HTTP Proxy Bettercap

In the settings bar (home screen), select "Network Settings" and then click on Ethernet. Here you should select the "Advanced Settings" option, which contains the "Proxy Server Settings" item. To further configure the proxy, select "Configure Manually", type in the proxy hostname and specify the port. Do not forget to list the domains that the proxy server should not use. You should leave this field empty if it does not exist. If the configuration process is successful, you will see the "Settings saved" notification.

In data centers, proxies are used to provide IP to virtual servers. After all, one server there can be used by a dozen users at the same time. And each needs to be allocated its own IP and port. All this is done through proxies.

To speed up scraping by leveraging asynchronous programming in Python, you can use the asyncio library along with asynchronous HTTP requests. The aiohttp library is commonly used for asynchronous HTTP requests. Here's a basic example to help you get started:

Install Required Packages:

pip install aiohttp

Asynchronous Scraping Script:

import asyncio
import aiohttp

async def scrape_url(session, url):
    try:
        async with session.get(url) as response:
            if response.status == 200:
                content = await response.text()
                # Process the content as needed
                print(f"Scraped {url}: {len(content)} characters")
            else:
                print(f"Failed to scrape {url}. Status code: {response.status}")
    except Exception as e:
        print(f"Error scraping {url}: {str(e)}")

async def main():
    urls_to_scrape = [
        'https://example.com/page1',
        'https://example.com/page2',
        # Add more URLs as needed
    ]

    async with aiohttp.ClientSession() as session:
        tasks = [scrape_url(session, url) for url in urls_to_scrape]
        await asyncio.gather(*tasks)

if __name__ == "__main__":
    asyncio.run(main())

• • This script defines an asynchronous function scrape_url to perform the scraping for a given URL.
  • The main function creates an asynchronous HTTP session using aiohttp.ClientSession and gathers the scraping tasks.
  • The asyncio.run(main()) line runs the main asynchronous function.

• Running the Script:

python your_scraper_script.py

This example demonstrates the basics of asynchronous scraping. Asynchronous programming can significantly speed up scraping tasks, especially when making multiple concurrent HTTP requests.

Keep in mind that not all websites support asynchronous scraping, and some may have restrictions or rate limiting. Always adhere to the website's terms of service, and consider adding delays between requests to avoid overloading the server.

To scrape all HTML content from a website using Scrapy, you need to create a spider that visits each page of the website and extracts the HTML content. Here's a simple example:

Create a Scrapy Project:
If you haven't already, create a Scrapy project by running the following commands in your terminal or command prompt:

scrapy startproject myproject
cd myproject

Define a Spider:
Open the spiders directory in your project and create a spider (e.g., html_spider.py). Edit the spider file with the following content:

import scrapy

class HtmlSpider(scrapy.Spider):
    name = 'html_spider'
    start_urls = ['http://example.com']  # Start with the main page of the website

    def parse(self, response):
        # Extract HTML content and yield it
        html_content = response.text
        yield {
            'url': response.url,
            'html_content': html_content
        }

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

This spider, named html_spider, starts with the main page (start_urls) and extracts the HTML content. It then follows links (a::attr(href)) to other pages and extracts their HTML content as well.

Run the Spider:
Run your spider using the following command:

scrapy crawl html_spider -o output.json

This command will execute the html_spider and save the output in a JSON file named output.json. Each item in the JSON file will contain the URL and HTML content of a page.

There are many free VPN services. But it is not safe to use them. After all, they are just engaged in parsing. That is, they collect information about users. Most often - their IP-addresses, as well as text data (these are search queries and their personal information).