1.append((309118,code,5,item[4],'2023-08-23','2023-08-23 22:00:00'))\n",
|
|
"print(list1)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c32bdb5c-d987-4b0f-98e3-9ce4e3ef3671",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 核对问卷人员信息"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c1b187e0-f566-43fa-88d8-090deb9ead19",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"\n",
|
|
"filename = 'data/北京农行人员名单2308.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
" \n",
|
|
"filename = 'data/Survey_20230913.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",
|
|
" code = str(line[4])\n",
|
|
" name = line[3]\n",
|
|
" \n",
|
|
" if code not in dict1.keys() or name!= dict1[code]['name']:\n",
|
|
" print(code,name)\n",
|
|
" \n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "39cd284f-99fe-4ba0-928c-9da01042e394",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 合并人员信息"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "7ef51041-ad78-4c6a-af83-ed3e0473b199",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"filename = 'data/北京农行人员名单2308.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"\n",
|
|
"filename = 'data/北京农行人员名单.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict2 = json.load(fl) \n",
|
|
"for k, v in dict2.items():\n",
|
|
" dict1[k] = v\n",
|
|
"filename = 'data/北京农行人员名单all.json'\n",
|
|
"\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl, ensure_ascii=False) \n",
|
|
"print(len(re_ta))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3877fc60-171c-434a-aa27-8f1fe9936dd2",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 报告按部门分类"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "80a85fcd-0597-4b58-898f-de420239919f",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import os,sys,shutil\n",
|
|
"import json\n",
|
|
"import glob\n",
|
|
"from pathlib import Path\n",
|
|
"\n",
|
|
"fi_path = '/home/songyi/python/mycrm/flask/pdf/files/309118'\n",
|
|
"new_path = 'file/309118'\n",
|
|
"old = []\n",
|
|
"dict2 = {}\n",
|
|
"\n",
|
|
"filename = 'data/北京农行人员名单all.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
|
"for fn in fls:\n",
|
|
" fi_name =Path(fn).stem.split('-')[0]\n",
|
|
" code = int(fi_name)\n",
|
|
" unit_path = Path(new_path,dict1[str(code)]['unit'])\n",
|
|
" unit_path.mkdir(parents = True, exist_ok = True)\n",
|
|
" n_name = Path(unit_path,Path(fn).stem+'.pdf')\n",
|
|
" if not os.path.exists(n_name):\n",
|
|
" shutil.copyfile(fn,n_name)\n",
|
|
" print(n_name)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3022dcdd-8700-468f-86ab-6ce43b118e1c",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 生成体测报告打印明细表"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "24433f75-6397-4b12-870e-611b77db8ded",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import os,sys,shutil\n",
|
|
"import json\n",
|
|
"import glob\n",
|
|
"from pathlib import Path\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"fi_path = '/home/songyi/python/mycrm/flask/pdf/files/309118'\n",
|
|
"new_path = 'file/309118'\n",
|
|
"list1 = []\n",
|
|
"filename = 'data/北京农行人员名单all.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
|
"for fn in fls:\n",
|
|
" list2 = []\n",
|
|
" fi_name =Path(fn).stem.split('-')[0] \n",
|
|
" code = int(fi_name)\n",
|
|
" unit = dict1[str(code)]['unit']\n",
|
|
" list2 = [fi_name,Path(fn).stem.split('-')[1],unit]\n",
|
|
" list1.append(list2)\n",
|
|
"filename = 'data/北京农行体测报告打印明细表.xlsx'\n",
|
|
"wb = openpyxl.Workbook()\n",
|
|
"sheet = wb.active\n",
|
|
"sheet.append(title)\n",
|
|
"for row in list1:\n",
|
|
" sheet.append(row)\n",
|
|
" \n",
|
|
"wb.save(filename) \n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d71a24d1-ab29-4852-9bfc-384deb8f57a5",
|
|
"metadata": {
|
|
"jp-MarkdownHeadingCollapsed": true,
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"# 数据分析"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d70ab6c9-4fb7-4f0d-864d-96e0ce05fb64",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 获取清理后数据"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "ac3b256e-7470-4cfa-b2ee-eb1110c9097c",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import time\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"item = {}\n",
|
|
"unit = {}\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k,v in dict1.items():\n",
|
|
" item[k] = v\n",
|
|
"filename = 'data/北京农行人员名单all.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
"re_ta = {}\n",
|
|
"list1 = []\n",
|
|
"#print(\"\\n运动项目信息：\")\n",
|
|
"filename = 'data/places_result_20230922-1695356859947.csv'\n",
|
|
"with open(filename,'r',newline='') as csv_file:\n",
|
|
" fl = csv.reader(csv_file,delimiter=',')\n",
|
|
" header = next(fl) \n",
|
|
" for line in fl:\n",
|
|
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
|
|
" list1.append(line)\n",
|
|
"#print(list1)\n",
|
|
"for result in list1:\n",
|
|
" user = str(result[2])\n",
|
|
" if user in dict1.keys(): \n",
|
|
" m_item = str(result[3]) \n",
|
|
" re_ta.setdefault(user,{}) \n",
|
|
" re_ta[user]['name'] = dict1[user]['name']\n",
|
|
" \n",
|
|
" re_ta[user]['sex'] = dict1[user]['sex']\n",
|
|
" re_ta[user]['birth'] = dict1[user]['birth'].replace('-','/')\n",
|
|
" item_name = item[m_item]['name']\n",
|
|
" re_ta[user].setdefault(item_name,{}) \n",
|
|
" score = int(result[4])/item[m_item]['divisor'] \n",
|
|
" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
|
|
" re_ta[user][item_name]['得分'] =result[5]\n",
|
|
"\n",
|
|
"print(len(re_ta))\n",
|
|
"liwai = []\n",
|
|
"for k, v in re_ta.items():\n",
|
|
" if (len(v)<8 and '身高' in v and '体重' in v) or (len(v)<7 and '身高' not in v and '体重' not in v) :\n",
|
|
" liwai.append(k)\n",
|
|
"print(liwai)\n",
|
|
"for k in liwai:\n",
|
|
" del re_ta[k]\n",
|
|
"print(len(re_ta))\n",
|
|
"filename = 'data/result_北京农行all.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(re_ta, fl, ensure_ascii=False) \n",
|
|
"print('ok')\n",
|
|
"print(len(re_ta))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "43c0dad1-9b96-4480-ae3d-d7fb4a2a8df5",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算人员年龄"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "567f512c-2f8a-4441-99c1-f091b40dfd3b",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import datetime\n",
|
|
"\n",
|
|
"filename = 'data/result_北京农行all.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"for k, v in dict1.items():\n",
|
|
" #print(k,v)\n",
|
|
" if '.' in v['birth']:\n",
|
|
" birth = v['birth'].split()[0].split('.')\n",
|
|
" else:\n",
|
|
" birth = v['birth'].split()[0].split('/')\n",
|
|
" \n",
|
|
" nian = int(birth[0].strip())\n",
|
|
" yue = int(birth[1].strip())\n",
|
|
" ri = int(birth[2].strip())\n",
|
|
" #print(k,nian,yue,ri)\n",
|
|
" if int(k) < 199:\n",
|
|
" days = (datetime.date(2023, 5, 11)-datetime.date(nian,yue,ri)).days\n",
|
|
" else:\n",
|
|
" days = (datetime.date(2023, 8, 24)-datetime.date(nian,yue,ri)).days\n",
|
|
" v['age'] = int(days/365)\n",
|
|
"filename = 'data/result_北京农行all.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl, ensure_ascii=False) \n",
|
|
"print('ok') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "7b2974f0-8b5e-40b9-a872-b0df27097096",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 汇总人员信息及成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "576f9b57-237f-4376-b795-122a4cd2222a",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"\n",
|
|
"items = ['体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k,v in dict1.items():\n",
|
|
" print(k)\n",
|
|
" score = 0\n",
|
|
" i = 0 \n",
|
|
" for k1,v1 in v.items(): \n",
|
|
" if k1 in items:\n",
|
|
" score = score + int(v1['得分'])\n",
|
|
" i+=1\n",
|
|
" dict1[k]['score'] = round(score/i,2) \n",
|
|
"\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl, ensure_ascii=False) \n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "0fd37ce2-f965-4a46-8207-c5ce9a7b426a",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算测试等级"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "ec2773cb-16ff-4957-aa51-627bfe0caf95",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"dict2['不合格'] = [0,255]\n",
|
|
"dict2['合格'] = [256,332]\n",
|
|
"dict2['良好'] = [333,367]\n",
|
|
"dict2['优秀'] = [368,500]\n",
|
|
"\n",
|
|
"for k1, v1 in dict2.items():\n",
|
|
" di = v1[0]\n",
|
|
" gao = v1[1]\n",
|
|
" i = 0 \n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if int(v['score']*100) in range(di,gao+1):\n",
|
|
" dict1[k]['level'] = k1\n",
|
|
" i+=1\n",
|
|
" if v['sex'] == '男':\n",
|
|
" m = m +1\n",
|
|
" else:\n",
|
|
" f = f+1\n",
|
|
" print(f'{di}~{gao}分人数：{i}人,男性：{m}人,女性:{f}人')\n",
|
|
"\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl) \n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "058f29fc-6de5-42b6-ba07-95d39e014418",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 根据年龄汇总人员信息及成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c605482a-3aa5-46ff-8648-2675408470a8",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" i = 0\n",
|
|
" score = 0\n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1):\n",
|
|
" score = score+v['score']\n",
|
|
" i+=1\n",
|
|
" if v['sex'] == '男':\n",
|
|
" m = m +1\n",
|
|
" \n",
|
|
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人,男性：{m}人')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "8a15ed82-93bb-4e25-a59e-2358c4d47ca5",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 根据年龄汇总人员信息及成绩（男）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a75f1748-444a-4b0f-a38c-79d814a16ae0",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" i = 0\n",
|
|
" score = 0\n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1) and v['sex'] == '男':\n",
|
|
" score = score+v['score']\n",
|
|
" i+=1\n",
|
|
" if i >0:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人')\n",
|
|
" else:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：0分，人数：0人') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "9840c5a8-2a06-4d7b-91f5-d3c2d43d1d02",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 根据年龄汇总人员信息及成绩（女）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d735d1e2-02d3-4768-a5eb-22792791ca23",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" i = 0\n",
|
|
" score = 0\n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1) and v['sex'] == '女':\n",
|
|
" score = score+v['score']\n",
|
|
" i+=1\n",
|
|
" if i >0:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人')\n",
|
|
" else:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：0分，人数：0人') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "f4a02b1d-2468-4430-8f55-3ffaf07efd34",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算平均成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "fc897a81-7727-4f37-8ab3-8e9de72855d6",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"#filename = 'data/result_石家庄.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"i = 1\n",
|
|
"m = 0\n",
|
|
"f = 0\n",
|
|
"score = 0\n",
|
|
"t_score = 0\n",
|
|
"for k,v in dict1.items():\n",
|
|
" if v['sex'] == '男':\n",
|
|
" m = m +1\n",
|
|
" score = score+v['score']\n",
|
|
"print(f'平均成绩：{round(score/m,4)}分，男性：{m}人')\n",
|
|
"t_score = t_score + score\n",
|
|
"score = 0\n",
|
|
"for k,v in dict1.items():\n",
|
|
" if v['sex'] == '女':\n",
|
|
" f = f +1\n",
|
|
" score = score+v['score']\n",
|
|
"print(f'平均成绩：{round(score/f,4)}分，女性：{f}人')\n",
|
|
"t_score = t_score + score\n",
|
|
"print(f'平均成绩：{round(t_score/522,4)}分，总体：522人')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "f4911bde-1a29-4fdf-a7f7-4ebef0905936",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算各年龄段测试等级(女）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "43c8fd61-4bdb-4d8e-8061-f4f186bd1845",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"dict2['不合格'] = [0,255]\n",
|
|
"dict2['合格'] = [256,332]\n",
|
|
"dict2['良好'] = [333,367]\n",
|
|
"dict2['优秀'] = [368,500]\n",
|
|
"dict3 = {}\n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" age = f'{di}-{gao}'\n",
|
|
" dict3.setdefault(age,{})\n",
|
|
" i = 0 \n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1): \n",
|
|
" dict3[age].setdefault(v['level'],0)\n",
|
|
" if v['sex'] == '女':\n",
|
|
" dict3[age][v['level']] = dict3[age][v['level']]+1\n",
|
|
" \n",
|
|
"for k, v in dict3.items():\n",
|
|
" print(k,v)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "6b5d0882-6c64-4e39-813b-a4c3ebb98006",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算各年龄段测试等级(男）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "aefe62b7-8fcf-43e0-a525-a8584b064167",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"dict2['不合格'] = [0,255]\n",
|
|
"dict2['合格'] = [256,332]\n",
|
|
"dict2['良好'] = [333,367]\n",
|
|
"dict2['优秀'] = [368,500]\n",
|
|
"dict3 = {}\n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" age = f'{di}-{gao}'\n",
|
|
" dict3.setdefault(age,{})\n",
|
|
" i = 0 \n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1): \n",
|
|
" dict3[age].setdefault(v['level'],0)\n",
|
|
" if v['sex'] == '男':\n",
|
|
" dict3[age][v['level']] = dict3[age][v['level']]+1\n",
|
|
" \n",
|
|
"for k, v in dict3.items():\n",
|
|
" print(k,v)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "446217a9-4805-4627-a904-ca734e348433",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算各项目成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "23b7518c-7434-467d-8d38-642f78bde7d9",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"items = ['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",
|
|
"for item in items:\n",
|
|
" score = 0\n",
|
|
" n = 0\n",
|
|
" for k, v in dict1.items():\n",
|
|
" if item in v.keys():\n",
|
|
" n = n + 1\n",
|
|
" score =score + int(v[item]['得分'])\n",
|
|
" print(item,round(score/n,2),n)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "2774523c-286d-460e-9003-434b4171f963",
|
|
"metadata": {},
|
|
"source": [
|
|
"# 百日筑基"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1f30663e-2790-4e0e-a5e5-9088941fe6d9",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 整理人员信息"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "4a99a23f-3b9e-438f-aaa3-79992112f9d2",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"filename = 'data/北京农行人员名单all.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict2 = json.load(fl)\n",
|
|
"list1 = ['握力组', '平衡组', '平和质', '气虚质', '阳虚质', '阴虚质', '痰湿质', '湿热质', '血瘀质', '气郁质', '特禀质'] \n",
|
|
"wb = openpyxl.load_workbook('data/北京农行体测分组情况.xlsx')\n",
|
|
"#sheet = wb.active\n",
|
|
"#sheets = wb.sheetnames\n",
|
|
"for item in list1:\n",
|
|
" sheet = wb[item]\n",
|
|
" for n in range(2, sheet.max_row+1):\n",
|
|
" if sheet.cell(n,1).value is not None:\n",
|
|
" code = int(sheet.cell(n, 1).value)\n",
|
|
" person.setdefault(code, {})\n",
|
|
" dict1 = {}\n",
|
|
" dict1['name'] = dict2[str(code)]['name']\n",
|
|
" dict1['phone'] = dict2[str(code)]['phone']\n",
|
|
" dict1['unit'] = item\n",
|
|
" name = sheet.cell(n, 2).value\n",
|
|
" person[code] = dict1\n",
|
|
"\n",
|
|
"filename = 'data/北京农行百日筑基.json'\n",
|
|
"with open(filename, 'w') as fl:\n",
|
|
" json.dump(person, fl, ensure_ascii=False)\n",
|
|
"print('ok') \n",
|
|
" \n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "2afc474b-daa9-4524-afdf-eed2d7a9e40f",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 人员分组"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "4bd746d9-b573-4cdb-a536-008fe9cc1517",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"item = {\n",
|
|
" '血瘀质':'term_6547430d71970_aIWYoQ',\n",
|
|
" '湿热质':'term_6547428956b35_BlEnpY',\n",
|
|
" '痰湿质':'term_654742123c1bd_hPSDR4',\n",
|
|
" '气虚质':'term_654741bc7c0fe_bf0PLC',\n",
|
|
" '气郁质':'term_6547415695b85_5FAHbR',\n",
|
|
" '阴虚质':'term_654740fdb2e6b_0pBU7m',\n",
|
|
" '阳虚质':'term_654740777e521_tsKUsG',\n",
|
|
" '特禀质':'term_65473fd157db4_FmXOE9',\n",
|
|
" '平和质':'term_65473f50247a5_bGI0dX',\n",
|
|
" '平衡组':'term_65473efbcc37f_dJgc2H',\n",
|
|
" '握力组':'term_65472c788dbf6_5Hj3iw'\n",
|
|
"}\n",
|
|
"filename = 'data/北京农行百日筑基.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"for k, v in dict1.items():\n",
|
|
" url = 'https://appvaCALBPV5946.h5.xiaoeknow.com/p/course/camp/'+item[v['unit']]\n",
|
|
" print(v['unit'],url)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "2112bdec-bd4e-46b7-88cb-ec53e70ad844",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 报告添加水印"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 137,
|
|
"id": "ced8ec31-2b80-4ba1-901a-233f0c31c32c",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2023-12-28T03:47:55.677670Z",
|
|
"iopub.status.busy": "2023-12-28T03:47:55.677205Z",
|
|
"iopub.status.idle": "2023-12-28T03:48:41.694191Z",
|
|
"shell.execute_reply": "2023-12-28T03:48:41.693753Z",
|
|
"shell.execute_reply.started": "2023-12-28T03:47:55.677631Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"ok!\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import os,sys,shutil\n",
|
|
"import json\n",
|
|
"import glob\n",
|
|
"from pathlib import Path\n",
|
|
"import PyPDF2\n",
|
|
"\n",
|
|
"\n",
|
|
"pdfWriter = PyPDF2.PdfWriter() \n",
|
|
"\n",
|
|
"fi_path = '/home/songyi/python/mycrm/flask/pdf/files/309118_1'\n",
|
|
"new_path = 'file/309118_sy'\n",
|
|
"\n",
|
|
"filename = 'data/北京农行百日筑基.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
"water = PyPDF2.PdfReader('data/气虚质.pdf').pages[0]\n",
|
|
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
|
"for fn in fls:\n",
|
|
" reader = PyPDF2.PdfReader(fn)\n",
|
|
" writer = PyPDF2.PdfWriter()\n",
|
|
" num = len(reader.pages)\n",
|
|
" code =str(int(Path(fn).stem.split('-')[0]))\n",
|
|
" sy_fn = 'data/'+dict1[code]['unit']+'.pdf'\n",
|
|
" water = PyPDF2.PdfReader(sy_fn).pages[0]\n",
|
|
" for i in range(num):\n",
|
|
" page = reader.pages[i]\n",
|
|
" if i == num -1:\n",
|
|
" page.merge_page(water)\n",
|
|
" writer.add_page(page)\n",
|
|
" with open(f'file/309118_sy/{Path(fn).stem}.pdf', 'wb') as target_file:\n",
|
|
" writer.write(target_file)\n",
|
|
" \n",
|
|
"print('ok!') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "223fa825-da92-4667-bfc4-d359b87d3385",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 核对有体测无报告人员"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 134,
|
|
"id": "12155bbc-81c7-48c5-a6bf-228184e9382c",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2023-12-28T03:13:06.270708Z",
|
|
"iopub.status.busy": "2023-12-28T03:13:06.270214Z",
|
|
"iopub.status.idle": "2023-12-28T03:13:06.288938Z",
|
|
"shell.execute_reply": "2023-12-28T03:13:06.288393Z",
|
|
"shell.execute_reply.started": "2023-12-28T03:13:06.270668Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"['11', '27', '28', '29', '31', '32', '34', '42', '47', '52', '60', '64', '75', '84', '85', '87', '98', '103', '104', '105', '106', '111', '113', '114', '118', '119', '123', '137', '151', '162', '222']\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import os,sys,shutil\n",
|
|
"import json\n",
|
|
"import glob\n",
|
|
"from pathlib import Path\n",
|
|
"import PyPDF2\n",
|
|
"\n",
|
|
"\n",
|
|
"pdfWriter = PyPDF2.PdfWriter() \n",
|
|
"\n",
|
|
"fi_path = '/home/songyi/python/mycrm/flask/pdf/files/309118'\n",
|
|
"new_path = 'file/309118_sy'\n",
|
|
"\n",
|
|
"filename = 'data/北京农行百日筑基.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
"list1 = []\n",
|
|
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
|
"for fn in fls:\n",
|
|
" code =str(int(Path(fn).stem.split('-')[0]))\n",
|
|
" list1.append(code)\n",
|
|
"list2 = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" if k not in list1 and k!='50':\n",
|
|
" list2.append(k)\n",
|
|
"print(list2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "95c57366-499f-4fa6-9504-2bb67e61d203",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 补充第一次测试人员报告"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 133,
|
|
"id": "edfbc320-a295-4564-b1e5-9165df5fbb22",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2023-12-28T03:12:46.687698Z",
|
|
"iopub.status.busy": "2023-12-28T03:12:46.687241Z",
|
|
"iopub.status.idle": "2023-12-28T03:12:46.720241Z",
|
|
"shell.execute_reply": "2023-12-28T03:12:46.719132Z",
|
|
"shell.execute_reply.started": "2023-12-28T03:12:46.687658Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"30\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import json\n",
|
|
"import datetime\n",
|
|
"import csv\n",
|
|
"from datetime import date\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"item = {}\n",
|
|
"unit = {}\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k,v in dict1.items():\n",
|
|
" item[k] = v\n",
|
|
"item['1']['en'] = 'lung'\n",
|
|
"item['2']['en'] = 'grip'\n",
|
|
"item['3']['en'] = 'flexion'\n",
|
|
"item['4']['en'] = 'jump'\n",
|
|
"item['5']['en'] = 'pushup'\n",
|
|
"item['6']['en'] = 'balance'\n",
|
|
"item['7']['en'] = 'reaction'\n",
|
|
"item['8']['en'] = 'step'\n",
|
|
"item['9']['en'] = 'situp'\n",
|
|
"item['10']['en'] = 'height'\n",
|
|
"item['11']['en'] = 'weight'\n",
|
|
"\n",
|
|
"\n",
|
|
"re_ta = {}\n",
|
|
"dict1 = {}\n",
|
|
"list1 = []\n",
|
|
"filename = 'data/北京农行人员名单all.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"\n",
|
|
"filename = 'data/places_result_20231228.csv'\n",
|
|
"with open(filename,'r',newline='') as csv_file:\n",
|
|
" fl = csv.reader(csv_file,delimiter=',')\n",
|
|
" header = next(fl) \n",
|
|
" for line in fl:\n",
|
|
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
|
|
" list1.append(line)\n",
|
|
"#f_item = ['lung','grip','flexion','jump','balance','reaction','step','situp']\n",
|
|
"#m_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step']\n",
|
|
"for result in list1:\n",
|
|
" user = str(result[2])\n",
|
|
" if user in list2:\n",
|
|
" rq = date.fromisoformat(result[6].replace('/','-'))\n",
|
|
" if user in dict1.keys():\n",
|
|
" l_xm = []\n",
|
|
" m_item = str(result[3]) \n",
|
|
" re_ta.setdefault(user,{}) \n",
|
|
" re_ta[user]['name'] = dict1[user]['name']\n",
|
|
" re_ta[user]['sex'] = dict1[user]['sex']\n",
|
|
" if dict1[user]['sex'] == '男':\n",
|
|
" l_xm = ['weight','height','lung','grip','flexion','jump','pushup','balance','reaction','step']\n",
|
|
" else:\n",
|
|
" l_xm = ['weight','height','lung','grip','flexion','jump','balance','reaction','step','situp']\n",
|
|
" re_ta[user]['unit'] = dict1[user]['unit']\n",
|
|
" birth = date.fromisoformat(dict1[user]['birth'].replace('/','-'))\n",
|
|
" #nian = int(birth[0].strip())\n",
|
|
" #yue = int(birth[1].strip())\n",
|
|
" #ri = int(birth[2].strip())\n",
|
|
" #print(k,nian,yue,ri)\n",
|
|
" item_name = item[m_item]['en'] \n",
|
|
" if item_name in l_xm: \n",
|
|
" days = (rq-birth).days \n",
|
|
" re_ta[user]['age'] = int(days/365)\n",
|
|
" re_ta[user]['month'] = int(days/365*12)\n",
|
|
" re_ta[user]['rq'] = result[6]\n",
|
|
"\n",
|
|
"\n",
|
|
" re_ta[user].setdefault(item_name,{}) \n",
|
|
" score = int(result[4])/item[m_item]['divisor'] \n",
|
|
" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
|
|
" #print(len(re_ta))\n",
|
|
"filename = 'data/result_北京农行补充人员.json'\n",
|
|
"\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(re_ta, fl, ensure_ascii=False) \n",
|
|
"print(len(re_ta))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 135,
|
|
"id": "8e578850-ea32-45e4-a78f-646c2a7aee1d",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2023-12-28T03:20:49.080841Z",
|
|
"iopub.status.busy": "2023-12-28T03:20:49.080377Z",
|
|
"iopub.status.idle": "2023-12-28T03:20:59.726002Z",
|
|
"shell.execute_reply": "2023-12-28T03:20:59.724866Z",
|
|
"shell.execute_reply.started": "2023-12-28T03:20:49.080802Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"30\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_北京农行补充人员.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"list1 = []\n",
|
|
"fiie_path ='./北京农行补充/'\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'] = fiie_path+id+'-'+ v['name']+'.pdf'\n",
|
|
" mydata['title'] = '中国农业银行股份有限公司'\n",
|
|
" mydata['subtitle'] = '北京市分行'\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','psy','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",
|
|
" \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": "3fcb653d-8f2b-4f01-99e0-9e563631563b",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 生成手机验证码"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 138,
|
|
"id": "2fc466e3-80cf-4357-8910-94f8548cd3a5",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2023-12-28T03:57:03.930890Z",
|
|
"iopub.status.busy": "2023-12-28T03:57:03.930680Z",
|
|
"iopub.status.idle": "2023-12-28T03:57:04.143869Z",
|
|
"shell.execute_reply": "2023-12-28T03:57:04.143389Z",
|
|
"shell.execute_reply.started": "2023-12-28T03:57:03.930868Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"ok\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import openpyxl\n",
|
|
"import os,sys,shutil\n",
|
|
"import json\n",
|
|
"import math\n",
|
|
"import glob\n",
|
|
"import random\n",
|
|
"from pathlib import Path\n",
|
|
"import pymongo\n",
|
|
"\n",
|
|
"myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
|
|
"mydb = myclient[\"baogao\"]\n",
|
|
"\n",
|
|
"place_id = 309118\n",
|
|
"place_code = '03'\n",
|
|
"dw_name = '中国农业银行股份有限公司北京市分行'\n",
|
|
"fi_path = '/home/songyi/python/mycrm/flask/pdf/files'\n",
|
|
"fls = glob.glob(f'{fi_path}/{str(place_id)}/*.pdf')\n",
|
|
"\n",
|
|
"code_list = []\n",
|
|
"for i in range(10): # 0~9\n",
|
|
" code_list.append(str(i))\n",
|
|
" \n",
|
|
"list1 = []\n",
|
|
"i = 0\n",
|
|
"while i < len(fls):\n",
|
|
" code = random.sample(code_list,4) #随机取4位数\n",
|
|
" code_num = ''.join(code) \n",
|
|
" if place_code+code_num not in list1:\n",
|
|
" list1.append(place_code+code_num)\n",
|
|
" i +=1\n",
|
|
"i = 0\n",
|
|
"list2= []\n",
|
|
"for fn in fls:\n",
|
|
" dict2 = {}\n",
|
|
" fi_name =Path(fn).stem.split('-')[0]\n",
|
|
" code = int(fi_name)\n",
|
|
" dxm = list1[i]\n",
|
|
" dict2 = {'place_id':place_id,'code':dxm,'fn':Path(fn).name}\n",
|
|
" list2.append(dict2)\n",
|
|
" i +=1\n",
|
|
"mycol = mydb[\"pdf\"]\n",
|
|
"x = mycol.insert_many(list2)\n",
|
|
"print('ok') \n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "4be9bcbe-bfeb-450e-9863-1d49605979a3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.12"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|