303 lines
9.1 KiB
Plaintext
303 lines
9.1 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "e09ac558-4859-46c8-ba33-bfff63fd1f8e",
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"metadata": {},
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"source": [
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"## 体测人员导入"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "2f3742c3-0247-4304-a580-530102cad1dc",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-04-24T05:31:25.507735Z",
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"iopub.status.busy": "2025-04-24T05:31:25.507412Z",
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"iopub.status.idle": "2025-04-24T05:31:25.525701Z",
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"shell.execute_reply": "2025-04-24T05:31:25.525213Z",
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"shell.execute_reply.started": "2025-04-24T05:31:25.507708Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"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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"from datetime import date\n",
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"from pathlib import Path\n",
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"\n",
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"wb = openpyxl.load_workbook('data/国图测试名单.xlsx')\n",
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"sheet = wb.active\n",
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"sheets = wb.sheetnames\n",
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"\n",
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"filename = 'data/国图人员.json'\n",
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"path = Path(filename)\n",
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"if path.exists():\n",
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" with open(filename,'r') as fl:\n",
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" person = json.load(fl) \n",
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"else:\n",
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" person = {}\n",
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" \n",
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"for n in range(2, sheet.max_row+1):\n",
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" code = int(sheet.cell(n, 1).value)\n",
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" if code not in person.keys():\n",
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" person.setdefault(code, {})\n",
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" dict1 = {}\n",
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" dict1['name'] = sheet.cell(n, 2).value\n",
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" dict1['sex'] = sheet.cell(n, 4).value\n",
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" dict1['birth'] = str(sheet.cell(n, 3).value).replace('/','-').split(' ')[0] \n",
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" if sheet.cell(n,6).value is not None:\n",
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" dict1['phone'] = str(sheet.cell(n,6).value) \n",
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" #dict1['phone'] = str(sheet.cell(n, 5).value)\n",
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" person[code] = dict1\n",
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"filename = 'data/国图人员.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": "b36f7788-0916-45b6-862b-e52d5f6f18d6",
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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": 19,
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"id": "8b649b7e-2608-4954-91ce-66f15b7e7806",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-04-24T05:31:31.562545Z",
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"iopub.status.busy": "2025-04-24T05:31:31.561874Z",
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"iopub.status.idle": "2025-04-24T05:31:31.572577Z",
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"shell.execute_reply": "2025-04-24T05:31:31.571499Z",
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"shell.execute_reply.started": "2025-04-24T05:31:31.562490Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"4\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 datetime\n",
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"import csv\n",
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"from datetime import date\n",
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"import my_module as My\n",
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"\n",
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"filename = 'data/国图人员.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl) \n",
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"filename = 'data/marks_20250424.csv'\n",
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"re_ta = My.get_result(filename,dict1)\n",
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"\n",
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"filename = 'data/result_国图人员.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(re_ta, fl, ensure_ascii=False) \n",
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"print(len(re_ta))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "261b7ded-936b-40cc-a14c-2f48fc191795",
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"metadata": {},
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"source": [
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"## 生成测试得分"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "fa481310-fb25-4523-9558-eef6717452ba",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-04-24T05:31:35.098100Z",
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"iopub.status.busy": "2025-04-24T05:31:35.097683Z",
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"iopub.status.idle": "2025-04-24T05:31:35.104461Z",
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"shell.execute_reply": "2025-04-24T05:31:35.103969Z",
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"shell.execute_reply.started": "2025-04-24T05:31:35.098077Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"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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"import time\n",
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"import my_module as My\n",
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"\n",
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"#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n",
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"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n",
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"filename = 'data/result_国图人员.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl) \n",
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"for k, v in dict2.items():\n",
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" #print(k)\n",
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" if v['sex'] == '男':\n",
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" sex = 'M'\n",
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" else:\n",
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" sex = 'F' \n",
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" if 'bmi' in v.keys():\n",
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" #bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n",
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" bmi_data = v['bmi']['成绩']\n",
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" data1 = {'code':k,'sex':sex,'age':v['age'],'item':'HeightWeight','result':bmi_data}\n",
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" dict2[k]['bmi'] = {}\n",
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" dict2[k]['bmi']['成绩'] = bmi_data\n",
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" dict2[k]['bmi']['score'] = My.cal_bmi(data1)\n",
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" for item_en in list_item:\n",
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" if item_en in v.keys(): \n",
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" data1 = {'code':k,'sex':sex,'age':v['age'],'item':item_en,'result':float(v[item_en]['成绩'].split()[0])}\n",
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" #print(k,v['name'])\n",
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" dict2[k][item_en]['score'] = My.cal_score(data1)\n",
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" #print(k,v[item_en]['成绩'],cal_score(data1))\n",
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"\n",
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"filename = f'data/result_国图人员.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(dict2,fl , ensure_ascii=False) \n",
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"print('ok!') "
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]
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},
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{
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"cell_type": "markdown",
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"id": "58709fec-703d-49b3-8596-313ba58b897b",
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"metadata": {},
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"source": [
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"## 生成报告"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"id": "480fe004-aea6-4477-9fdd-a80818d731ac",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-04-24T05:31:37.488914Z",
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"iopub.status.busy": "2025-04-24T05:31:37.488126Z",
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"iopub.status.idle": "2025-04-24T05:31:39.680755Z",
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"shell.execute_reply": "2025-04-24T05:31:39.680234Z",
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"shell.execute_reply.started": "2025-04-24T05:31:37.488842Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"4\n"
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]
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}
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],
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"source": [
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"import requests\n",
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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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"headers = {\n",
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" \"Content-Type\": \"application/json; charset=UTF-8\"\n",
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" }\n",
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"filename = 'data/result_国图人员.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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"file_path ='./国图/'\n",
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"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
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"i=0\n",
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"list2 = []\n",
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"for k, v in dict1.items():\n",
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" list1 = []\n",
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" mydata = {}\n",
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" \n",
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" id = str(k).rjust(5,\"0\")\n",
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" mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
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" mydata['title'] = '世诺书院'\n",
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" mydata['subtitle'] = ' '#v['unit']\n",
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" mydata['id'] = id\n",
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" mydata['name'] = v['name']\n",
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" if v['sex'] == '男':\n",
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" mydata['gender'] = 'male'\n",
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" else:\n",
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" mydata['gender'] = 'female' \n",
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" mydata['month'] = v['month']\n",
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" mydata['fits'] = {}\n",
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" survey_list = ['tcm','psy','spine']\n",
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" for item in survey_list:\n",
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" if item in v.keys():\n",
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" mydata.setdefault('surveys',{})\n",
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" mydata['surveys'][item] = v[item]\n",
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" for item in list_item:\n",
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" if item in v.keys():\n",
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" mydata.setdefault('fits',{})\n",
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" if item in ['lung','pushup','step','situp']:\n",
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" mark = v[item]['成绩'].split()[0].split('.')[0]\n",
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" else:\n",
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" mark = v[item]['成绩'].split()[0]\n",
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" mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n",
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" #if len(mydata['fits']) >2 or len(mydata['surveys']) >0:\n",
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" if len(mydata['fits']) >2 or 'surveys' in mydata.keys():\n",
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" #if len(mydata['fits']) >2 : \n",
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" list1.append(mydata)\n",
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" list2.append([k,v['name']])\n",
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" i+=1\n",
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" x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n",
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" #print(id,v['name'],x.text)\n",
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" #x.close()\n",
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"print(i)"
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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": "947cd639-3373-4431-a262-2fb4a9c131af",
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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": "3.12.3"
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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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