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512song committed 2025-06-06 22:40:27 +08:00
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@@ -10,27 +10,12 @@
},
{
"cell_type": "code",
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"execution_count": null,
"id": "bbba6efc-73cd-4db6-bae7-014724fee731",
"metadata": {
"execution": {
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"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
@@ -59,26 +44,10 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "9448933d-527c-410d-ba55-4ce1819a8c1e",
"metadata": {
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
@@ -113,27 +82,12 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "ce406710-6b7d-4c51-98ec-78883bd3ce5f",
"metadata": {
"execution": {
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"\n",
@@ -166,27 +120,12 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "970e171e-1360-448f-a28c-520ccb8f314a",
"metadata": {
"execution": {
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"60\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import datetime\n",
@@ -216,27 +155,12 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "def3f47a-24ef-4815-b63b-2a16b79b4c15",
"metadata": {
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},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok!\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import time\n",
@@ -283,17 +207,9 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"id": "67e63f07-3f20-4e0e-9c07-7bf6024eeb4b",
"metadata": {
"execution": {
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}
},
"metadata": {},
"outputs": [],
"source": [
"import json\n",
@@ -344,10 +260,409 @@
"wb.save(filename)"
]
},
{
"cell_type": "markdown",
"id": "b1c9377b-0da3-481a-9334-b85aa0487374",
"metadata": {},
"source": [
"## 导入问卷信息"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "e454f645-e593-4619-9fce-eabe0fa9f2a9",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-05T06:49:32.523392Z",
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}
},
"outputs": [],
"source": [
"import json\n",
"import csv\n",
"import openpyxl\n",
"import time\n",
"from datetime import date\n",
"#import my_module as My\n",
"\n",
"dict1 = {}\n",
"filename = 'data/result_党建出版社2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"filename = 'data/党建出版社2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict3 = json.load(fl)\n",
"\n",
"phone = {}\n",
"for k,v in dict3.items():\n",
" if 'phone' in v.keys():\n",
" phone[str(v['phone'])] = k\n",
"\n",
"list1 = []\n",
"filename = 'data/survey_records_20250605.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",
" list1.append(line)\n",
"#print(list1)\n",
"dict2 = {}\n",
"psy =[]\n",
"tcm = []\n",
"spine = []\n",
"for i in range(0,57):\n",
" psy.append(0)\n",
"\n",
"for i in range(0,60):\n",
" tcm.append(0)\n",
"for i in range(0,26):\n",
" spine.append(0)\n",
"i= 1\n",
"for item in list1:\n",
" if item[3] in phone.keys():\n",
" psy =[]\n",
" tcm = []\n",
" spine = []\n",
" for i in range(0,57):\n",
" psy.append(0)\n",
" #psy[44] = []\n",
" for i in range(0,60):\n",
" tcm.append(0)\n",
" for i in range(0,26):\n",
" spine.append(0)\n",
" \n",
" content = json.loads(item[4])\n",
" if phone[item[3]] not in dict1.keys():\n",
" dict1[phone[item[3]]] = dict3[phone[item[3]]]\n",
" rq = date.fromisoformat(item[5].replace('/','-').split(' ')[0])\n",
" #dict1[phone[item[2]]]['rq'] = date.fromisoformat(item[6].replace('/','-').split(' ')[0])\n",
" else:\n",
" rq = date.fromisoformat('2025-05-30')\n",
" for k, v in content.items():\n",
" if 'psy' in k:\n",
" i = int(k[3:])\n",
" psy[i-1] = int(v)\n",
" if 'tcm' in k:\n",
" i = int(k[3:])\n",
" tcm[i-1] = int(v)\n",
" if 'spine' in k:\n",
" i = int(k[5:])\n",
" spine[i-1] = int(v)\n",
" if 'psy' in item[4]:\n",
" #for i in range(5,26):\n",
" # new_valve = 5-psy[i]\n",
" # psy[i] = new_valve\n",
" \n",
" \n",
" dict1[phone[item[3]]]['psy57'] = psy\n",
" if 'tcm' in item[4]:\n",
" dict1[phone[item[3]]]['tcm'] = tcm\n",
" if 'spine' in item[4]:\n",
" dict1[phone[item[3]]]['spine'] = spine\n",
" birth = date.fromisoformat(dict3[phone[item[3]]]['birth'].replace('/','-'))\n",
" \n",
" days = (rq-birth).days \n",
" dict1[phone[item[3]]]['age'] = int(days/365)\n",
" dict1[phone[item[3]]]['month'] = int(days/365*12)\n",
" \n",
"\n",
"filename = 'data/result_党建出版社2025-1.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict1, fl, ensure_ascii=False)\n",
"#print(data1[1])"
]
},
{
"cell_type": "markdown",
"id": "41a8ef94-57a1-4697-b99b-cb546adb09e5",
"metadata": {},
"source": [
"## 统计参加问卷人员"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "2ea13ff2-a675-41b2-b104-0f5cd1c9a0b5",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-05T01:06:25.708014Z",
"iopub.status.busy": "2025-06-05T01:06:25.707173Z",
"iopub.status.idle": "2025-06-05T01:06:25.734176Z",
"shell.execute_reply": "2025-06-05T01:06:25.733170Z",
"shell.execute_reply.started": "2025-06-05T01:06:25.707934Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"85\n"
]
}
],
"source": [
"import json\n",
"import csv\n",
"import openpyxl\n",
"import time\n",
"from datetime import date\n",
"\n",
"\n",
"filename = 'data/党建出版社2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"phone1 = set()\n",
"phone2 = set()\n",
"for k,v in dict1.items():\n",
" phone1.add(v['phone'])\n",
"list1 = []\n",
"filename = 'data/survey_records_20250605.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",
" list1.append(line)\n",
"print(len(phone1))\n",
"i =1\n",
"list2 = []\n",
"for item in list1:\n",
" code = int(item[3])\n",
" for k, v in dict1.items():\n",
" list3 = []\n",
" if v['phone'] == code: \n",
" list3.append(k)\n",
" list3.append(v['name'])\n",
" list3.append(v['sex'])\n",
" list3.append(v['unit'])\n",
" list3.append(code)\n",
" list2.append(list3)\n",
"filename = 'data/党建出版社问卷情况表2025.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"#sheet.append(title)\n",
"for row in list2:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename) "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0db73bab-bd7b-4446-ab8e-432f918288b7",
"id": "7c2ef41d-bba9-4776-9a0e-71e14cd7d3fe",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import csv\n",
"import openpyxl\n",
"import time\n",
"from datetime import date\n",
"\n",
"\n",
"filename = 'data/党建出版社2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"phone1 = set()\n",
"phone2 = set()\n",
"for k,v in dict1.items():\n",
" phone1.add(v['phone'])\n",
"list1 = []\n",
"filename = 'data/survey_records_20250605.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",
" list1.append(line)\n",
"print(len(phone1))\n",
"i =1\n",
"list2 = []\n",
"for item in list1:\n",
" code = int(item[3])\n",
" if code not in phone1:\n",
" print(code)"
]
},
{
"cell_type": "markdown",
"id": "ffb387e1-41b5-4a4d-a9ca-89e1c5650880",
"metadata": {},
"source": [
"## 生成报告"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "462bc4e8-1659-43a0-9cbf-a87a4dfc5376",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-05T06:50:13.169871Z",
"iopub.status.busy": "2025-06-05T06:50:13.168552Z",
"iopub.status.idle": "2025-06-05T06:50:51.648786Z",
"shell.execute_reply": "2025-06-05T06:50:51.647689Z",
"shell.execute_reply.started": "2025-06-05T06:50:13.169789Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"65\n"
]
}
],
"source": [
"import requests\n",
"import json\n",
"import openpyxl\n",
"\n",
"\n",
"headers = {\n",
" \"Content-Type\": \"application/json; charset=UTF-8\"\n",
" }\n",
"filename = 'data/result_党建出版社2025-1.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"file_path ='./党建出版社2025/'\n",
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
"i=0\n",
"list2 = []\n",
"for k, v in dict1.items():\n",
" list1 = []\n",
" mydata = {}\n",
" \n",
" id = str(k).rjust(4,\"0\")\n",
" mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
" mydata['title'] = '党建读物出版社'\n",
" mydata['subtitle'] = ' '\n",
" mydata['id'] = id\n",
" mydata['name'] = v['name']\n",
" if v['sex'] == '男':\n",
" mydata['gender'] = 'male'\n",
" else:\n",
" mydata['gender'] = 'female'\n",
" \n",
" mydata['month'] = v['month']\n",
" mydata['fits'] = {}\n",
" survey_list = ['tcm','psy57','spine']\n",
" for item in survey_list:\n",
" if item in v.keys():\n",
" mydata.setdefault('surveys',{})\n",
" mydata['surveys'][item] = v[item]\n",
" \n",
" \n",
" #mydata['fits'] = {}\n",
" for item in list_item:\n",
" if item in v.keys():\n",
" mydata.setdefault('fits',{})\n",
" if item in ['lung','pushup','step','situp']:\n",
" mark = v[item]['成绩'].split()[0].split('.')[0]\n",
" else:\n",
" mark = v[item]['成绩'].split()[0]\n",
" mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n",
" if len(mydata['fits']) >2 or len(mydata['surveys']) >0:\n",
" #if len(mydata['fits']) >2 : \n",
" list1.append(mydata)\n",
" list2.append([k,v['name']])\n",
" i+=1\n",
" x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n",
" #print(id,v['name'],x.text)\n",
" #print(mydata)\n",
" #x.close()\n",
"print(i)"
]
},
{
"cell_type": "markdown",
"id": "f28bb6dd-c8de-4761-a8a1-83b65a504a7d",
"metadata": {},
"source": [
"## 计算中医体质"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "0f393c7d-26b2-4bb2-8f18-702f5ee52abf",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-05T06:59:54.308502Z",
"iopub.status.busy": "2025-06-05T06:59:54.307891Z",
"iopub.status.idle": "2025-06-05T06:59:54.340029Z",
"shell.execute_reply": "2025-06-05T06:59:54.339248Z",
"shell.execute_reply.started": "2025-06-05T06:59:54.308441Z"
}
},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'tcm_calc' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[24], line 15\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m item \u001b[38;5;129;01min\u001b[39;00m tcm:\n\u001b[1;32m 14\u001b[0m list1\u001b[38;5;241m.\u001b[39mappend(item)\n\u001b[0;32m---> 15\u001b[0m score \u001b[38;5;241m=\u001b[39m \u001b[43mtcm_calc\u001b[49m(list1)\n\u001b[1;32m 17\u001b[0m result \u001b[38;5;241m=\u001b[39m tcm_kind(score)\n\u001b[1;32m 18\u001b[0m kind \u001b[38;5;241m=\u001b[39m result[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mkind\u001b[39m\u001b[38;5;124m'\u001b[39m]\n",
"\u001b[0;31mNameError\u001b[0m: name 'tcm_calc' is not defined"
]
}
],
"source": [
"import openpyxl\n",
"import my_module as My\n",
"\n",
"filename = 'data/result_党建出版社2025-1.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"i = 1\n",
"list2 = []\n",
"for k, v in dict1.items():\n",
" if 'tcm' in v.keys():\n",
" list1 = []\n",
" tcm =v['tcm']\n",
" for item in tcm:\n",
" list1.append(item)\n",
" score = tcm_calc(list1)\n",
"\n",
" result = tcm_kind(score)\n",
" kind = result['kind']\n",
" near = result['near']\n",
" #print(i,k,kinds[kind], near, score)\n",
" #i+=1\n",
" list3 = []\n",
" list3.append(k)\n",
" list3.append(kinds[kind])\n",
" list3.append(near)\n",
" for item in score:\n",
" list3.append(item)\n",
" list2.append(list3)\n",
"print(list2)\n",
"filename = 'data/党建出版社中医情况明细表2025.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"\n",
"for row in list2:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename)\n",
"print('ok') "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "02057c2d-f2e5-4c09-8c2d-508bedb95817",
"metadata": {},
"outputs": [],
"source": []