Knight Proxy

The basic configuration is written in nginx.conf file in the program directory. You need to create a server article and specify there the port number and the place for cached data. Thus, for example, by using port 8080 you may organize a local proxy to test your own sites.

Data parsing in most cases refers to the collection of technical or other information. For example, a local proxy server can be used for parsing "log data". That is, information about the work of the site, the application, which in the future will be useful for developers to find and fix various bugs.

To install Selenium WebDriver Chromedriver on Linux using Python, follow these steps:

Install Chromedriver:

First, you need to download the Chromedriver binary for your Linux distribution from the Chromedriver download page. Choose the appropriate version for your Linux distribution (e.g., Ubuntu, Debian, Fedora, etc.) and download the .deb, .rpm, or .tar.gz file.

Install Chromedriver using .deb or .rpm package:

If you downloaded the .deb or .rpm package, you can install it using the following commands:

For .deb package:

sudo dpkg -i chromedriver.deb

For .rpm package:

sudo yum -y install chromedriver.rpm

Install Chromedriver using .tar.gz package:

If you downloaded the .tar.gz package, you can install it using the following commands:

Extract the package:

tar -xvf chromedriver.tar.gz

Move the Chromedriver binary to a desired location (e.g., /usr/local/bin):

sudo mv chromedriver /usr/local/bin/

Set the executable permission for the Chromedriver binary:

sudo chmod +x /usr/local/bin/chromedriver

Verify the installation:

To verify that Chromedriver is installed correctly, you can run the following command in the terminal:

chromedriver --version

This should display the Chromedriver version.

Install Selenium Python package:

Finally, install the Selenium Python package using pip:

pip install selenium

Now you have installed Selenium WebDriver Chromedriver on your Linux system using Python. You can use the following Python code to set up the Chrome WebDriver and start a browser session:

from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.chrome.options import Options

# Set up the Chrome WebDriver
chrome_options = Options()
service = Service('/usr/local/bin/chromedriver')
driver = webdriver.Chrome(service=service, options=chrome_options)

# Navigate to the target web page
driver.get("https://www.example.com")

# Close the browser
driver.quit()

Remember to replace "/usr/local/bin/chromedriver" with the actual path to the Chromedriver binary on your system.

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.

It means a private proxy server used by several users. For example, one of them has bought a paid proxy and lets his friend use it for a fee. That is, he "shared" his proxy (shared means "common").