python----/达州/数据库连接.ipynb at 2d8c1ea8f9755d399579fa933f432ac4b4a94d3e

Files

T

- 新增websocket客户端和服务端实现
- 添加图片压缩工具和快速压缩脚本
- 实现学生信息处理相关API
- 添加MQTT客户端和消息处理功能
- 更新.gitignore忽略更多文件类型
- 添加数据库操作工具和示例
- 实现多个测试脚本和工具类

2026-04-13 14:47:50 +08:00

29 KiB

Raw Blame History

In [1]:

import pymysql
import snowflake
from faker import Faker
fake = Faker('zh_CN')
import random
# 创建数据库连接
connection = pymysql.connect(
host='192.168.0.244',
user='root',
password='Abcd@123456',
database='qy_school',
charset='utf8'
)
# 创建游标对象
cursor = connection.cursor()
sql="select * from student"
cursor.execute(sql)
result=cursor.fetchall()

In [ ]:

from requests import get,post
import time
from datetime import datetime

ip  = "http://192.168.0.244:8101"
param = {
    "username": "tangchao",
    "password": "123456a",
    "client_id": "client",
    "grant_type": "password",
    "client_secret": "123456",
}
data = get(url=f"{ip}/oauth/token",params=param).json()
token = data["access_token"]
header = {
    "content-type": "application/json",
    "authorization": f"Bearer {token}",
}

[1;31m在当前单元格或上一个单元格中执行代码时 Kernel 崩溃。

[1;31m请查看单元格中的代码，以确定故障的可能原因。

[1;31m单击<a href='https://aka.ms/vscodeJupyterKernelCrash'>此处</a>了解详细信息。

[1;31m有关更多详细信息，请查看 Jupyter <a href='command:jupyter.viewOutput'>log</a>。

In [5]:

sql="select * from student"
cursor.execute(sql)
result=cursor.fetchall()

In [6]:

tem = get(f"{ip}/dorm/bed/pageList?page=1&pageSize=3000&building=&floor=&roomNumber=&grade=&department=&major=&className=&keyword=&pageNumber=1&teamId=106",headers=header).json()["data"]["records"]

In [7]:

ids = [ i["stuId"] for i in tem if i["stuId"]]

In [8]:

ids

Out [8]:

In [7]:

# ids = []
# for item in result:
#     id = item[0]
#     ids.append(id)
# ids = [9131, 9135, 9139, 9140, 9141, 9142, 9151]

In [9]:

sql = "select * from t_camera"
cursor.execute(sql)
camera=cursor.fetchall()
channels = []

In [10]:

for item in camera:
    channels.append(item[17])

In [11]:

channels

Out [11]:

['16',
 '17',
 '18',
 '19',
 '20',
 '21',
 '22',
 '23',
 '24',
 '25',
 '26',
 '27',
 '28',
 '29',
 '30',
 '31',
 '32',
 '33',
 '34',
 '35',
 '36',
 '37',
 '38',
 '39',
 '40',
 '41',
 '42',
 '43',
 '44',
 '45',
 '46',
 '47',
 '1',
 '2',
 '3',
 '4',
 '5',
 '6',
 '7',
 '8',
 '9',
 '10',
 '11',
 '12',
 '13',
 '14',
 '15']

In [12]:

import uuid

In [14]:

times = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
count = random.randint(1, 4)
channel = random.choice(channels)
data = {
  "batch_info": {
    "batch_id": str(uuid.uuid4()),
    "detected_image_path":"",
    "total_faces": count,
    "cameraid": "camera_001",
    "cameracode": "CAM001"
  },
   "results":""
  }
child = []
for item in random.choices(ids, k=count):
    tem =   {
      "sim": "0.876",
      "simFaceurl": "",
      "baseFacesurl": "",
      "faceBaseid": "",
      "name": "",
      "sex": "",
      "empid": f"{item}",
      "telephone": "",
      "remark": "",
      "channel": f"{channel}",
      "ename": "Face",
      "cname": "人脸比对",
      "createtime": times
    }
    child.append(tem)
data["results"] = child
print(data)
post(f"{ip}/ai/stuface/receive",json=data,headers=header).text

Out [14]:

{'batch_info': {'batch_id': '0e76d74a-42ee-4de0-bd3c-b8fd5c817542', 'detected_image_path': '', 'total_faces': 4, 'cameraid': 'camera_001', 'cameracode': 'CAM001'}, 'results': [{'sim': '0.876', 'simFaceurl': '', 'baseFacesurl': '', 'faceBaseid': '', 'name': '', 'sex': '', 'empid': '9941', 'telephone': '', 'remark': '', 'channel': '35', 'ename': 'Face', 'cname': '人脸比对', 'createtime': '2025-10-23 14:36:49'}, {'sim': '0.876', 'simFaceurl': '', 'baseFacesurl': '', 'faceBaseid': '', 'name': '', 'sex': '', 'empid': '9601', 'telephone': '', 'remark': '', 'channel': '35', 'ename': 'Face', 'cname': '人脸比对', 'createtime': '2025-10-23 14:36:49'}, {'sim': '0.876', 'simFaceurl': '', 'baseFacesurl': '', 'faceBaseid': '', 'name': '', 'sex': '', 'empid': '11014', 'telephone': '', 'remark': '', 'channel': '35', 'ename': 'Face', 'cname': '人脸比对', 'createtime': '2025-10-23 14:36:49'}, {'sim': '0.876', 'simFaceurl': '', 'baseFacesurl': '', 'faceBaseid': '', 'name': '', 'sex': '', 'empid': '10540', 'telephone': '', 'remark': '', 'channel': '35', 'ename': 'Face', 'cname': '人脸比对', 'createtime': '2025-10-23 14:36:49'}]}

'{"success":true,"msg":"操作成功","code":0,"data":null}'

In [ ]:

times = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
count = 1
channel = 18
data = {
  "batch_info": {
    "batch_id": str(uuid.uuid4()),
    "detected_image_path":"",
    "total_faces": 3,
    "cameraid": "camera_001",
    "cameracode": "CAM001"
  },
   "results":""
  }
child = []
for item in [11030,11631,10385]:
    tem =   {
      "sim": "0.876",
      "simFaceurl": "",
      "baseFacesurl": "",
      "faceBaseid": "",
      "name": "",
      "sex": "",
      "empid": f"{item}",
      "telephone": "",
      "remark": "",
      "channel": f"{channel}",
      "ename": "Face",
      "cname": "人脸比对",
      "createtime": times
    }
    child.append(tem)
data["results"] = child
post(f"{ip}/ai/stuface/receive",json=data,headers=header).text

'{"success":true,"msg":"操作成功","code":0,"data":null}'

[1;31m在当前单元格或上一个单元格中执行代码时 Kernel 崩溃。

[1;31m请查看单元格中的代码，以确定故障的可能原因。

[1;31m单击<a href='https://aka.ms/vscodeJupyterKernelCrash'>此处</a>了解详细信息。

[1;31m有关更多详细信息，请查看 Jupyter <a href='command:jupyter.viewOutput'>log</a>。

29 KiB Raw Blame History

29 KiB

Raw Blame History