Proxy Clean Pump

Connect your computer to a functioning router, then open any browser, go to the settings and enable manual configuration. Specify the IP, gateway with DNSI and subnet mask in the appropriate fields. In the "Home network" tab, under "Computers", go to "IPMP Proxy" and turn off this function. Under "System", click on the gear symbol, and under "Components", specify the Proxy UDP HTTP utility and click "Refresh".

In Windows 8 and later editions it is recommended to setup network proxy through Group Policy. To do this, run GPMC.msc (via "Run" or enter in the "Search"), then select the section with the users, from the list of parameters select "Internet Settings". Further settings are not different from the standard ones in Windows. You can set proxy, specify the start page, enter restrictions and so on.

To quickly scrape a large number of sites using Node.js, you can leverage asynchronous programming and utilize libraries like axios for making HTTP requests and cheerio for parsing HTML. Additionally, you may consider using the p-queue library to manage the concurrency and control the rate of requests. Here's a basic example to get you started

Install Required Packages:

npm install axios cheerio p-queue

Create a Scraper Script:

const axios = require('axios');
const cheerio = require('cheerio');
const PQueue = require('p-queue');

// List of sites to scrape
const sites = [
  'https://example1.com',
  'https://example2.com',
  // Add more URLs as needed
];

// Set the concurrency level (adjust as needed)
const concurrency = 5;

// Initialize a queue with concurrency control
const queue = new PQueue({ concurrency });

// Function to scrape a single site
async function scrapeSite(url) {
  try {
    const response = await axios.get(url);
    const $ = cheerio.load(response.data);

    // Use Cheerio to parse and extract data
    const title = $('title').text();
    console.log(`Scraped ${url} - Title: ${title}`);
  } catch (error) {
    console.error(`Error scraping ${url}: ${error.message}`);
  }
}

// Enqueue scraping tasks for each site
sites.forEach((site) => {
  queue.add(() => scrapeSite(site));
});

// Wait for all tasks to complete
queue.onIdle().then(() => {
  console.log('All scraping tasks completed.');
});

This example uses axios for making HTTP requests, cheerio for HTML parsing, and p-queue for controlling concurrency.

Run the Script:

node your_scraper_script.js

Adjust the sites array with the URLs you want to scrape.

This example uses a simple queue system to control the number of concurrent requests, preventing potential issues with rate limiting or overwhelming the target websites. However, be mindful of the websites' terms of service and robots.txt rules to avoid scraping restrictions.

Sending large files over UDP can be a bit tricky because UDP does not guarantee delivery, order, or even that packets won't be duplicated. However, it is possible to send large files using UDP by breaking the file into smaller chunks and sending each chunk separately. Here's a step-by-step guide on how to do it in Python:

1. Import necessary libraries:

import os
import socket
import pickle

2. Define a function to serialize the file data:

def serialize_file_data(file_data):
    return pickle.dumps(file_data)

3. Create a UDP socket:

def create_udp_socket(host, port):
    sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
    sock.bind((host, port))
    return sock

4. Send the file data over UDP:

def send_file(sock, file_data, host, port):
    serialized_file_data = serialize_file_data(file_data)
    sock.sendto(serialized_file_data, (host, port))

5. Define a function to deserialize the file data:

def deserialize_file_data(file_data):
    return pickle.loads(file_data)

6. Create a function to receive the file data:

def receive_file(sock, host, port):
    while True:
        data, addr = sock.recvfrom(4096)
        file_data = deserialize_file_data(data)
        yield file_data

7. Putting it all together:

if __name__ == "__main__":
    file_path = "large_file.txt"
    host, port = "127.0.0.1", 12345
    sock = create_udp_socket(host, port)
    send_file(sock, file_path, host, port)

On the receiving side, you will need to collect all the received file data and save it to a file.

A proxy pool is a database that includes addresses for multiple proxy servers. For example, each VPN service has one. And it "distributes" them in order to the connected users.