Python Script to Keep Campus Network Connection Alive

Background : The campus network uses a web‑based login that requires manual entry of username and password, and the session expires after about a day, causing frequent disconnections.

Idea : Create a Python script that runs in an infinite loop, pings 8.8.8.8 to check connectivity, and when the ping fails, automatically performs a POST request to the login URL using stored (Base64‑encoded) credentials, then resumes pinging.

Technical Points :

Use Python's urllib and urllib2 modules to send HTTP POST requests.

Encode/decode credentials with Base64.

Invoke subprocess to run the system ping command.

Implementation Details : The script can be scheduled as a Windows Task or a Linux crontab entry to start on boot, keeping the network alive with minimal CPU (1‑2%) and memory (≈4 MB) usage.

Code :

<code>#coding=utf8
import urllib, urllib2
import base64
import os, subprocess

username = 'your_base64_encoded_username'
password = 'your_base64_encoded_password'
url = 'https://login.xxxx.edu.cn/auth_action.php'  # campus login URL

def isConnecting():
    # Judge network connect status
    res = subprocess.call('ping 8.8.8.8 -n 1', shell=True)
    return False if res else True

def Signon():
    # Sign on
    data = {
        'action': 'login',
        'username': base64.decodestring(username),
        'password': base64.decodestring(password),
        'ac_id': 1,
        'save_me': 0,
        'ajax': 1,
    }
    data = urllib.urlencode(data)
    response = urllib2.urlopen(url, data)
    response = response.read().decode('utf8')
    print(response)

def main():
    while True:
        if not isConnecting():
            # no‑connect status, attempt sign on
            Signon()

if __name__ == "__main__":
    try:
        main()
    except Exception as e:
        print('[ERROR]:')
        print(e)
</code>

Conclusion : This simple script demonstrates how Python can automate routine network tasks, providing a reliable way to keep a lab computer continuously online for remote work. It can also be deployed on a server, Raspberry Pi, or any always‑on machine.