{ "cells": [ { "cell_type": "markdown", "id": "bf152e7d-6a36-4877-98d9-f11e3a73792e", "metadata": {}, "source": [ "## 导入人员信息" ] }, { "cell_type": "code", "execution_count": 149, "id": "1b92b7c5-cb77-49da-95b7-34827ecf1d16", "metadata": { "execution": { "iopub.execute_input": "2023-04-28T23:44:56.066757Z", "iopub.status.busy": "2023-04-28T23:44:56.065886Z", "iopub.status.idle": "2023-04-28T23:44:58.568470Z", "shell.execute_reply": "2023-04-28T23:44:58.567666Z", "shell.execute_reply.started": "2023-04-28T23:44:56.066716Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ok\n" ] } ], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "wb = openpyxl.load_workbook('data/燕山石化人员情况表.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, 2).value\n", " if sheet.cell(n, 7).value ==1:\n", " sex = '男'\n", " else:\n", " sex = '女'\n", " dict1['sex'] = sheet.cell(n, 3).value\n", " birth = str(sheet.cell(n, 6).value).split()[0]\n", " dict1['birth'] = birth\n", " if sheet.cell(n,5).value is not None:\n", " dict1['phone'] = sheet.cell(n, 5).value\n", " if sheet.cell(n,7).value is not None:\n", " dict1['id_num'] = sheet.cell(n, 7).value\n", " if sheet.cell(n,8).value is not None:\n", " dict1['SAP'] = sheet.cell(n, 8).value\n", " if sheet.cell(n,9).value is not None:\n", " dict1['工作单位'] = sheet.cell(n, 9).value\n", " if sheet.cell(n,10).value is not None:\n", " dict1['车间'] = sheet.cell(n, 10).value\n", " else:\n", " dict1['车间'] =''\n", " if sheet.cell(n,11).value is not None:\n", " dict1['班组'] = sheet.cell(n, 11).value\n", " else:\n", " dict1['班组'] =''\n", " if sheet.cell(n,12).value is not None:\n", " dict1['工作性质'] = sheet.cell(n, 11).value\n", " person[code] = dict1\n", "filename = 'data/燕山石化人员名单.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "f5c73dff-697d-4ba5-a90c-9bed68eaf4b3", "metadata": {}, "source": [ "## 每日成绩导入" ] }, { "cell_type": "code", "execution_count": 150, "id": "71e1ec6a-6797-4496-969a-1d1461b9ea58", "metadata": { "execution": { "iopub.execute_input": "2023-04-28T23:45:21.332726Z", "iopub.status.busy": "2023-04-28T23:45:21.331812Z", "iopub.status.idle": "2023-04-28T23:45:21.591418Z", "shell.execute_reply": "2023-04-28T23:45:21.590691Z", "shell.execute_reply.started": "2023-04-28T23:45:21.332693Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "335\n", "123 孙剑 已测试！\n", "335\n", "4136\n" ] } ], "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/燕山石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "\n", "filename = 'data/places_result_20230428.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]['部门'] = dict1[user]['工作单位']\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_燕山石化.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "for k in re_ta.keys():\n", " if k in dict2.keys():\n", " print(k,dict2[k]['name'],'已测试！')\n", "for k, v in re_ta.items():\n", " if k not in dict2.keys():\n", " dict2[k] = v\n", " else:\n", " for k1,v1 in v.items():\n", " dict2[k][k1] = v1\n", "filename = 'data/result_燕山石化（20230428）.json'\n", "with open(filename,'w') as fl:\n", " json.dump(re_ta, fl, ensure_ascii=False) \n", "print(len(re_ta))\n", "filename = 'data/result_燕山石化.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict2, fl, ensure_ascii=False) \n", "print(len(dict2))" ] }, { "cell_type": "markdown", "id": "79147ba8-4b90-40ba-81a9-e6062600c239", "metadata": {}, "source": [ "## 每日成绩导出" ] }, { "cell_type": "code", "execution_count": 151, "id": "c24880ad-bbbd-4ad8-a894-cbcea389e822", "metadata": { "execution": { "iopub.execute_input": "2023-04-28T23:46:14.648250Z", "iopub.status.busy": "2023-04-28T23:46:14.647361Z", "iopub.status.idle": "2023-04-28T23:46:14.803308Z", "shell.execute_reply": "2023-04-28T23:46:14.802604Z", "shell.execute_reply.started": "2023-04-28T23:46:14.648208Z" }, "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "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", "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", "\n", "filename = 'data/result_燕山石化（20230428）.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/燕山石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", " \n", "list1 = []\n", "for k, v in dict1.items():\n", " list2 = []\n", " list2.append(str(k).rjust(5,'0'))\n", " list2.append(v['name']) \n", " list2.append(dict2[k]['sex'])\n", " list2.append(dict2[k]['工作单位']) \n", " list2.append(dict2[k]['车间'])\n", " list2.append(dict2[k]['班组'])\n", " for item in items:\n", " if item in v.keys():\n", " list2.append(v[item]['成绩']) \n", " elif item =='name':\n", " list2.append(v[item])\n", " else:\n", " list2.append('') \n", " list1.append(list2)\n", "filename = 'data/燕山石化体测情况表(20230428).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)" ] }, { "cell_type": "markdown", "id": "6d431fc1-b743-467c-91b3-9788e245becb", "metadata": {}, "source": [ "## 统计部门测试人数" ] }, { "cell_type": "code", "execution_count": 152, "id": "68454877-f1fe-4eed-8a48-265e428f892e", "metadata": { "execution": { "iopub.execute_input": "2023-04-28T23:46:28.786698Z", "iopub.status.busy": "2023-04-28T23:46:28.786246Z", "iopub.status.idle": "2023-04-28T23:46:28.816358Z", "shell.execute_reply": "2023-04-28T23:46:28.815328Z", "shell.execute_reply.started": "2023-04-28T23:46:28.786667Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'储运厂工会': 37, '炼油厂工会': 42, '化学品厂工会': 29, '高科公司工会': 69, '有机化工厂工会': 91, '物装中心工会': 3, '合成树脂厂': 10, '热电厂工会': 2, '合成橡胶厂工会': 27, '教育培训中心工会': 2, '烯烃厂工会': 11, '检验计量中心工会': 8, '机关工会': 2, '生产运行保障中心': 2}\n" ] } ], "source": [ "import json\n", "import openpyxl\n", "\n", "filename = 'data/result_燕山石化（20230428）.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "dict2 = {}\n", "for k, v in dict1.items():\n", " unit = v['部门']\n", " dict2.setdefault(unit,0)\n", " dict2[unit] = dict2[unit] + 1\n", "print(dict2)\n", "title =['单位','体测人数']\n", "list1 = [] \n", "for k, v in dict2.items():\n", " list2 = []\n", " list2 = [k,v]\n", " list1.append(list2)\n", "filename = 'data/燕山石化部门测试人数情况表(20230428).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)" ] }, { "cell_type": "markdown", "id": "8becc0af-d22b-46a2-b35e-9122942515d4", "metadata": {}, "source": [ "## 每日未测试人员情况表" ] }, { "cell_type": "code", "execution_count": 26, "id": "7085bf6f-7465-44fb-bddb-38130fbe5618", "metadata": { "execution": { "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" }, "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "\n", "title = ['编号','姓名','性别','单位','车间','班组']\n", "filename = 'data/result_燕山石化（20230417）.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/燕山石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "list1 = []\n", "for k, v in dict2.items():\n", " list2 = []\n", " if k not in dict1.keys():\n", " list2.append(str(k).rjust(5,'0'))\n", " list2.append(v['name']) \n", " list2.append(dict2[k]['sex'])\n", " list2.append(dict2[k]['工作单位']) \n", " list2.append(dict2[k]['车间'])\n", " list2.append(dict2[k]['班组'])\n", " list1.append(list2)\n", "filename = 'data/燕山石化未体测人员名单(20230417).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) " ] }, { "cell_type": "markdown", "id": "3231f52d-776f-4d29-b6f5-c28f6a0c30a9", "metadata": {}, "source": [ "## 汇总未测试人员情况表" ] }, { "cell_type": "code", "execution_count": 148, "id": "eddf7dab-b28d-402a-aeaf-27c120048ecb", "metadata": { "execution": { "iopub.execute_input": "2023-04-27T12:02:16.168114Z", "iopub.status.busy": "2023-04-27T12:02:16.167671Z", "iopub.status.idle": "2023-04-27T12:02:16.802793Z", "shell.execute_reply": "2023-04-27T12:02:16.802099Z", "shell.execute_reply.started": "2023-04-27T12:02:16.168084Z" }, "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "\n", "title = ['编号','姓名','性别','单位','车间','班组']\n", "filename = 'data/result_燕山石化.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "# 筛选重名剔除名单\n", "chongming = []\n", "filename = 'data/燕山石化重名人员测试情况.xlsx'\n", "wb = openpyxl.load_workbook(filename)\n", "sheet = wb.active\n", "for n in range(1, sheet.max_row+1,2):\n", " if sheet.cell(n,1).value is not None:\n", " code1 = int(sheet.cell(n, 1).value)\n", " code2 = int(sheet.cell(n+1, 1).value)\n", " bz1 = sheet.cell(n, 4).value\n", " bz2 = sheet.cell(n+1, 4).value\n", " if bz1 =='否' and bz2 =='否':\n", " chongming.append(max(code1,code2))\n", " else:\n", " chongming.append(code1)\n", " chongming.append(code2)\n", "\n", "filename = 'data/燕山石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "list1 = []\n", "for k, v in dict2.items():\n", " list2 = []\n", " if k not in dict1.keys() and int(k) not in chongming:\n", " list2.append(str(k).rjust(5,'0'))\n", " list2.append(v['name']) \n", " list2.append(dict2[k]['sex'])\n", " list2.append(dict2[k]['工作单位']) \n", " list2.append(dict2[k]['车间'])\n", " list2.append(dict2[k]['班组'])\n", " list1.append(list2)\n", "filename = 'data/燕山石化未体测人员名单(截至20230427).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) " ] }, { "cell_type": "markdown", "id": "4dd9b2b7-bd3d-4d5b-ac84-3a49bcada8b5", "metadata": {}, "source": [ "## 统计测试项目不足人员" ] }, { "cell_type": "code", "execution_count": 123, "id": "641863ef-324f-4c33-a0a9-699031afb6f1", "metadata": { "execution": { "iopub.execute_input": "2023-04-26T11:17:42.517140Z", "iopub.status.busy": "2023-04-26T11:17:42.516342Z", "iopub.status.idle": "2023-04-26T11:17:42.630705Z", "shell.execute_reply": "2023-04-26T11:17:42.629971Z", "shell.execute_reply.started": "2023-04-26T11:17:42.517107Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "7756 张志兴 ['身高', '体重', '肺活量', '握力']\n", "3999 解勇 ['身高', '体重', '肺活量', '握力']\n", "7037 郭维东 ['身高', '体重', '握力', '选择反应时']\n", "57 郑文芬 ['身高', '体重', '坐位体前屈', '握力']\n", "4031 庞荔元 ['身高', '体重', '肺活量', '选择反应时']\n", "4025 马珺 ['身高', '体重', '选择反应时']\n", "7790 吴志鹏 ['身高', '体重', '握力']\n", "4851 李晓甦 ['身高', '体重', '单脚站立', '握力']\n", "8133 张来强 ['身高', '体重', '肺活量', '选择反应时']\n", "5628 康文刚 ['身高', '体重', '肺活量', '握力']\n", "8151 赵春先 ['身高', '体重', '握力']\n", "3699 毛树新 ['身高', '体重', '纵跳', '选择反应时']\n", "1699 孙雪飞 ['身高', '体重', '肺活量', '选择反应时']\n", "1960 徐慧国 ['身高', '体重', '肺活量', '单脚站立']\n", "3563 孙志强 ['身高', '体重', '握力', '纵跳']\n", "7682 孙宏林 ['肺活量', '身高', '体重']\n", "4370 张宝 ['身高', '体重', '肺活量', '选择反应时']\n" ] } ], "source": [ "import json\n", "import openpyxl\n", "\n", "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", "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", "filename = 'data/result_燕山石化.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/燕山石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "dict3 = {}\n", "for k, v in dict1.items():\n", " list1 = []\n", " for item in v.keys():\n", " if item in items:\n", " list1.append(item)\n", " dict3[k] = list1\n", "for k, v in dict3.items():\n", " if len(v)<=4 and '身高' in v and '体重' in v:\n", " print(k,dict2[k]['name'],v)\n", " " ] }, { "cell_type": "markdown", "id": "d3a69840-29fc-434d-af47-ad864f9e511c", "metadata": {}, "source": [ "## 汇总成绩导入" ] }, { "cell_type": "code", "execution_count": 142, "id": "b735248a-c1b0-4e90-8df4-37cd7625cb1a", "metadata": { "execution": { "iopub.execute_input": "2023-04-27T11:19:41.635154Z", "iopub.status.busy": "2023-04-27T11:19:41.634745Z", "iopub.status.idle": "2023-04-27T11:19:41.975500Z", "shell.execute_reply": "2023-04-27T11:19:41.974722Z", "shell.execute_reply.started": "2023-04-27T11:19:41.635125Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3802\n", "3802\n" ] } ], "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/燕山石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "\n", "filename = 'data/places_result_20230427-all.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]['部门'] = dict1[user]['工作单位']\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", "\n", "filename = 'data/result_燕山石化-all.json'\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": "5bdcad97-309f-4d29-82c4-b53c68b9ee22", "metadata": {}, "source": [ "## 统计重复人员信息" ] }, { "cell_type": "code", "execution_count": 132, "id": "0dd5da15-92e0-45c2-b9e9-11417210974e", "metadata": { "execution": { "iopub.execute_input": "2023-04-27T07:22:33.663659Z", "iopub.status.busy": "2023-04-27T07:22:33.662808Z", "iopub.status.idle": "2023-04-27T07:22:35.472369Z", "shell.execute_reply": "2023-04-27T07:22:35.471662Z", "shell.execute_reply.started": "2023-04-27T07:22:33.663618Z" }, "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "\n", "list1 = []\n", "list2 = set()\n", "filename = 'data/燕山石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "filename = 'data/result_燕山石化-all.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl) \n", "\n", "for k,v in dict1.items():\n", " name = v['name']\n", " if name in list1:\n", " list2.add(name)\n", " list1.append(name)\n", "list3 = []\n", "for item in list2:\n", " for k,v in dict1.items():\n", " if v['name'] == item:\n", " list3.append([k,v['name'],v['sex'],v['birth']])\n", "filename = 'data/燕山石化重名人员名单.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "#sheet.append(title)\n", "for row in list3:\n", " sheet.append(row)\n", " \n", "wb.save(filename) " ] }, { "cell_type": "markdown", "id": "96375506-0cca-4a9b-b0da-162460d25e51", "metadata": {}, "source": [ "## 重复人员测试情况" ] }, { "cell_type": "code", "execution_count": 137, "id": "5df8eb8f-3594-40be-a491-b4d750bbd554", "metadata": { "execution": { "iopub.execute_input": "2023-04-27T08:23:39.947764Z", "iopub.status.busy": "2023-04-27T08:23:39.947326Z", "iopub.status.idle": "2023-04-27T08:23:40.072095Z", "shell.execute_reply": "2023-04-27T08:23:40.071367Z", "shell.execute_reply.started": "2023-04-27T08:23:39.947734Z" }, "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "\n", "list1 = []\n", "list2 = set()\n", "filename = 'data/燕山石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "filename = 'data/result_燕山石化-all.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl) \n", "\n", "\n", "list3 = []\n", "\n", "filename = 'data/燕山石化重名人员名单.xlsx'\n", "wb = openpyxl.load_workbook(filename)\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "\n", "\n", "for n in range(1, sheet.max_row+1):\n", " if sheet.cell(n,1).value is not None:\n", " code = int(sheet.cell(n, 1).value)\n", " name = dict1[str(code)]['name']\n", " unit = dict1[str(code)]['工作单位']\n", " if str(code) in dict2.keys():\n", " ce = '是'\n", " else:\n", " ce = '否'\n", " list3.append([code,name,unit,ce])\n", "filename = 'data/燕山石化重名人员测试情况.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "#sheet.append(title)\n", "for row in list3:\n", " sheet.append(row)\n", " \n", "wb.save(filename) " ] }, { "cell_type": "code", "execution_count": null, "id": "bfd8e77d-85a5-44aa-b075-b37278910a3f", "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": "3.10.6" } }, "nbformat": 4, "nbformat_minor": 5 }