20251021
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@@ -10,15 +10,15 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 8,
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"id": "d6449ec6-54af-4f68-8c32-69372e390acf",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-09-22T03:30:37.564857Z",
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"iopub.status.busy": "2025-09-22T03:30:37.564250Z",
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"iopub.status.idle": "2025-09-22T03:30:37.781384Z",
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"shell.execute_reply": "2025-09-22T03:30:37.780531Z",
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"shell.execute_reply.started": "2025-09-22T03:30:37.564798Z"
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"iopub.execute_input": "2025-09-22T12:07:43.029162Z",
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"shell.execute_reply.started": "2025-09-22T12:07:43.029136Z"
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}
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},
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"outputs": [
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@@ -45,7 +45,7 @@
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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, 5).value\n",
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" dict1['sex'] = sheet.cell(n, 6).value\n",
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" dict1['unit'] = 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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" dict1['phone'] = sheet.cell(n, 5).value \n",
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@@ -66,15 +66,15 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 15,
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"id": "c24c957e-6cc5-4cab-81e2-cec86a7498c7",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-09-22T03:48:21.444109Z",
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"iopub.status.busy": "2025-09-22T03:48:21.443422Z",
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"iopub.status.idle": "2025-09-22T03:48:21.472961Z",
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"shell.execute_reply": "2025-09-22T03:48:21.472454Z",
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"shell.execute_reply.started": "2025-09-22T03:48:21.444045Z"
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"iopub.execute_input": "2025-09-22T12:49:46.218013Z",
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"iopub.status.busy": "2025-09-22T12:49:46.217356Z",
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"iopub.status.idle": "2025-09-22T12:49:46.243578Z",
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"shell.execute_reply": "2025-09-22T12:49:46.242996Z",
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"shell.execute_reply.started": "2025-09-22T12:49:46.217955Z"
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}
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},
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"outputs": [
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@@ -82,7 +82,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"33\n"
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"31\n"
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]
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}
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],
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@@ -144,11 +144,61 @@
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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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"execution_count": 16,
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"id": "a64ad6b7-b1dd-42ca-9619-3adcb8e0674e",
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"metadata": {},
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"outputs": [],
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"source": []
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-09-22T12:49:52.460408Z",
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"iopub.status.busy": "2025-09-22T12:49:52.459655Z",
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"iopub.status.idle": "2025-09-22T12:49:52.470790Z",
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"shell.execute_reply": "2025-09-22T12:49:52.469571Z",
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"shell.execute_reply.started": "2025-09-22T12:49:52.460338Z"
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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_通用技术中国医药.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(str(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_通用技术中国医药.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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@@ -160,15 +210,15 @@
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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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"execution_count": 17,
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"id": "020be101-938b-427e-918d-faf2e74b5b7e",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-09-22T03:57:31.502714Z",
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"iopub.status.busy": "2025-09-22T03:57:31.501987Z",
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"iopub.status.idle": "2025-09-22T03:57:31.516781Z",
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"shell.execute_reply": "2025-09-22T03:57:31.515780Z",
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"shell.execute_reply.started": "2025-09-22T03:57:31.502649Z"
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"iopub.execute_input": "2025-09-22T12:49:55.871938Z",
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"iopub.status.busy": "2025-09-22T12:49:55.871204Z",
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"iopub.status.idle": "2025-09-22T12:49:55.886755Z",
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"shell.execute_reply": "2025-09-22T12:49:55.885950Z",
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"shell.execute_reply.started": "2025-09-22T12:49:55.871866Z"
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}
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},
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"outputs": [],
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@@ -244,10 +294,103 @@
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" json.dump(dict1, fl, ensure_ascii=False)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "7ec62459-2938-4c0c-b35a-f4341630f1c6",
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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": 19,
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"id": "17dd5667-d970-46d2-b241-27338dbba4bb",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-09-22T12:51:00.278870Z",
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"iopub.status.busy": "2025-09-22T12:51:00.278200Z",
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"iopub.status.idle": "2025-09-22T12:51:14.234951Z",
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"shell.execute_reply": "2025-09-22T12:51:14.233971Z",
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"shell.execute_reply.started": "2025-09-22T12:51:00.278810Z"
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},
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"scrolled": true
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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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"31\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_通用技术中国医药-1.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 ='./中国医药/'\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(4,\"0\")\n",
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" mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
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" mydata['title'] = '中国医药'\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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" \n",
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" mydata['month'] = v['month']\n",
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" mydata['fits'] = {}\n",
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" survey_list = ['tcm','psy57','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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" \n",
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" \n",
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" #mydata['fits'] = {}\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 = str(v[item]['成绩']).split()[0].split('.')[0]\n",
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" else:\n",
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" mark = str(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 : \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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" #print(mydata)\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": "9560d0ca-4d39-400b-b054-214e243ca4e5",
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"id": "4297b542-206e-4f0e-9339-ba88e712443e",
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"metadata": {},
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"outputs": [],
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"source": []
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