20231128
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{
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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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"\n",
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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": 11,
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"id": "bbba6efc-73cd-4db6-bae7-014724fee731",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-11-28T02:30:49.403409Z",
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"iopub.status.busy": "2023-11-28T02:30:49.403129Z",
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"iopub.status.idle": "2023-11-28T02:30:49.433515Z",
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"shell.execute_reply": "2023-11-28T02:30:49.432950Z",
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"shell.execute_reply.started": "2023-11-28T02:30:49.403391Z"
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},
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"tags": []
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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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"ok\n"
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]
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}
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],
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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/中国石化化工销售员工花名册（20231128）.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, 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, 3).value\n",
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" dict1['unit'] = sheet.cell(n, 4).value\n",
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" dict1['id'] = sheet.cell(n,5).value\n",
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" id = str(sheet.cell(n,5).value)\n",
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" birth = id[6:10]+'-'+ id[10:12]+'-' +id[12:14]\n",
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" dict1['birth'] = birth\n",
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" person[code] = dict1\n",
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"filename = 'data/中国石化化工销售.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": 12,
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"id": "ce406710-6b7d-4c51-98ec-78883bd3ce5f",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-11-28T02:32:36.887442Z",
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"iopub.status.busy": "2023-11-28T02:32:36.887196Z",
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"iopub.status.idle": "2023-11-28T02:32:36.893879Z",
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"shell.execute_reply": "2023-11-28T02:32:36.893384Z",
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"shell.execute_reply.started": "2023-11-28T02:32:36.887424Z"
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},
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"tags": []
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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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"ok\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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"\n",
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"filename = 'data/中国石化化工销售.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl)\n",
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"list1 = []\n",
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"for k, v in dict1.items():\n",
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" dict2 = {}\n",
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" #if dict1['sex'] =='男':\n",
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" # sex = 1\n",
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" \n",
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" dict2 = {'id':k,'name':v['name'],'gender':v['sex'],'birth':v['birth'],'unit':v['unit']}\n",
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" list1.append(dict2)\n",
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"json_data = json.dumps(list1,ensure_ascii=False, indent=4) \n",
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"\n",
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"# 将 json 数据写入文件\n",
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"with open(\"data/data_中国石化化工销售.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": 7,
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"id": "970e171e-1360-448f-a28c-520ccb8f314a",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-10-18T02:17:23.733390Z",
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"iopub.status.busy": "2023-10-18T02:17:23.733131Z",
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"iopub.status.idle": "2023-10-18T02:17:23.758353Z",
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"shell.execute_reply": "2023-10-18T02:17:23.757550Z",
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"shell.execute_reply.started": "2023-10-18T02:17:23.733366Z"
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},
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"tags": []
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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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"141\n",
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"141\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 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/北京党校.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_20231018.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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"print(len(re_ta))\n",
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"filename = 'data/result_北京党校.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": "d034a61d-1fbd-417b-99bd-277e43ebb678",
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"metadata": {},
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"source": [
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"## 导出测试人员信息"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "867ad6b0-9e9d-48bc-a10a-3b9cb6125890",
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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','部门','身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
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"\n",
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"filename = 'data/result_北京党校.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/北京党校.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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" 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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" list1.append(list2)\n",
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"filename = 'data/北京党校.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": "699c6a40-a6ae-4300-9646-708cb85aa5e8",
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"metadata": {},
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"source": [
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"## 手工数据导入数据库"
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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 openpyxl\n",
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"import json\n",
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"\n",
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"filename = 'data/北京党校.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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"wb = openpyxl.load_workbook('data/北京党校手工数据.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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"dict3 = {1:10,2:11,3:7,4:2,5:6,6:3,7:1}\n",
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"sheet = wb.active\n",
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"data1 =list(sheet.values)\n",
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"del data1[0]\n",
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"list1 = []\n",
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"for item in data1:\n",
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" code = int(item[0])\n",
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" list1.append((496534,code,item[2],item[1],'2023-10-15','2023-10-15 14:00:00'))\n",
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"print(list1)"
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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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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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