389 lines
12 KiB
Plaintext
389 lines
12 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "bf152e7d-6a36-4877-98d9-f11e3a73792e",
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"metadata": {},
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"source": [
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"## 导入人员信息"
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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": 110,
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"id": "1b92b7c5-cb77-49da-95b7-34827ecf1d16",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-04-25T10:41:09.138090Z",
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"iopub.status.busy": "2023-04-25T10:41:09.137225Z",
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"iopub.status.idle": "2023-04-25T10:41:11.696860Z",
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"shell.execute_reply": "2023-04-25T10:41:11.695874Z",
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"shell.execute_reply.started": "2023-04-25T10:41:09.138049Z"
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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/燕山石化人员情况表.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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" if sheet.cell(n, 7).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'] = sheet.cell(n, 3).value\n",
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" birth = str(sheet.cell(n, 6).value).split()[0]\n",
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" dict1['birth'] = birth\n",
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" if sheet.cell(n,5).value is not None:\n",
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" dict1['phone'] = sheet.cell(n, 5).value\n",
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" if sheet.cell(n,7).value is not None:\n",
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" dict1['id_num'] = sheet.cell(n, 7).value\n",
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" if sheet.cell(n,8).value is not None:\n",
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" dict1['SAP'] = sheet.cell(n, 8).value\n",
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" if sheet.cell(n,9).value is not None:\n",
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" dict1['工作单位'] = sheet.cell(n, 9).value\n",
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" if sheet.cell(n,10).value is not None:\n",
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" dict1['车间'] = sheet.cell(n, 10).value\n",
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" else:\n",
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" dict1['车间'] =''\n",
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" if sheet.cell(n,11).value is not None:\n",
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" dict1['班组'] = sheet.cell(n, 11).value\n",
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" else:\n",
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" dict1['班组'] =''\n",
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" if sheet.cell(n,12).value is not None:\n",
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" dict1['工作性质'] = sheet.cell(n, 11).value\n",
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" person[code] = dict1\n",
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"filename = 'data/燕山石化人员名单.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": "f5c73dff-697d-4ba5-a90c-9bed68eaf4b3",
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"metadata": {},
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"source": [
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"## 每日成绩导入"
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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": 111,
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"id": "71e1ec6a-6797-4496-969a-1d1461b9ea58",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-04-25T10:41:24.604593Z",
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"iopub.status.busy": "2023-04-25T10:41:24.603754Z",
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"iopub.status.idle": "2023-04-25T10:41:24.838577Z",
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"shell.execute_reply": "2023-04-25T10:41:24.837823Z",
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"shell.execute_reply.started": "2023-04-25T10:41:24.604553Z"
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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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"454\n",
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"454\n",
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"3099\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/燕山石化人员名单.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_20230425.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]['部门'] = dict1[user]['工作单位']\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_燕山石化.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl)\n",
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"for k in re_ta.keys():\n",
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" if k in dict2.keys():\n",
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" print(k,dict2[k]['name'],'已测试！')\n",
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"for k, v in re_ta.items():\n",
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" if k not in dict2.keys():\n",
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" dict2[k] = v\n",
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" else:\n",
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" for k1,v1 in v.items():\n",
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" dict2[k][k1] = v1\n",
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"filename = 'data/result_燕山石化（20230425）.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(re_ta, fl, ensure_ascii=False) \n",
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"print(len(re_ta))\n",
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"filename = 'data/result_燕山石化.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(dict2, fl, ensure_ascii=False) \n",
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"print(len(dict2))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "79147ba8-4b90-40ba-81a9-e6062600c239",
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"metadata": {},
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"source": [
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"## 每日成绩导出"
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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": 112,
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"id": "c24880ad-bbbd-4ad8-a894-cbcea389e822",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-04-25T10:41:45.914369Z",
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"iopub.status.busy": "2023-04-25T10:41:45.913494Z",
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"iopub.status.idle": "2023-04-25T10:41:46.098743Z",
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"shell.execute_reply": "2023-04-25T10:41:46.098046Z",
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"shell.execute_reply.started": "2023-04-25T10:41:45.914321Z"
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},
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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','车间','班组','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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"filename = 'data/result_燕山石化（20230425）.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/燕山石化人员名单.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]['工作单位']) \n",
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" list2.append(dict2[k]['车间'])\n",
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" list2.append(dict2[k]['班组'])\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/燕山石化体测情况表(20230425).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": "6d431fc1-b743-467c-91b3-9788e245becb",
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"metadata": {},
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"source": [
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"## 统计部门测试人数"
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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": 113,
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"id": "68454877-f1fe-4eed-8a48-265e428f892e",
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"metadata": {
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"execution": {
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||
"iopub.execute_input": "2023-04-25T10:41:58.467679Z",
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||
"iopub.status.busy": "2023-04-25T10:41:58.467274Z",
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||
"iopub.status.idle": "2023-04-25T10:41:58.499250Z",
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||
"shell.execute_reply": "2023-04-25T10:41:58.498205Z",
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||
"shell.execute_reply.started": "2023-04-25T10:41:58.467652Z"
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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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"{'行政事务中心（离退中心）工会': 18, '炼油厂工会': 95, '化学品厂工会': 67, '高科公司工会': 109, '烯烃厂工会': 13, '有机化工厂工会': 98, '储运厂工会': 8, '检验计量中心工会': 16, '教育培训中心工会': 1, '合成橡胶厂工会': 10, '合成树脂厂': 10, '消防中心工会': 1, '生产运行保障中心': 1, '物装中心工会': 2, '机关工会': 5}\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 openpyxl\n",
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"\n",
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"filename = 'data/result_燕山石化（20230425）.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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" unit = v['部门']\n",
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" dict2.setdefault(unit,0)\n",
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" dict2[unit] = dict2[unit] + 1\n",
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"print(dict2)\n",
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"title =['单位','体测人数']\n",
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"list1 = [] \n",
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"for k, v in dict2.items():\n",
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" list2 = []\n",
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" list2 = [k,v]\n",
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" list1.append(list2)\n",
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"filename = 'data/燕山石化部门测试人数情况表(20230425).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": "8becc0af-d22b-46a2-b35e-9122942515d4",
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"metadata": {},
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"source": [
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"## 每日未测试人员情况表"
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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": 26,
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"id": "7085bf6f-7465-44fb-bddb-38130fbe5618",
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||
"metadata": {
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||
"execution": {
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||
"iopub.execute_input": "2023-04-17T12:58:45.236098Z",
|
||
"iopub.status.busy": "2023-04-17T12:58:45.235274Z",
|
||
"iopub.status.idle": "2023-04-17T12:58:46.270936Z",
|
||
"shell.execute_reply": "2023-04-17T12:58:46.270191Z",
|
||
"shell.execute_reply.started": "2023-04-17T12:58:45.236059Z"
|
||
},
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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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"\n",
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"title = ['编号','姓名','性别','单位','车间','班组']\n",
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"filename = 'data/result_燕山石化（20230417）.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/燕山石化人员名单.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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"list1 = []\n",
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"for k, v in dict2.items():\n",
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" list2 = []\n",
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" if k not in dict1.keys():\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]['工作单位']) \n",
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" list2.append(dict2[k]['车间'])\n",
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" list2.append(dict2[k]['班组'])\n",
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" list1.append(list2)\n",
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"filename = 'data/燕山石化未体测人员名单(20230417).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": "code",
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||
"execution_count": null,
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||
"id": "6e1dda56-541b-4afe-8ae7-2a8dd7ec5eac",
|
||
"metadata": {},
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||
"outputs": [],
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||
"source": []
|
||
}
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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": "3.10.6"
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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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}
|