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Asset Name	Asset Type	IP Address	Operating System	Software Version	Threat Type	Vulnerability	Impact	Likelihood	Mitigation Strategy	Last Patch Date	Number of Users	Number of Admins	Number of Connections	Location	Backup Frequency	Backup Type	Backup Location	Encryption Type	Compliance	Logging	Auditing	Incident Response	Business Continuity	Risk Label
Server 1	Physical	192.168.0.1	Windows Server 2019	10.0.177

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alay_dict = pd.read_csv('new_kamusalay.csv', names=['original', 'replacement'], encoding='latin-1')

alay_dict_map = dict(zip(alay_dict['original'], alay_dict['replacement']))

def normalize_alay(text):
    return ' '.join([alay_dict_map[word] if word in alay_dict_map else word for word in text.split(' ')])
  
print("normalize_alay: ", normalize_alay("aamiin adek abis"))
# normalize_alay:  amin adik habis

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function ClickConnect() {
  console.log('Working')
  document
    .querySelector('#top-toolbar > colab-connect-button')
    .shadowRoot.querySelector('#connect')
    .click()
}

setInterval(ClickConnect, 60000)

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Google Images Scraper

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sudo apt-get update
sudo apt-get install software-properties-common
sudo add-apt-repository universe
sudo add-apt-repository ppa:certbot/certbot
sudo apt-get update
sudo apt-get install python3-certbot-nginx

sudo certbot --nginx

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server {
    listen 80;
    server_name www.travens-ai.my.id;

    location /static {
        alias /root/flask-vm/static;
    }

    location / {
        proxy_pass http://127.0.0.1:5000;

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import { Component } from "react";

import logo from "./logo.svg";
import "./App.css";

class App extends Component {
  constructor() {
    super();

    this.state = {

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gpu_info = !nvidia-smi
gpu_info = '\n'.join(gpu_info)
if gpu_info.find('failed') >= 0:
  print('Not connected to a GPU')
else:
  print(gpu_info)
  
from psutil import virtual_memory
ram_gb = virtual_memory().total / 1e9
print('Your runtime has {:.1f} gigabytes of available RAM\n'.format(ram_gb))

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import requests
from bs4 import BeautifulSoup as soup
import os

# Define Website to Download pdf
url = 'website to download pdfs'

# Get Website content
r = requests.get(url)