YouTube View Bot Proxy

There are special online services that use IP and HTTP connection tags to determine if a proxy is being used from your equipment. The most popular are Proxy Checker, Socproxy.

Scraping Razor pages in a separate AppDomain in C# is an advanced scenario, and it's not a common approach. However, if you have specific requirements that necessitate this, you can achieve it by creating a separate AppDomain for the scraping task. Keep in mind that creating a new AppDomain introduces complexity, and you need to consider potential security and performance implications.

Below is a basic example of how you can use a separate AppDomain for scraping Razor pages. In this example, I'm assuming that you want to perform scraping logic within the separate AppDomain:

using System;
using System.Reflection;

class Program
{
    static void Main()
    {
        // Create a new AppDomain
        AppDomain scraperDomain = AppDomain.CreateDomain("ScraperDomain");

        try
        {
            // Load and execute the scraping logic in the separate AppDomain
            scraperDomain.DoCallBack(() =>
            {
                // This code runs in the separate AppDomain

                // Load necessary assemblies (e.g., your scraping library)
                Assembly.Load("YourScrapingLibrary");

                // Perform your scraping logic
                RazorPageScraper scraper = new RazorPageScraper();
                scraper.Scrape();
            });
        }
        finally
        {
            // Unload the AppDomain to release resources
            AppDomain.Unload(scraperDomain);
        }
    }
}

// RazorPageScraper class in a separate assembly or namespace
public class RazorPageScraper
{
    public void Scrape()
    {
        // Your scraping logic here
        Console.WriteLine("Scraping Razor pages...");
    }
}

In this example:

1. The AppDomain is created using AppDomain.CreateDomain.
2. The scraping logic is executed inside the separate AppDomain using AppDomain.DoCallBack.
3. The RazorPageScraper class, containing the scraping logic, is assumed to be in a separate assembly or namespace.

Keep in mind:

• Security: Loading and executing code in a separate AppDomain may have security implications. Ensure that you understand the risks and take appropriate precautions.
• Performance: Creating a new AppDomain incurs overhead. It might not be suitable for lightweight scraping tasks.

This example is simplified, and you need to adapt it based on your specific requirements and the structure of your scraping code.

Web scraping to collect email addresses from web pages raises ethical and legal considerations. It's important to respect privacy and adhere to the terms of service of the websites you are scraping. Additionally, harvesting email addresses for unsolicited communication may violate anti-spam regulations.

If you have a legitimate use case, here's a basic example in Python using the requests library and regular expressions to extract email addresses. Note that this is a simplistic example and may not cover all email address variations:

import re
import requests

def extract_emails_from_text(text):
    email_pattern = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b'
    return re.findall(email_pattern, text)

def scrape_emails_from_url(url):
    response = requests.get(url)
    if response.status_code == 200:
        page_content = response.text
        emails = extract_emails_from_text(page_content)
        return emails
    else:
        print(f"Failed to fetch content from {url}. Status code: {response.status_code}")
        return []

# Example usage
url_to_scrape = 'https://example.com'
emails_found = scrape_emails_from_url(url_to_scrape)

if emails_found:
    print("Email addresses found:")
    for email in emails_found:
        print(email)
else:
    print("No email addresses found.")

Keep in mind the following:

1. Ethics and Legality:

   • Ensure that your scraping activities are ethical and comply with the laws and terms of service of the websites you are scraping.

2. Robots.txt:

   • Check the website's robots.txt file to understand if scraping is allowed or restricted.

3. Consent:

   • Respect user privacy and obtain consent if necessary.

4. Anti-Spam Regulations:

   • Be aware of and comply with anti-spam regulations in your region.

5. Variability of Email Formats:

   • Email address formats can vary, and the regular expression provided is a basic example. You may need to adjust it based on the actual formats you encounter.

6. Use of APIs:

   • If available, consider using official APIs provided by websites to access data rather than scraping.

To create your own proxy server, you can use open-source software such as Privoxy or Squid. Here's a step-by-step guide using Privoxy:

Install Privoxy: Download the latest version of Privoxy from the official website (https://www.privoxy.org/download/) and install it on your computer. The installation process varies depending on your operating system.

Configure Privoxy: After installing Privoxy, open the configuration file, usually located at /etc/privoxy/config.txt on Linux or C:\Program Files\Privoxy\config\config.txt on Windows. You can also find the configuration file in the installation directory.

Edit the configuration file: Open the configuration file in a text editor and make the following changes:

Uncomment the following line by removing the # symbol at the beginning:

listen-address 0.0.0.0

Uncomment the following line and change the port number if desired (e.g., 8118):

listen-port 8118

forward-suffix .privoxy

Add the following line to forward requests to a specific destination server (replace with the desired server's address):

forward-suffix 

Save the configuration file and restart Privoxy: Close the text editor and restart Privoxy to apply the changes. On Linux, you can use the following command:

sudo /etc/init.d/privoxy restart

On Windows, locate the Privoxy service in the Windows Services list and restart it.

Test your proxy server: Open a web browser and configure it to use your new proxy server (e.g., http://localhost:8118). Test by accessing a website to ensure that the proxy server is working correctly.

To keep only unique external links while scraping with Scrapy, you can use a set to track the visited external links and filter out duplicates. Here's an example spider that demonstrates how to achieve this:

import scrapy
from urllib.parse import urlparse, urljoin

class UniqueLinksSpider(scrapy.Spider):
    name = 'unique_links'
    start_urls = ['http://example.com']  # Replace with the starting URL of your choice
    visited_external_links = set()

    def parse(self, response):
        # Extract all links from the current page
        all_links = response.css('a::attr(href)').extract()

        for link in all_links:
            full_url = urljoin(response.url, link)

            # Check if the link is external
            if urlparse(full_url).netloc != urlparse(response.url).netloc:
                # Check if it's a unique external link
                if full_url not in self.visited_external_links:
                    # Add the link to the set of visited external links
                    self.visited_external_links.add(full_url)

                    # Yield the link or process it further
                    yield {
                        'external_link': full_url
                    }

        # Follow links to other pages
        for next_page_url in response.css('a::attr(href)').extract():
            yield scrapy.Request(url=urljoin(response.url, next_page_url), callback=self.parse)

- visited_external_links is a class variable that keeps track of the unique external links across all instances of the spider.
- The parse method extracts all links from the current page.
- For each link, it checks if it is an external link by comparing the netloc (domain) of the current page and the link.
- If the link is external, it checks if it is unique by looking at the visited_external_links set.
- If the link is unique, it is added to the set, and the spider yields the link or processes it further.
- The spider then follows links to other pages, recursively calling the parse method.

Remember to replace the start_urls with the URL from which you want to start scraping.