Cb01 Proxy

In Node.js, you can introduce delays in your scraping logic using the setTimeout function, which allows you to execute a function after a specified amount of time has passed. This is useful for implementing delays between consecutive requests to avoid overwhelming a server or to comply with rate-limiting policies.

Here's a simple example using the setTimeout function in a Node.js script:

const axios = require('axios'); // Assuming you use Axios for making HTTP requests

// Function to scrape data from a URL with a delay
async function scrapeWithDelay(url, delay) {
  try {
    // Make the HTTP request
    const response = await axios.get(url);

    // Process the response data (replace this with your scraping logic)
    console.log(`Scraped data from ${url}:`, response.data);

    // Introduce a delay before making the next request
    await sleep(delay);

    // Make the next request or perform additional scraping logic
    // ...

  } catch (error) {
    console.error(`Error scraping data from ${url}:`, error.message);
  }
}

// Function to introduce a delay using setTimeout
function sleep(ms) {
  return new Promise(resolve => setTimeout(resolve, ms));
}

// Example usage
const urlsToScrape = ['https://example.com/page1', 'https://example.com/page2', 'https://example.com/page3'];

// Loop through each URL and initiate scraping with a delay
const delayBetweenRequests = 2000; // Adjust the delay time in milliseconds (e.g., 2000 for 2 seconds)
for (const url of urlsToScrape) {
  scrapeWithDelay(url, delayBetweenRequests);
}

In this example:

• The scrapeWithDelay function performs the scraping logic for a given URL and introduces a delay before making the next request.
• The sleep function is a simple utility function that returns a promise that resolves after a specified number of milliseconds, effectively introducing a delay.
• The urlsToScrape array contains the URLs you want to scrape. Adjust the delay time (delayBetweenRequests) based on your scraping needs.

Please note that introducing delays is crucial when scraping websites to avoid being blocked or flagged for suspicious activity.

If you are experiencing TimeoutException errors when trying to run Selenium in headless mode in PyCharm, there are several potential causes and solutions. Here are some steps to troubleshoot and address the issue:

1. Increase Wait Time:

   • Headless mode may introduce additional latency, and elements might take longer to load. Increase the timeout for explicit waits to give the elements enough time to become available.

from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC

driver = webdriver.Chrome(options=options)

# Increase the timeout as needed
wait = WebDriverWait(driver, 20)

# Example wait for an element to be clickable
element = wait.until(EC.element_to_be_clickable((By.ID, 'your_locator')))

• Use Different Locator Strategies:

  • If one locator strategy is causing timeouts, try using a different one. For example, switch from By.ID to By.XPATH or vice versa.

• Verify Element Identification:

  • Confirm that the element locator used in your script is correct and uniquely identifies the intended element.

• Check for JavaScript Errors:

  • Open the browser console and check for any JavaScript errors that might be affecting the behavior of the page.

• Increase Browser Window Size:

  • Some websites may behave differently in headless mode based on the window size. Try setting a larger window size.

options.add_argument('--window-size=1920,1080')

• Update ChromeDriver:

  • Ensure that you are using the latest version of ChromeDriver that is compatible with your Chrome browser version.

• Use a Custom User Agent:

  • Some websites may behave differently based on the user agent. Try setting a custom user agent.

options.add_argument('--user-agent=Your_Custom_User_Agent')

• Check for Captchas or Additional Security Measures:

  • Some websites may use captchas or additional security measures that could cause delays. Ensure that your script is not encountering captchas.

• Browser Profile:

  • In some cases, the behavior of the browser may change when running in headless mode. Experiment with different browser profiles or use a clean profile.

• Network Issues:

  • Ensure that there are no network-related issues that might be causing delays in loading elements.

• Check Proxy Settings:

  • If you are using a proxy, ensure that the proxy settings are configured correctly for headless mode.

• Headless Mode Compatibility:

  • Some websites may have issues with headless mode due to user agent detection or other factors. Test your script on different websites to see if the issue persists.

To count the number of lost packets over UDP, you can use a combination of network monitoring tools and custom scripts. Here's a step-by-step guide to help you achieve this:

1. Install a network monitoring tool:

You can use a network monitoring tool like Wireshark, tcpdump, or ngrep to capture the UDP packets on your network. These tools allow you to analyze the packets and identify lost packets.

2. Capture UDP packets:

Use the network monitoring tool to capture the UDP packets on the interface where the communication is taking place. For example, if you're monitoring a local server, you might use tcpdump with the following command:

tcpdump -i eth0 udp and host 192.168.1.100

Replace eth0 with the appropriate interface name and 192.168.1.100 with the IP address of the server you're monitoring.

3. Analyze the captured packets:

Once you have captured the UDP packets, analyze them to identify the lost packets. You can do this by looking for the sequence numbers in the UDP packets. If the sequence number of a packet is not consecutive to the previous packet, it means the packet was lost.

4. Write a custom script:

You can write a custom script in a language like Python to parse the captured packets and count the lost packets. Here's an example of a simple Python script that counts lost packets:

import re

def count_lost_packets(packet_data):
    sequence_numbers = re.findall(r'UDP, src port \((\d+)\)', packet_data)
    lost_packets = 0

    for i in range(1, len(sequence_numbers)):
        if int(sequence_numbers[i]) != int(sequence_numbers[i - 1]) + 1:
            lost_packets += 1

    return lost_packets

# Read the captured packets from a file
with open('captured_packets.txt', 'r') as file:
    packet_data = file.read()

# Count the lost packets
lost_packets = count_lost_packets(packet_data)
print(f'Number of lost packets: {lost_packets}')

Replace 'captured_packets.txt' with the path to the file containing the captured packets.

5. Run the script:

Run the script to count the lost packets. The script will output the number of lost packets in the captured data.

On the PC you can use SOCKS5 proxies, for example, through the browser Firefox. There are such a function in the settings, you just need to activate it. The only nuance: the connection speed or ping indicators in this case may be slowed down.

In CentOS, if there is no graphical interface (from the terminal), proxy configuration is done through the export http_proxy=http://User:Pass@Proxy:Port/ command. Accordingly, User is the user, Pass is the password to identify you, Proxy is the IP address of the proxy, and Port is the port number. If you have DE, the configuration can be done via Network Manager (as in any other Linux distribution).