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512song committed 2025-11-17 22:46:37 +08:00
1 parent 48f119d087
commit 31ddcb887f
9 files changed
+1089 -276
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体测单位/my_module.py
+1 -1
View File
@@ -138,7 +138,7 @@ def get_result(filename,dict1):
list1.append(line)
for result in list1:
user = str(int(result[2]))
user = str(int(result[2])).strip()
rq = date.fromisoformat(result[5].replace('/','-'))
if user in dict1.keys():
l_xm = []
体测单位/体质检测数据处理.ipynb
+29 -45
View File
@@ -690,11 +690,11 @@
"headers = {\n",
" \"Content-Type\": \"application/json; charset=UTF-8\"\n",
" }\n",
"filename = 'data/result_镇海2025-1.json'\n",
"filename = 'data/result_北海2025-1.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"file_path ='./镇海石化2025/'\n",
"file_path ='./北海炼化2025-1/'\n",
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
"i=0\n",
"list2 = []\n",
@@ -703,9 +703,9 @@
" mydata = {}\n",
" \n",
" #id = str(k).rjust(8,\"0\")\n",
" id = str(k)\n",
" id = str(k).rjust(4,\"0\")\n",
" mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
" mydata['title'] = '中国石化镇海炼化公司'\n",
" mydata['title'] = '中国石化北海炼化有限责任公司'\n",
" mydata['subtitle'] = v['unit']\n",
" mydata['id'] = id\n",
" mydata['name'] = v['name']\n",
@@ -732,8 +732,8 @@
" 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",
" 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",
@@ -915,19 +915,19 @@
"import glob\n",
"from pathlib import Path\n",
"\n",
"fi_path = '/home/songyi/pdf-typescript-old2/镇海石化2025'\n",
"new_path = 'file/镇海石化2025'\n",
"fi_path = '/home/songyi/pdf-typescript-old2/北海炼化2025'\n",
"new_path = 'file/北海炼化2025'\n",
"old = []\n",
"dict2 = {}\n",
"\n",
"filename = 'data/result_镇海2025-1.json'\n",
"filename = 'data/result_北海2025-1.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
"print(len(fls))\n",
"for fn in fls:\n",
" fi_name =Path(fn).stem.split('-')[0]\n",
" code = fi_name \n",
" code = str(int(fi_name)) \n",
" unit_path = Path(new_path,dict1[str(code)]['unit'])\n",
" unit_path.mkdir(parents = True, exist_ok = True)\n",
" n_name = Path(unit_path,Path(fn).stem+'.pdf')\n",
@@ -946,15 +946,15 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 18,
"id": "02319955-7fb6-4791-ae45-55b03bdadd54",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-07T06:31:33.947472Z",
"iopub.status.busy": "2025-11-07T06:31:33.946853Z",
"iopub.status.idle": "2025-11-07T06:31:34.095980Z",
"shell.execute_reply": "2025-11-07T06:31:34.095388Z",
"shell.execute_reply.started": "2025-11-07T06:31:33.947411Z"
"iopub.execute_input": "2025-11-17T14:25:08.413467Z",
"iopub.status.busy": "2025-11-17T14:25:08.412602Z",
"iopub.status.idle": "2025-11-17T14:25:08.498336Z",
"shell.execute_reply": "2025-11-17T14:25:08.497785Z",
"shell.execute_reply.started": "2025-11-17T14:25:08.413400Z"
},
"tags": []
},
@@ -974,9 +974,9 @@
"from pathlib import Path\n",
"import openpyxl\n",
"\n",
"fi_path = '/home/songyi/pdf-typescript-old2/镇海石化2025'\n",
"fi_path = '/home/songyi/pdf-typescript-old2/北海炼化2025'\n",
"\n",
"filename = 'data/result_镇海2025-1.json'\n",
"filename = 'data/result_北海2025-1.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
@@ -985,14 +985,14 @@
"for fn in fls:\n",
" list2 = []\n",
" fi_name =Path(fn).stem.split('-')[0] \n",
" code = fi_name\n",
" code = str(int(fi_name))\n",
" sex = dict1[str(code)]['sex']\n",
" unit = dict1[str(code)]['unit']\n",
" list2 = [fi_name,Path(fn).stem.split('-')[1],sex,unit]\n",
" \n",
" list1.append(list2)\n",
"\n",
"filename = 'data/2025年镇海石化体测报告明细表.xlsx'\n",
"filename = 'data/2025年北海炼化体测报告明细表.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
@@ -1656,7 +1656,7 @@
"import openpyxl\n",
"\n",
"\n",
"filename = 'data/result_胜利采油厂1.json'\n",
"filename = 'data/result_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
@@ -1709,7 +1709,7 @@
" mydata['score'] = round(score/len(mydata['fits']),2)\n",
" if len(mydata['fits']) >2:\n",
" dict2[str(k)] = mydata\n",
"filename = f'data/data_胜利采油厂.json'\n",
"filename = f'data/data_镇海2025.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2,fl , ensure_ascii=False) \n",
"print(len(dict2)) "
@@ -1735,7 +1735,7 @@
"import json\n",
"\n",
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
"filename = 'data/data_胜利采油厂.json'\n",
"filename = 'data/data_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"i = 1\n",
@@ -2108,7 +2108,7 @@
" score = 0\n",
" n = 0\n",
" for k, v in dict1.items():\n",
" if item == v['unit'] and v['sex'] == '男':\n",
" if item == v['unit'] and v['sex'] == '女':\n",
" score = score + v['score']\n",
" n = n +1 \n",
" if n>0:\n",
@@ -2175,7 +2175,7 @@
"import json\n",
"\n",
"items = ['BMI','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/data_宁夏能化人员.json'\n",
"filename = 'data/data_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
@@ -2222,17 +2222,9 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": null,
"id": "6f9768ce-2ef5-4253-9fc6-49dbdcf00a19",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T05:36:30.068876Z",
"iopub.status.busy": "2025-11-14T05:36:30.068084Z",
"iopub.status.idle": "2025-11-14T05:36:30.079053Z",
"shell.execute_reply": "2025-11-14T05:36:30.078052Z",
"shell.execute_reply.started": "2025-11-14T05:36:30.068800Z"
}
},
"metadata": {},
"outputs": [],
"source": [
"import json\n",
@@ -2584,17 +2576,9 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": null,
"id": "9ecd3ad8-c8af-4f3e-90e5-1618fea905a4",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T05:36:39.675837Z",
"iopub.status.busy": "2025-11-14T05:36:39.675165Z",
"iopub.status.idle": "2025-11-14T05:36:39.706916Z",
"shell.execute_reply": "2025-11-14T05:36:39.706427Z",
"shell.execute_reply.started": "2025-11-14T05:36:39.675772Z"
}
},
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
体测单位/北海炼化.ipynb
+301 -43
View File
@@ -2165,9 +2165,7 @@
{
"cell_type": "markdown",
"id": "76c5c17a-462d-4a7b-95a5-6b895f5a25dc",
"metadata": {
"jp-MarkdownHeadingCollapsed": true
},
"metadata": {},
"source": [
"# 2024年体质检测"
]
@@ -3042,10 +3040,26 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 13,
"id": "58f6dbab-9ea2-4295-ae78-36951b67c2d3",
"metadata": {},
"outputs": [],
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-17T07:32:41.466054Z",
"iopub.status.busy": "2025-11-17T07:32:41.465351Z",
"iopub.status.idle": "2025-11-17T07:32:41.591984Z",
"shell.execute_reply": "2025-11-17T07:32:41.591337Z",
"shell.execute_reply.started": "2025-11-17T07:32:41.465990Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"880 ok\n"
]
}
],
"source": [
"import openpyxl\n",
"import json\n",
@@ -3186,15 +3200,15 @@
},
{
"cell_type": "code",
"execution_count": 57,
"execution_count": 14,
"id": "7b79c7bb-ce87-44b2-95b1-01e9cb66d5f0",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-13T05:44:27.934101Z",
"iopub.status.busy": "2025-11-13T05:44:27.933541Z",
"iopub.status.idle": "2025-11-13T05:44:27.991293Z",
"shell.execute_reply": "2025-11-13T05:44:27.990805Z",
"shell.execute_reply.started": "2025-11-13T05:44:27.934053Z"
"iopub.execute_input": "2025-11-17T07:32:53.282654Z",
"iopub.status.busy": "2025-11-17T07:32:53.281905Z",
"iopub.status.idle": "2025-11-17T07:32:53.332471Z",
"shell.execute_reply": "2025-11-17T07:32:53.331897Z",
"shell.execute_reply.started": "2025-11-17T07:32:53.282586Z"
}
},
"outputs": [
@@ -3236,15 +3250,15 @@
},
{
"cell_type": "code",
"execution_count": 60,
"execution_count": 15,
"id": "458725a6-3b5b-48a1-af90-cd4d0bda3635",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-13T05:51:01.753768Z",
"iopub.status.busy": "2025-11-13T05:51:01.752925Z",
"iopub.status.idle": "2025-11-13T05:51:01.812931Z",
"shell.execute_reply": "2025-11-13T05:51:01.812381Z",
"shell.execute_reply.started": "2025-11-13T05:51:01.753692Z"
"iopub.execute_input": "2025-11-17T07:33:02.993633Z",
"iopub.status.busy": "2025-11-17T07:33:02.993053Z",
"iopub.status.idle": "2025-11-17T07:33:03.110653Z",
"shell.execute_reply": "2025-11-17T07:33:03.109552Z",
"shell.execute_reply.started": "2025-11-17T07:33:02.993579Z"
}
},
"outputs": [
@@ -3278,6 +3292,72 @@
"print('ok')"
]
},
{
"cell_type": "markdown",
"id": "aff5b1b6-a6af-44dd-beb0-cb2b68999496",
"metadata": {},
"source": [
"## 生成测试得分"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "ef655e34-635b-4baa-97c3-925022f45949",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-17T10:47:57.459196Z",
"iopub.status.busy": "2025-11-17T10:47:57.458528Z",
"iopub.status.idle": "2025-11-17T10:47:57.506947Z",
"shell.execute_reply": "2025-11-17T10:47:57.506509Z",
"shell.execute_reply.started": "2025-11-17T10:47:57.459138Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok!\n"
]
}
],
"source": [
"import json\n",
"import time\n",
"import my_module as My\n",
"\n",
"#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n",
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n",
"filename = 'data/result_北海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl) \n",
"for k, v in dict2.items():\n",
" #print(k)\n",
" if v['sex'] == '男':\n",
" sex = 'M'\n",
" else:\n",
" sex = 'F' \n",
" if 'bmi' in v.keys():\n",
" #bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n",
" bmi_data = v['bmi']['成绩']\n",
" data1 = {'code':k,'sex':sex,'age':v['age'],'item':'HeightWeight','result':bmi_data}\n",
" dict2[k]['bmi'] = {}\n",
" dict2[k]['bmi']['成绩'] = bmi_data\n",
" dict2[k]['bmi']['score'] = My.cal_bmi(data1)\n",
" for item_en in list_item:\n",
" if item_en in v.keys(): \n",
" data1 = {'code':k,'sex':sex,'age':v['age'],'item':item_en,'result':float(v[item_en]['成绩'].split()[0])}\n",
" #print(k,v['name'])\n",
" dict2[k][item_en]['score'] = My.cal_score(data1)\n",
" #print(k,v[item_en]['成绩'],cal_score(data1))\n",
"\n",
"filename = f'data/result_北海2025.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2,fl , ensure_ascii=False) \n",
"print('ok!') "
]
},
{
"cell_type": "markdown",
"id": "12b33ee8-2b4e-4b85-9301-4fbcadf4129c",
@@ -3407,15 +3487,15 @@
},
{
"cell_type": "code",
"execution_count": 65,
"execution_count": 16,
"id": "0bbf2cb6-e7d9-4d0d-beba-77ac50082f05",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-13T06:17:23.628451Z",
"iopub.status.busy": "2025-11-13T06:17:23.627881Z",
"iopub.status.idle": "2025-11-13T06:17:23.729071Z",
"shell.execute_reply": "2025-11-13T06:17:23.728586Z",
"shell.execute_reply.started": "2025-11-13T06:17:23.628397Z"
"iopub.execute_input": "2025-11-17T07:33:16.521656Z",
"iopub.status.busy": "2025-11-17T07:33:16.520913Z",
"iopub.status.idle": "2025-11-17T07:33:16.617830Z",
"shell.execute_reply": "2025-11-17T07:33:16.617274Z",
"shell.execute_reply.started": "2025-11-17T07:33:16.521587Z"
}
},
"outputs": [],
@@ -3427,7 +3507,7 @@
"from datetime import date\n",
"\n",
"list1 = []\n",
"filename = 'data/sql_20251113.csv'\n",
"filename = 'data/sql_20251117.csv'\n",
"with open(filename,'r',newline='') as csv_file:\n",
" fl = csv.reader(csv_file,delimiter=',')\n",
" header = next(fl) \n",
@@ -3452,7 +3532,72 @@
" list2 = [code,dict3[code]['name'],dict3[code]['unit'],phone_num]\n",
" list3.append(list2)\n",
"title =['测试编号','姓名','部门','手机号码']\n",
"filename = 'data/北海炼化问卷人员（截至20251113）.xlsx'\n",
"filename = 'data/北海炼化问卷人员（截至20251116）.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": "60d7de83-75aa-44bf-99da-492627032ca1",
"metadata": {},
"source": [
"## 问卷不符合信息人员"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "d3c0061f-fc24-483e-8e93-08872c77547f",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-17T01:29:17.936230Z",
"iopub.status.busy": "2025-11-17T01:29:17.935493Z",
"iopub.status.idle": "2025-11-17T01:29:17.974203Z",
"shell.execute_reply": "2025-11-17T01:29:17.973659Z",
"shell.execute_reply.started": "2025-11-17T01:29:17.936162Z"
}
},
"outputs": [],
"source": [
"import json\n",
"import csv\n",
"import openpyxl\n",
"import time\n",
"from datetime import date\n",
"\n",
"list1 = []\n",
"filename = 'data/sql_20251117.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",
"filename = 'data/北海炼化人员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",
"dict2 = {}\n",
"list3 = []\n",
"for item in list1: \n",
" phone_num = str(item[0])[2:] \n",
" if phone_num not in phone:\n",
" list2 = []\n",
" content = json.loads(json.loads(item[1])) \n",
" code = phone_num\n",
" list2 = [code,content['name'],content['birth'],content['gender']]\n",
" list3.append(list2)\n",
"title =['测试编号','姓名','部门','手机号码']\n",
"filename = 'data/北海炼化问卷信息不符合人员（截至20251116）.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
@@ -3464,15 +3609,15 @@
},
{
"cell_type": "code",
"execution_count": 43,
"execution_count": 8,
"id": "277fce35-2f95-4d52-8cab-4e27c9acd7b8",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-10T09:40:12.759033Z",
"iopub.status.busy": "2025-11-10T09:40:12.758367Z",
"iopub.status.idle": "2025-11-10T09:40:12.843476Z",
"shell.execute_reply": "2025-11-10T09:40:12.842924Z",
"shell.execute_reply.started": "2025-11-10T09:40:12.758969Z"
"iopub.execute_input": "2025-11-17T01:22:21.248136Z",
"iopub.status.busy": "2025-11-17T01:22:21.247270Z",
"iopub.status.idle": "2025-11-17T01:22:21.339031Z",
"shell.execute_reply": "2025-11-17T01:22:21.338544Z",
"shell.execute_reply.started": "2025-11-17T01:22:21.248063Z"
}
},
"outputs": [],
@@ -3487,7 +3632,7 @@
"dict1 = {}\n",
"list1 = []\n",
"list2 = set()\n",
"filename = 'data/sql_20251110.csv'\n",
"filename = 'data/sql_20251117.csv'\n",
"with open(filename,'r',newline='') as csv_file:\n",
" fl = csv.reader(csv_file,delimiter=',')\n",
" header = next(fl) \n",
@@ -3530,7 +3675,7 @@
" list4 = [phone,v['name'],v['unit']]\n",
" list3.append(list4)\n",
"title =['手机号码','姓名','部门']\n",
"filename = 'data/北海炼化未参加问卷人员（截至20251110）.xlsx'\n",
"filename = 'data/北海炼化未参加问卷人员（截至20251116）.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
@@ -3552,15 +3697,15 @@
},
{
"cell_type": "code",
"execution_count": 62,
"execution_count": 6,
"id": "f67f63d1-be8a-47ef-b95f-bdfca9725838",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-13T06:00:49.916395Z",
"iopub.status.busy": "2025-11-13T06:00:49.915561Z",
"iopub.status.idle": "2025-11-13T06:00:50.043798Z",
"shell.execute_reply": "2025-11-13T06:00:50.043247Z",
"shell.execute_reply.started": "2025-11-13T06:00:49.916323Z"
"iopub.execute_input": "2025-11-17T01:19:30.426467Z",
"iopub.status.busy": "2025-11-17T01:19:30.425891Z",
"iopub.status.idle": "2025-11-17T01:19:30.551084Z",
"shell.execute_reply": "2025-11-17T01:19:30.550545Z",
"shell.execute_reply.started": "2025-11-17T01:19:30.426412Z"
}
},
"outputs": [],
@@ -3574,7 +3719,7 @@
"\n",
"dict1 = {}\n",
"list1 = []\n",
"filename = 'data/sql_20251110.csv'\n",
"filename = 'data/sql_20251117.csv'\n",
"with open(filename,'r',newline='') as csv_file:\n",
" fl = csv.reader(csv_file,delimiter=',')\n",
" header = next(fl) \n",
@@ -3615,7 +3760,7 @@
" list2 = [k,v['name'],v['sex'],v['birth']]\n",
" list1.append(list2)\n",
"title =['手机号码','姓名','性别','出生年月']\n",
"filename = 'data/北海炼化问卷人员（截至20251110）.xlsx'\n",
"filename = 'data/北海炼化问卷人员（截至20251116）.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
@@ -3702,10 +3847,123 @@
"wb.save(filename)"
]
},
{
"cell_type": "markdown",
"id": "fc7701c1-0ce3-4fb9-a8eb-c9f8f2d44337",
"metadata": {},
"source": [
"## 导入问卷信息"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "4628f644-a571-4f2b-8d7b-e6b60b2ddcfd",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-17T12:25:33.111224Z",
"iopub.status.busy": "2025-11-17T12:25:33.110488Z",
"iopub.status.idle": "2025-11-17T12:25:33.267732Z",
"shell.execute_reply": "2025-11-17T12:25:33.267196Z",
"shell.execute_reply.started": "2025-11-17T12:25:33.111154Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"781\n"
]
}
],
"source": [
"import json\n",
"import csv\n",
"import openpyxl\n",
"import time\n",
"from datetime import date\n",
"\n",
"list1 = []\n",
"filename = 'data/sql_20251117.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",
"filename = 'data/北海炼化人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict3 = json.load(fl)\n",
"filename = 'data/result_北海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"phone = {}\n",
"for k,v in dict3.items():\n",
" if 'phone' in v.keys():\n",
" phone[str(v['phone'])] = k\n",
"\n",
"\n",
"\n",
"nn = 0\n",
"for item in list1:\n",
" dict2 = {}\n",
" \n",
" phone_num = str(item[0])[2:]\n",
" if phone_num in phone:\n",
" content = json.loads(json.loads(item[1]))\n",
" tcm = []\n",
" spine = []\n",
" psy = []\n",
" for i in range(0,45):\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",
" 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",
" if i<23:\n",
" spine[i-1] = int(v)\n",
" else:\n",
" spine[i] = int(v)\n",
" for i in range(26,40):\n",
" new_valve = 1+psy[i]\n",
" psy[i] = new_valve \n",
" code = phone[phone_num]\n",
" if code in dict3.keys() and code in dict1.keys(): \n",
" dict1[code]['tcm'] = tcm \n",
" dict1[code]['spine'] = spine\n",
" dict1[code]['psy'] = psy\n",
" elif code not in dict1.keys(): \n",
" dict1.setdefault(code,{})\n",
" dict1[code] = dict3[code]\n",
" birth = date.fromisoformat(dict3[code]['birth'])\n",
" rq = date.fromisoformat('2025-11-17')\n",
" days = (rq-birth).days \n",
" dict1[code]['age'] = int(days/365)\n",
" dict1[code]['month'] = int(days/365*12)\n",
" dict1[code]['rq'] = '2025-11-17'\n",
" dict1[code]['tcm'] = tcm \n",
" dict1[code]['spine'] = spine\n",
" dict1[code]['psy'] = psy\n",
"filename = 'data/result_北海2025-1.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict1, fl, ensure_ascii=False)\n",
"print(len(dict1))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4b58eeae-089d-4007-ab5a-1e1e9e088dd7",
"id": "013474d1-e2e0-4562-bd72-80ec9425f0c9",
"metadata": {},
"outputs": [],
"source": []
体测单位/天津石化.ipynb
+102
View File
@@ -3513,6 +3513,108 @@
"print(len(list1),'ok')"
]
},
{
"cell_type": "markdown",
"id": "fd5cb794-6197-4204-a421-fd7a14aeab20",
"metadata": {},
"source": [
"## 获取人员测试成绩"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "52de3ba0-f430-444b-87e9-1f13c3e2dcc2",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-17T13:15:52.024202Z",
"iopub.status.busy": "2025-11-17T13:15:52.023733Z",
"iopub.status.idle": "2025-11-17T13:15:52.062303Z",
"shell.execute_reply": "2025-11-17T13:15:52.061818Z",
"shell.execute_reply.started": "2025-11-17T13:15:52.024158Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"253\n"
]
}
],
"source": [
"import json\n",
"import datetime\n",
"import csv\n",
"from datetime import date\n",
"import my_module1 as My\n",
"\n",
"filename = 'data/天津石化人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"filename = 'data/marks_20251117-2.csv'\n",
"re_ta = My.get_result(filename,dict1)\n",
"\n",
"\n",
"filename = 'data/result_天津石化2025.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": "f58f041b-a3cb-475c-8ac2-a8a747c96386",
"metadata": {},
"source": [
"## 统计未体测人员明细表"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "04990b9f-a8f9-4442-935e-d223fde24e72",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-17T13:21:58.571623Z",
"iopub.status.busy": "2025-11-17T13:21:58.570712Z",
"iopub.status.idle": "2025-11-17T13:21:58.620055Z",
"shell.execute_reply": "2025-11-17T13:21:58.619536Z",
"shell.execute_reply.started": "2025-11-17T13:21:58.571556Z"
}
},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"filename = 'data/result_天津石化2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/天津石化人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
"\n",
"list1 = []\n",
"\n",
"i = 1\n",
"for k, v in dict1.items(): \n",
" list2 = [i,k,v['name'],v['unit']]\n",
" i+=1\n",
" list1.append(list2)\n",
"#print(list1)\n",
"filename = f'data/天津石化体测人员名单（截至20251117）.xlsx'\n",
"title = ['序号','员工编号','姓名','部门']\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
"for row in list1:\n",
" sheet.append(row) \n",
"wb.save(filename)"
]
},
{
"cell_type": "markdown",
"id": "85a03b00-9624-4ae9-aa6d-386798d457df",
体测单位/宁夏能化.ipynb
+381 -74
View File
@@ -975,26 +975,10 @@
},
{
"cell_type": "code",
"execution_count": 30,
"execution_count": null,
"id": "396e64b8-c306-4613-9848-f0f183052b78",
"metadata": {
"execution": {
"iopub.execute_input": "2025-10-10T02:18:51.157197Z",
"iopub.status.busy": "2025-10-10T02:18:51.156880Z",
"iopub.status.idle": "2025-10-10T02:18:51.211412Z",
"shell.execute_reply": "2025-10-10T02:18:51.210755Z",
"shell.execute_reply.started": "2025-10-10T02:18:51.157161Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"210 ok\n"
]
}
],
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import csv\n",
@@ -1033,26 +1017,10 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": null,
"id": "f60e8194-7ef6-49d8-8538-9b79f35bb64d",
"metadata": {
"execution": {
"iopub.execute_input": "2025-10-10T02:09:50.365387Z",
"iopub.status.busy": "2025-10-10T02:09:50.364816Z",
"iopub.status.idle": "2025-10-10T02:09:50.391653Z",
"shell.execute_reply": "2025-10-10T02:09:50.391205Z",
"shell.execute_reply.started": "2025-10-10T02:09:50.365335Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"145 ok\n"
]
}
],
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import csv\n",
@@ -1117,17 +1085,9 @@
},
{
"cell_type": "code",
"execution_count": 28,
"execution_count": null,
"id": "f0853629-e971-492b-88c8-4e9521b4b017",
"metadata": {
"execution": {
"iopub.execute_input": "2025-10-10T02:16:14.316496Z",
"iopub.status.busy": "2025-10-10T02:16:14.315869Z",
"iopub.status.idle": "2025-10-10T02:16:14.344471Z",
"shell.execute_reply": "2025-10-10T02:16:14.343924Z",
"shell.execute_reply.started": "2025-10-10T02:16:14.316435Z"
}
},
"metadata": {},
"outputs": [],
"source": [
"import json\n",
@@ -1161,17 +1121,324 @@
"wb.save(filename)"
]
},
{
"cell_type": "markdown",
"id": "98de56de-95fe-4f21-be25-896fb1bda175",
"metadata": {},
"source": [
"## 问卷转换"
]
},
{
"cell_type": "code",
"execution_count": 29,
"execution_count": null,
"id": "22be8f39-afbb-448a-8ae6-c825c7d38757",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"\n",
"title = []\n",
"\n",
"filename = 'data/surveys_records_宁夏能化.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"title = ['id', 'date_created']\n",
"data_title = ['name', 'gender', 'birth', 'code', 'unit', 'height', 'weight', 'next_weight', 'waist', 'hip', 'level4', 'level3', 'level2', 'recipe', 'level1', 'last_level4', 'last_level3', 'last_level2', 'last_level1', 'last_recipe', 'last_lose', 'last_sport', 'sport_type', 'sport_duration', 'last_sport_time', 'last_lose-Comment', 'last_recipe-Comment', 'last_lose_weight', 'last_sport-Comment', 'sport_type-Comment']\n",
"for item in dict1:\n",
" list2 = []\n",
" for xm in title:\n",
" if xm in item.keys():\n",
" list2.append(item[xm])\n",
" else:\n",
" list2.append('')\n",
" for xm in data_title:\n",
" if xm in item['data'].keys():\n",
" if xm =='sport_type':\n",
" list2.append(','.join(item['data'][xm]))\n",
" else:\n",
" list2.append(item['data'][xm])\n",
" else:\n",
" list2.append('')\n",
" \n",
" list1.append(list2)\n",
"all_title = ['id', 'date_created','name', 'gender', 'birth', 'code', 'unit', 'height', 'weight', 'next_weight', 'waist', 'hip', 'level4', 'level3', 'level2', 'recipe', 'level1', 'last_level4', 'last_level3', 'last_level2', 'last_level1', 'last_recipe', 'last_lose', 'last_sport', 'sport_type', 'sport_duration', 'last_sport_time', 'last_lose-Comment', 'last_recipe-Comment', 'last_lose_weight', 'last_sport-Comment', 'sport_type-Comment']\n",
"filename = 'data/宁夏能化干预人员问卷（20251114）.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(all_title)\n",
"for row in list1:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename) "
]
},
{
"cell_type": "markdown",
"id": "ad2f24f2-f43c-4181-a5e4-16876b0d7443",
"metadata": {
"execution": {
"iopub.execute_input": "2025-10-10T02:18:10.620552Z",
"iopub.status.busy": "2025-10-10T02:18:10.619865Z",
"iopub.status.idle": "2025-10-10T02:18:10.652211Z",
"shell.execute_reply": "2025-10-10T02:18:10.651710Z",
"shell.execute_reply.started": "2025-10-10T02:18:10.620490Z"
"iopub.execute_input": "2025-11-14T09:41:32.283676Z",
"iopub.status.busy": "2025-11-14T09:41:32.283096Z",
"iopub.status.idle": "2025-11-14T09:41:32.303376Z",
"shell.execute_reply": "2025-11-14T09:41:32.302637Z",
"shell.execute_reply.started": "2025-11-14T09:41:32.283623Z"
}
},
"source": [
"## 问卷导入数据库"
]
},
{
"cell_type": "markdown",
"id": "88f6e148-bfd3-4394-8cfd-de7c84306431",
"metadata": {},
"source": [
"### 导入人员信息"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "747ff8ae-9e50-452f-9dcf-f5ba7c5b8f51",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"import psycopg2\n",
"\n",
"conn = psycopg2.connect(\n",
" host=\"localhost\",\n",
" database=\"tice\",\n",
" user=\"mydata\",\n",
" password=\"songyi\"\n",
")\n",
"cur = conn.cursor()\n",
"wb = openpyxl.load_workbook('data/宁夏能化干预人员问卷（20251114）.xlsx',data_only=True)\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"person = {}\n",
"for n in range(2, sheet.max_row+1):\n",
" code = str(sheet.cell(n, 6).value)\n",
" person.setdefault(code, {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 3).value\n",
" dict1['sex'] = sheet.cell(n, 4).value\n",
" birth = str(sheet.cell(n, 5).value).split()[0]\n",
" if len(birth)==7:\n",
" dict1['birth'] = birth+'-01'\n",
" else:\n",
" dict1['birth'] = birth\n",
" dict1['unit'] = sheet.cell(n, 7).value\n",
" person[code] = dict1\n",
"org_id = 1\n",
"data1 = []\n",
"for k,v in person.items():\n",
" tuple1 = (v['name'],v['sex'],v['unit'],v['birth'],k,org_id)\n",
" print(tuple1)\n",
" data1.append(tuple1)\n",
"sql = \"INSERT INTO fitness_person ( name, sex,unit,birth,code,org_id) VALUES (%s, %s, %s,%s, %s, %s)\" \n",
"#print(data1)\n",
"cur.executemany(sql, data1)\n",
"conn.commit()\n",
"\n",
"# 关闭连接\n",
"cur.close()\n",
"conn.close()"
]
},
{
"cell_type": "markdown",
"id": "5c2a37a0-18d3-4c89-8dd9-283a417b5c60",
"metadata": {},
"source": [
"### 导入问卷信息"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0b386dac-a335-41ba-8838-59b2866bb9a3",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"import psycopg2\n",
"\n",
"conn = psycopg2.connect(\n",
" host=\"localhost\",\n",
" database=\"tice\",\n",
" user=\"mydata\",\n",
" password=\"songyi\"\n",
")\n",
"cur = conn.cursor()\n",
"\n",
"org_id = 1\n",
"event_id = 1\n",
"filename = 'data/surveys_records_宁夏能化.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"title = ['date_created', 'height', 'weight', 'next_weight', 'waist', 'hip', 'level4', 'level3', 'level2', 'recipe', 'level1', 'last_level4', 'last_level3', 'last_level2', 'last_level1', 'last_recipe', 'last_lose', 'last_sport', 'sport_type', 'sport_duration', 'last_sport_time', 'last_lose_Comment', 'last_recipe_Comment', 'last_lose_weight', 'last_sport_Comment', 'sport_type_Comment']\n",
"data_title = ['height', 'weight', 'next_weight', 'waist', 'hip', 'level4', 'level3', 'level2', 'recipe', 'level1', 'last_level4', 'last_level3', 'last_level2', 'last_level1', 'last_recipe', 'last_lose', 'last_sport', 'sport_type', 'sport_duration', 'last_sport_time', 'last_lose-Comment', 'last_recipe-Comment', 'last_lose_weight', 'last_sport-Comment', 'sport_type-Comment']\n",
"for item in dict1:\n",
" \n",
" code = item['data']['code']\n",
" sql = \"SELECT id from fitness_person where code = %s and org_id = %s\"\n",
" params = (code,org_id)\n",
" cur.execute(sql, params)\n",
" rows = cur.fetchone()\n",
" if rows:\n",
" list2 = []\n",
" id = rows[0]\n",
" list2.append(event_id)\n",
" list2.append(id)\n",
" date_created = item['date_created']\n",
" list2.append(date_created)\n",
" for xm in data_title:\n",
" if xm in item['data'].keys():\n",
" if xm =='sport_type':\n",
" list2.append(','.join(item['data'][xm]))\n",
" else:\n",
" list2.append(item['data'][xm])\n",
" else:\n",
" list2.append('')\n",
" list1.append(tuple(list2))\n",
"sql = \"INSERT INTO fitness_survey_data (event_id,user_id,date_created, height, weight, next_weight, waist, hip, level4, level3, level2, recipe, level1, last_level4, last_level3, last_level2, last_level1, last_recipe, last_lose, last_sport, sport_type, sport_duration, last_sport_time, last_lose_Comment, last_recipe_Comment, last_lose_weight, last_sport_Comment, sport_type_Comment)\" \n",
"sql = sql + \" VALUES (%s,%s, %s, %s,%s, %s, %s, %s, %s,%s, %s, %s, %s, %s,%s, %s, %s, %s, %s,%s, %s, %s, %s, %s,%s, %s, %s, %s)\"\n",
"cur.executemany(sql, list1)\n",
"conn.commit()\n",
"\n",
"# 关闭连接\n",
"cur.close()\n",
"conn.close()"
]
},
{
"cell_type": "markdown",
"id": "83a2518b-12d8-4ef8-8ee9-5b4289a94208",
"metadata": {},
"source": [
"## 问卷导入JSON"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b7133988-213c-4b52-8d6b-17b56b8ea310",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"wb = openpyxl.load_workbook('data/宁夏能化干预人员问卷（20251114）.xlsx',data_only=True)\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"person = {}\n",
"for n in range(2, sheet.max_row+1):\n",
" code = str(sheet.cell(n, 6).value)\n",
" person.setdefault(code, {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 3).value\n",
" dict1['sex'] = sheet.cell(n, 4).value\n",
" birth = str(sheet.cell(n, 5).value).split()[0]\n",
" if len(birth)==7:\n",
" dict1['birth'] = birth+'-01'\n",
" else:\n",
" dict1['birth'] = birth\n",
" dict1['unit'] = sheet.cell(n, 7).value\n",
" person[code] = dict1\n",
"#print(person)\n",
"\n",
"filename = 'data/surveys_records_宁夏能化.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"title = ['date_created', 'height', 'weight', 'next_weight', 'waist', 'hip', 'level4', 'level3', 'level2', 'recipe', 'level1', 'last_level4', 'last_level3', 'last_level2', 'last_level1', 'last_recipe', 'last_lose', 'last_sport', 'sport_type', 'sport_duration', 'last_sport_time', 'last_lose_Comment', 'last_recipe_Comment', 'last_lose_weight', 'last_sport_Comment', 'sport_type_Comment']\n",
"data_title = ['height', 'weight', 'next_weight', 'waist', 'hip', 'level4', 'level3', 'level2', 'recipe', 'level1', 'last_level4', 'last_level3', 'last_level2', 'last_level1', 'last_recipe', 'last_lose', 'last_sport', 'sport_type', 'sport_duration', 'last_sport_time', 'last_lose-Comment', 'last_recipe-Comment', 'last_lose_weight', 'last_sport-Comment', 'sport_type-Comment']\n",
"for item in dict1: \n",
" dict2 = {}\n",
" code = item['data']['code']\n",
" rq = item['date_created'].split()[0]\n",
" dict2['height'] = item['data']['height']\n",
" dict2['weight'] = item['data']['weight']\n",
" dict2['next_weight'] = item['data']['weight']-item['data']['next_weight']\n",
" dict2['bmi'] = (item['data']['weight']/item['data']['height'])/item['data']['height']*10000\n",
" bmi = (item['data']['weight']/item['data']['height'])/item['data']['height']*10000\n",
" if bmi<18.5:\n",
" bmi_zt = '体重偏轻'\n",
" elif bmi >=18.5 and bmi <24.0:\n",
" bmi_zt = '体重正常'\n",
" elif bmi >=24.0 and bmi <28.0:\n",
" bmi_zt = '体重超重'\n",
" else:\n",
" bmi_zt = '体重肥胖'\n",
" dict2['bmi_zt'] = bmi_zt\n",
" dict2['waist'] = item['data']['waist']\n",
" dict2['hip'] = item['data']['hip']\n",
" whr = dict2['waist']/dict2['hip']\n",
" if item['data']['gender'] =='male' and whr > 0.9:\n",
" whr_zt = '超标'\n",
" elif item['data']['gender'] =='female' and whr > 0.85:\n",
" whr_zt = '超标'\n",
" else:\n",
" whr_zt = '正常'\n",
" dict2['whr'] = whr\n",
" dict2['whr_zt'] = whr_zt\n",
" if 'sport_type' in item['data'].keys(): \n",
" dict2['sport_type'] = ','.join(item['data']['sport_type']).replace('other','其他')\n",
" dict2['sport_duration'] = item['data']['sport_duration']\n",
" dict2['recipe'] = item['data']['recipe']\n",
" if 'last_sport' in item['data'].keys(): \n",
" dict2['last_sport'] = item['data']['last_sport']\n",
" if 'last_sport_time' in item['data'].keys():\n",
" dict2['last_sport_time'] = item['data']['last_sport_time']\n",
" if 'last_sport-Comment' in item['data'].keys():\n",
" dict2['last_sport-Comment'] = item['data']['last_sport-Comment']\n",
" dict2['last_recipe'] = item['data']['last_recipe']\n",
" if 'last_recipe-Comment' in item['data'].keys(): \n",
" dict2['last_recipe-Comment'] = item['data']['last_recipe-Comment']\n",
" if 'last_lose' in item['data'].keys(): \n",
" dict2['last_lose'] = item['data']['last_lose']\n",
" if 'last_lose_weight' in item['data'].keys():\n",
" dict2['last_lose_weight'] = item['data']['last_lose_weight']\n",
" if 'last_lose-Comment' in item['data'].keys(): \n",
" dict2['last_lose-Comment'] = item['data']['last_lose-Comment']\n",
" if code in person.keys():\n",
" person[code][rq] = dict2\n",
"filename = 'data/宁夏能化干预人员问卷情况.json'\n",
"\n",
"with open(filename,'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
"print(len(person),'ok')\n",
" "
]
},
{
"cell_type": "markdown",
"id": "7805ebad-fe9d-4bc2-a537-c665fc831332",
"metadata": {},
"source": [
"## 问卷信息汇总导出"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "633c35d3-61f0-4a9d-9982-441e4c1291b9",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-17T09:35:16.409939Z",
"iopub.status.busy": "2025-11-17T09:35:16.409246Z",
"iopub.status.idle": "2025-11-17T09:35:16.664860Z",
"shell.execute_reply": "2025-11-17T09:35:16.664302Z",
"shell.execute_reply.started": "2025-11-17T09:35:16.409918Z"
}
},
"outputs": [],
@@ -1179,38 +1446,78 @@
"import json\n",
"import openpyxl\n",
"\n",
"\n",
"title = ['员工编号','姓名','性别','部门','手机号码']\n",
"\n",
"filename = 'data/survey_宁夏能化干预人员.json'\n",
"filename = 'data/宁夏能化干预人员问卷情况.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/宁夏能化干预人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
" \n",
"list1 = []\n",
"for k, v in dict2.items():\n",
" \n",
" if str(k) in dict1.keys():\n",
"list1 = ['name','sex','birth','unit']\n",
"xm = ['height','weight','next_weight','bmi','bmi_zt','waist', 'hip','whr','whr_zt' ]\n",
"data2 = []\n",
"for k,v in dict1.items():\n",
" list2 = []\n",
" list2 = [k,v['name'],v['sex'],v['unit'],dict1[k]['phone']] \n",
" list1.append(list2)\n",
"filename = 'data/宁夏能化干预人员参加问卷人员（20251010）.xlsx'\n",
" \n",
" for k1,v1 in v.items():\n",
" #list2 = []\n",
" if k1 not in list1:\n",
" list2.append(k1)\n",
" list2.sort()\n",
" \n",
" for rq in list2:\n",
" for k1, v1 in v[rq].items():\n",
" data1 = []\n",
" data1.append(rq)\n",
" data1.append(k)\n",
" data1.append(v['unit'])\n",
" data1.append(v['name'])\n",
" data1.append(v['sex'])\n",
" data1.append(v['sex'])\n",
" for item in xm:\n",
" data1.append(v[rq][item])\n",
" if 'sport_type' in v[rq].keys():\n",
" data1.append(v[rq]['sport_type'])\n",
" else:\n",
" data1.append('')\n",
" if 'sport_type' in v[rq].keys():\n",
" data1.append(v[rq]['sport_type'])\n",
" else:\n",
" data1.append('')\n",
" \n",
" if 'sport_duration' in v[rq].keys():\n",
" data1.append(v[rq]['sport_duration'])\n",
" else:\n",
" data1.append('')\n",
" if v[rq]['recipe']=='free':\n",
" data1.append('自行控制')\n",
" else:\n",
" data1.append('减脂餐')\n",
" if v[rq]['last_sport']=='是':\n",
" data1.append('运动时长：'+str(v[rq]['last_sport_time'])+'分钟')\n",
" else:\n",
" data1.append('未运动，'+v[rq]['last_sport-Comment'])\n",
" if v[rq]['last_recipe']=='是':\n",
" data1.append('是')\n",
" else:\n",
" data1.append('否。'+v[rq]['last_recipe-Comment'])\n",
" if v[rq]['last_lose']=='是':\n",
" data1.append('是，减重'+str(v[rq]['last_lose_weight'])+'公斤。')\n",
" elif 'last_lose-Comment' in v[rq].keys():\n",
" data1.append('否。'+v[rq]['last_lose-Comment'])\n",
" else:\n",
" data1.append('否。')\n",
" data2.append(data1)\n",
" \n",
"filename = 'data/宁夏能化干预人员问卷信息（20251114）.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
"for row in list1:\n",
"for row in data2:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename)"
"wb.save(filename) "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f32288ee-167c-4e2a-9679-5d927db34950",
"id": "c19f04a8-64a4-4660-8359-7780de4a5227",
"metadata": {},
"outputs": [],
"source": []
体测单位/新疆油田采油工艺研究院.ipynb
+36 -36
View File
@@ -82,15 +82,15 @@
},
{
"cell_type": "code",
"execution_count": 39,
"execution_count": 1,
"id": "cac3736a-56da-403b-9e62-5caaf989a6d4",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T05:28:56.646944Z",
"iopub.status.busy": "2025-11-14T05:28:56.646299Z",
"iopub.status.idle": "2025-11-14T05:28:58.033233Z",
"shell.execute_reply": "2025-11-14T05:28:58.032644Z",
"shell.execute_reply.started": "2025-11-14T05:28:56.646884Z"
"iopub.execute_input": "2025-11-17T14:38:09.521433Z",
"iopub.status.busy": "2025-11-17T14:38:09.520770Z",
"iopub.status.idle": "2025-11-17T14:38:11.569824Z",
"shell.execute_reply": "2025-11-17T14:38:11.569224Z",
"shell.execute_reply.started": "2025-11-17T14:38:09.521373Z"
}
},
"outputs": [
@@ -98,7 +98,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"72 ok\n"
"82 ok\n"
]
}
],
@@ -195,15 +195,15 @@
},
{
"cell_type": "code",
"execution_count": 40,
"execution_count": 2,
"id": "925f7152-b365-4df8-8d98-73569aef68f8",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T05:30:21.558180Z",
"iopub.status.busy": "2025-11-14T05:30:21.557445Z",
"iopub.status.idle": "2025-11-14T05:30:21.572875Z",
"shell.execute_reply": "2025-11-14T05:30:21.571867Z",
"shell.execute_reply.started": "2025-11-14T05:30:21.558103Z"
"iopub.execute_input": "2025-11-17T14:38:34.526723Z",
"iopub.status.busy": "2025-11-17T14:38:34.525935Z",
"iopub.status.idle": "2025-11-17T14:38:34.542026Z",
"shell.execute_reply": "2025-11-17T14:38:34.541025Z",
"shell.execute_reply.started": "2025-11-17T14:38:34.526661Z"
}
},
"outputs": [
@@ -211,7 +211,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"35\n"
"40\n"
]
}
],
@@ -225,7 +225,7 @@
"filename = 'data/新疆油田采油工艺研究院-202511.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"filename = 'data/marks_20251114-1.csv'\n",
"filename = 'data/marks_20251117-3.csv'\n",
"re_ta = My.get_result(filename,dict1)\n",
"\n",
"\n",
@@ -287,15 +287,15 @@
},
{
"cell_type": "code",
"execution_count": 41,
"execution_count": 3,
"id": "0e71f6b8-e17e-49f8-a577-7a2eb6f5e994",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T05:30:31.220354Z",
"iopub.status.busy": "2025-11-14T05:30:31.219652Z",
"iopub.status.idle": "2025-11-14T05:30:31.233956Z",
"shell.execute_reply": "2025-11-14T05:30:31.232979Z",
"shell.execute_reply.started": "2025-11-14T05:30:31.220290Z"
"iopub.execute_input": "2025-11-17T14:38:58.670424Z",
"iopub.status.busy": "2025-11-17T14:38:58.669763Z",
"iopub.status.idle": "2025-11-17T14:38:58.683725Z",
"shell.execute_reply": "2025-11-17T14:38:58.682758Z",
"shell.execute_reply.started": "2025-11-17T14:38:58.670352Z"
}
},
"outputs": [
@@ -664,15 +664,15 @@
},
{
"cell_type": "code",
"execution_count": 42,
"execution_count": 4,
"id": "83872322-129c-410d-a9a3-ef6f4fe8dcde",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T05:31:42.228026Z",
"iopub.status.busy": "2025-11-14T05:31:42.227253Z",
"iopub.status.idle": "2025-11-14T05:31:42.243026Z",
"shell.execute_reply": "2025-11-14T05:31:42.242577Z",
"shell.execute_reply.started": "2025-11-14T05:31:42.227955Z"
"iopub.execute_input": "2025-11-17T14:41:08.300902Z",
"iopub.status.busy": "2025-11-17T14:41:08.300597Z",
"iopub.status.idle": "2025-11-17T14:41:08.314893Z",
"shell.execute_reply": "2025-11-17T14:41:08.314440Z",
"shell.execute_reply.started": "2025-11-17T14:41:08.300875Z"
}
},
"outputs": [
@@ -680,7 +680,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"35\n"
"40\n"
]
}
],
@@ -692,7 +692,7 @@
"from datetime import date\n",
"\n",
"list1 = []\n",
"filename = 'data/sql_20251114.csv'\n",
"filename = 'data/sql_20251117-1.csv'\n",
"with open(filename,'r',newline='') as csv_file:\n",
" fl = csv.reader(csv_file,delimiter=',')\n",
" header = next(fl) \n",
@@ -823,15 +823,15 @@
},
{
"cell_type": "code",
"execution_count": 43,
"execution_count": 5,
"id": "694ad38e-755e-4885-94a9-c157ddc96564",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T05:32:21.311002Z",
"iopub.status.busy": "2025-11-14T05:32:21.310252Z",
"iopub.status.idle": "2025-11-14T05:32:41.401453Z",
"shell.execute_reply": "2025-11-14T05:32:41.400670Z",
"shell.execute_reply.started": "2025-11-14T05:32:21.310932Z"
"iopub.execute_input": "2025-11-17T14:42:09.546636Z",
"iopub.status.busy": "2025-11-17T14:42:09.546054Z",
"iopub.status.idle": "2025-11-17T14:42:32.426068Z",
"shell.execute_reply": "2025-11-17T14:42:32.424869Z",
"shell.execute_reply.started": "2025-11-17T14:42:09.546580Z"
}
},
"outputs": [
@@ -839,7 +839,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"35\n"
"40\n"
]
}
],
体测单位/沧州炼化.ipynb
+216 -70
View File
@@ -10,15 +10,15 @@
},
{
"cell_type": "code",
"execution_count": 25,
"execution_count": 8,
"id": "270e8c57-36d3-476c-8c50-4d8bc38a918a",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-13T08:43:12.873509Z",
"iopub.status.busy": "2025-11-13T08:43:12.873249Z",
"iopub.status.idle": "2025-11-13T08:43:13.076138Z",
"shell.execute_reply": "2025-11-13T08:43:13.075593Z",
"shell.execute_reply.started": "2025-11-13T08:43:12.873486Z"
"iopub.execute_input": "2025-11-17T01:38:45.210547Z",
"iopub.status.busy": "2025-11-17T01:38:45.209877Z",
"iopub.status.idle": "2025-11-17T01:38:45.422897Z",
"shell.execute_reply": "2025-11-17T01:38:45.422462Z",
"shell.execute_reply.started": "2025-11-17T01:38:45.210491Z"
}
},
"outputs": [
@@ -26,7 +26,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"1301 ok\n"
"1295 ok\n"
]
}
],
@@ -41,8 +41,8 @@
"person = {}\n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = sheet.cell(n, 2).value\n",
" person.setdefault(code, {})\n",
" code = int(sheet.cell(n, 2).value)\n",
" person.setdefault(str(code), {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 4).value\n",
" dict1['sex'] = sheet.cell(n, 5).value\n",
@@ -50,7 +50,7 @@
" dict1['unit'] = sheet.cell(n, 3).value\n",
" if sheet.cell(n, 7).value is not None:\n",
" dict1['phone'] = str(sheet.cell(n, 7).value)\n",
" person[code] = dict1\n",
" person[str(code)] = dict1\n",
"filename = 'data/沧州炼化人员.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
@@ -59,15 +59,48 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"id": "6c5f1858-e01e-4cf0-85b1-2019a37c3b37",
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
"from datetime import date\n",
"\n",
"wb = openpyxl.load_workbook('data/沧州炼化人员.xlsx')\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"person = {}\n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = sheet.cell(n, 2).value\n",
" person.setdefault(str(code), {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 4).value\n",
" dict1['sex'] = sheet.cell(n, 5).value\n",
" dict1['birth'] = str(sheet.cell(n, 6).value).replace('/','-').split(' ')[0] \n",
" dict1['unit'] = sheet.cell(n, 3).value\n",
" if sheet.cell(n, 7).value is not None:\n",
" dict1['phone'] = str(sheet.cell(n, 7).value)\n",
" person[str(code)] = dict1\n",
"filename = 'data/沧州炼化人员.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
"print(len(person),'ok')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "829d9460-a14e-4689-a7c4-d00bbd8c2e32",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-07T08:37:47.436725Z",
"iopub.status.busy": "2025-11-07T08:37:47.435955Z",
"iopub.status.idle": "2025-11-07T08:37:47.582958Z",
"shell.execute_reply": "2025-11-07T08:37:47.582377Z",
"shell.execute_reply.started": "2025-11-07T08:37:47.436655Z"
"iopub.execute_input": "2025-11-16T05:42:54.899442Z",
"iopub.status.busy": "2025-11-16T05:42:54.898753Z",
"iopub.status.idle": "2025-11-16T05:42:55.048242Z",
"shell.execute_reply": "2025-11-16T05:42:55.047690Z",
"shell.execute_reply.started": "2025-11-16T05:42:54.899375Z"
}
},
"outputs": [
@@ -123,26 +156,10 @@
},
{
"cell_type": "code",
"execution_count": 19,
"execution_count": null,
"id": "7b6c8cb8-50ab-4b59-ac9a-6afb3db61476",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-09T05:35:48.182110Z",
"iopub.status.busy": "2025-11-09T05:35:48.181365Z",
"iopub.status.idle": "2025-11-09T05:35:48.197106Z",
"shell.execute_reply": "2025-11-09T05:35:48.196434Z",
"shell.execute_reply.started": "2025-11-09T05:35:48.182041Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1297 ok\n"
]
}
],
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
@@ -175,15 +192,15 @@
},
{
"cell_type": "code",
"execution_count": 29,
"execution_count": 12,
"id": "ccb2fe86-c588-4373-85df-37adda55c694",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T04:02:24.632013Z",
"iopub.status.busy": "2025-11-14T04:02:24.631372Z",
"iopub.status.idle": "2025-11-14T04:02:24.726424Z",
"shell.execute_reply": "2025-11-14T04:02:24.725880Z",
"shell.execute_reply.started": "2025-11-14T04:02:24.631959Z"
"iopub.execute_input": "2025-11-17T01:44:40.400061Z",
"iopub.status.busy": "2025-11-17T01:44:40.399563Z",
"iopub.status.idle": "2025-11-17T01:44:40.476607Z",
"shell.execute_reply": "2025-11-17T01:44:40.476073Z",
"shell.execute_reply.started": "2025-11-17T01:44:40.400012Z"
}
},
"outputs": [
@@ -191,7 +208,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"1175\n"
"1225\n"
]
}
],
@@ -205,7 +222,7 @@
"filename = 'data/沧州炼化人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"filename = 'data/marks_20251114.csv'\n",
"filename = 'data/marks_20251117-1.csv'\n",
"re_ta = My.get_result(filename,dict1)\n",
"\n",
"\n",
@@ -215,6 +232,67 @@
"print(len(re_ta))"
]
},
{
"cell_type": "markdown",
"id": "0748c41c-bb8e-49e4-a88d-814928e9b956",
"metadata": {},
"source": [
"## 导入手工数据"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "9054c821-24a6-4ec3-82b4-1af2fbfd5090",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-17T01:45:32.893349Z",
"iopub.status.busy": "2025-11-17T01:45:32.892548Z",
"iopub.status.idle": "2025-11-17T01:45:32.978502Z",
"shell.execute_reply": "2025-11-17T01:45:32.977928Z",
"shell.execute_reply.started": "2025-11-17T01:45:32.893261Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"122\n",
"123\n",
"1225\n"
]
}
],
"source": [
"import openpyxl\n",
"import json\n",
"from datetime import date\n",
"\n",
"wb = openpyxl.load_workbook('data/沧州俯卧撑手工成绩.xlsx')\n",
"sheet = wb.active\n",
"filename = 'data/result_沧州炼化.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl) \n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = str(sheet.cell(n, 1).value)\n",
" item = 'pushup'\n",
" mark = str(sheet.cell(n, 2).value)\n",
" rq = str(sheet.cell(n, 3).value)\n",
" if code in dict2.keys():\n",
" dict2[code]['rq'] = rq\n",
" dict2[code].setdefault(item,{})\n",
" dict2[code][item]['成绩'] = mark\n",
" else:\n",
" print(code)\n",
" \n",
"filename = 'data/result_沧州炼化-1.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2, fl, ensure_ascii=False) \n",
"print(len(re_ta)) "
]
},
{
"cell_type": "markdown",
"id": "a446935a-db14-41d5-9420-d1a5ddd0e548",
@@ -225,17 +303,9 @@
},
{
"cell_type": "code",
"execution_count": 30,
"execution_count": null,
"id": "503c30bb-c537-43f6-b3c7-a1eeff4c313f",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T04:02:34.921004Z",
"iopub.status.busy": "2025-11-14T04:02:34.920268Z",
"iopub.status.idle": "2025-11-14T04:02:34.953734Z",
"shell.execute_reply": "2025-11-14T04:02:34.953246Z",
"shell.execute_reply.started": "2025-11-14T04:02:34.920949Z"
}
},
"metadata": {},
"outputs": [],
"source": [
"import json\n",
@@ -291,15 +361,15 @@
},
{
"cell_type": "code",
"execution_count": 31,
"execution_count": 7,
"id": "57de7845-76f2-4cdc-88a9-eb869acb28a5",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T04:02:42.621335Z",
"iopub.status.busy": "2025-11-14T04:02:42.620669Z",
"iopub.status.idle": "2025-11-14T04:02:42.655530Z",
"shell.execute_reply": "2025-11-14T04:02:42.654876Z",
"shell.execute_reply.started": "2025-11-14T04:02:42.621305Z"
"iopub.execute_input": "2025-11-17T01:05:50.422689Z",
"iopub.status.busy": "2025-11-17T01:05:50.421236Z",
"iopub.status.idle": "2025-11-17T01:05:50.450916Z",
"shell.execute_reply": "2025-11-17T01:05:50.450368Z",
"shell.execute_reply.started": "2025-11-17T01:05:50.422616Z"
}
},
"outputs": [],
@@ -344,15 +414,15 @@
},
{
"cell_type": "code",
"execution_count": 34,
"execution_count": 14,
"id": "c2ca861f-54ca-4312-bf24-20dbc2f3f2e6",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T04:11:04.381187Z",
"iopub.status.busy": "2025-11-14T04:11:04.380519Z",
"iopub.status.idle": "2025-11-14T04:11:04.413211Z",
"shell.execute_reply": "2025-11-14T04:11:04.412250Z",
"shell.execute_reply.started": "2025-11-14T04:11:04.381125Z"
"iopub.execute_input": "2025-11-17T01:46:18.717093Z",
"iopub.status.busy": "2025-11-17T01:46:18.716407Z",
"iopub.status.idle": "2025-11-17T01:46:18.735809Z",
"shell.execute_reply": "2025-11-17T01:46:18.735127Z",
"shell.execute_reply.started": "2025-11-17T01:46:18.717026Z"
}
},
"outputs": [
@@ -361,17 +431,16 @@
"output_type": "stream",
"text": [
"1553238 齐金永 公用工程部 13231725301 2\n",
"1553763 王鑫 应急救援中心 15632778668 2\n",
"1552999 赵崇胜 储运部 13722775060 2\n",
"01553836 王成柱 炼油一部 13111760190 1\n",
"01553839 徐振柱 炼油一部 17772650508 1\n"
"1553836 王成柱 炼油一部 13111760190 1\n",
"1553839 徐振柱 炼油一部 17772650508 1\n"
]
}
],
"source": [
"import json\n",
"\n",
"filename = 'data/result_沧州炼化.json'\n",
"filename = 'data/result_沧州炼化-1.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"xm = ['bmi','lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n",
@@ -384,10 +453,87 @@
" print(k,v['name'],v['unit'],v['phone'],len(list1))"
]
},
{
"cell_type": "markdown",
"id": "57a9f492-6971-4572-9e9e-8086a49dc6ce",
"metadata": {},
"source": [
"## 导出测试人员信息"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "e014e1f8-e13d-4bb1-a64a-606a3e44a876",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-17T01:46:49.086947Z",
"iopub.status.busy": "2025-11-17T01:46:49.086254Z",
"iopub.status.idle": "2025-11-17T01:46:49.440499Z",
"shell.execute_reply": "2025-11-17T01:46:49.439939Z",
"shell.execute_reply.started": "2025-11-17T01:46:49.086882Z"
}
},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"items = ['lung','grip','flexion','jump','pushup','situp','balance','reaction','step']\n",
"title = ['编号','姓名','性别','单位','部门','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_沧州炼化-1.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/沧州炼化人员.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]['unit'])\n",
" list2.append(dict2[k]['birth'])\n",
" if 'phone' in v.keys():\n",
" list2.append(dict2[k]['phone'])\n",
" else:\n",
" list2.append('')\n",
" \n",
" if 'bmi' in v.keys():\n",
" height = v['bmi']['成绩'].split(',')[0]\n",
" weight = v['bmi']['成绩'].split(',')[1]\n",
" list2.append(height)\n",
" list2.append(weight)\n",
" else:\n",
" list2.append('')\n",
" list2.append('')\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",
" \n",
" list1.append(list2)\n",
"filename = 'data/沧州炼化体测情况表(2025年）-1.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": "code",
"execution_count": null,
"id": "e6dea90d-2b60-4ff5-9598-a49f41b6ab24",
"id": "4042e92b-1d63-489a-9652-3f9f48453db8",
"metadata": {},
"outputs": [],
"source": []
体测单位/镇海.ipynb
+21 -5
View File
@@ -2537,10 +2537,26 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 96,
"id": "9663b933-57f4-486c-80e6-f9d513bbe6a8",
"metadata": {},
"outputs": [],
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-14T07:35:38.747096Z",
"iopub.status.busy": "2025-11-14T07:35:38.746559Z",
"iopub.status.idle": "2025-11-14T07:35:38.947152Z",
"shell.execute_reply": "2025-11-14T07:35:38.945993Z",
"shell.execute_reply.started": "2025-11-14T07:35:38.747068Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"+8613793180751 send success\n"
]
}
],
"source": [
"from tencentcloud.common import credential\n",
"from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException\n",
@@ -2553,7 +2569,7 @@
"\n",
"\n",
"\n",
"dw_jc = \"中国石化镇海炼化公司\"\n",
"dw_jc = \"镇海炼化体测用户\"\n",
"filename = 'data/镇海短信码2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
@@ -2575,7 +2591,7 @@
" client = sms_client.SmsClient(cred, \"ap-guangzhou\", clientProfile)\n",
" req = models.SendSmsRequest()\n",
" req.SmsSdkAppId = \"1400140089\"\n",
" req.SignName = \"坤铭教育\"\n",
" req.SignName = \"北京坤铭教育\"\n",
" req.TemplateId = \"1875765\" \n",
" req.TemplateParamSet = [dw_jc,yzm]\n",
" req.PhoneNumberSet = [phone]\n",
高考数据导入.ipynb
+2 -2
View File
@@ -2459,7 +2459,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -2473,7 +2473,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
"version": "3.12.3"
},
"toc-autonumbering": true,
"toc-showcode": false,