Pornleach Proxy

Open the browser settings and go to the "Advanced" section. Click on "System" and then, in the window that opens, click on "Open proxy settings for computer". A window will appear in front of you, showing all the current settings. Another way to find out the http proxy is to download and install the SocialKit Proxy Checker utility on your computer.

To parse all pages of a website in Python, you can use web scraping libraries such as requests for fetching HTML content and BeautifulSoup or lxml for parsing and extracting data. Additionally, you might need to manage crawling and handle the structure of the website.

Here's a basic example using requests and BeautifulSoup:

import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin, urlparse

def get_all_links(url):
    response = requests.get(url)
    soup = BeautifulSoup(response.text, 'html.parser')
    
    # Extract all links on the page
    links = [a['href'] for a in soup.find_all('a', href=True)]
    
    return links

def parse_all_pages(base_url):
    all_links = get_all_links(base_url)
    all_pages_content = []

    for link in all_links:
        # Form the full URL for each link
        full_url = urljoin(base_url, link)

        # Ensure the link is within the same domain to avoid external links
        if urlparse(full_url).netloc == urlparse(base_url).netloc:
            # Get HTML content of the page
            page_content = requests.get(full_url).text
            all_pages_content.append({'url': full_url, 'content': page_content})

    return all_pages_content

# Example usage
base_url = 'https://example.com'
all_pages_data = parse_all_pages(base_url)

# Now you have a list of dictionaries with data for each page
for page_data in all_pages_data:
    print(f"URL: {page_data['url']}")
    # Process HTML content of each page as needed
    # For example, you can use BeautifulSoup for further data extraction

This example fetches all links from the initial page and then iterates through each link, fetching and storing the HTML content of the linked pages. Make sure to handle relative URLs and filter external links based on your requirements.

In C++, parsing XML Schema Definition (XSD) files involves reading and interpreting the structure defined in the XSD to understand the schema of XML documents. There is no standard library in C++ specifically for parsing XSD files, but you can use existing XML parsing libraries in conjunction with your own logic to achieve this.

Here's an example using the pugixml library for XML parsing in C++. Before you begin, make sure to download and install the pugixml library (https://pugixml.org/) and link it to your project.

#include 
#include "pugixml.hpp"

void parseXSD(const char* xsdFilePath) {
    pugi::xml_document doc;
    
    if (doc.load_file(xsdFilePath)) {
        // Iterate through elements and attributes in the XSD
        for (pugi::xml_node node = doc.child("xs:schema"); node; node = node.next_sibling("xs:schema")) {
            for (pugi::xml_node element = node.child("xs:element"); element; element = element.next_sibling("xs:element")) {
                const char* elementName = element.attribute("name").value();
                std::cout << "Element Name: " << elementName << std::endl;

                // You can extract more information or navigate deeper into the XSD structure as needed
            }
        }
    } else {
        std::cerr << "Failed to load XSD file." << std::endl;
    }
}

int main() {
    const char* xsdFilePath = "path/to/your/file.xsd";
    parseXSD(xsdFilePath);

    return 0;
}

In this example:

• The pugixml library is used to load and parse the XSD file.
• The code then iterates through the <xs:schema> elements and extracts information about <xs:element> elements.

Remember to replace "path/to/your/file.xsd" with the actual path to your XSD file.

Note that handling XSD files can be complex depending on the complexity of the schema. If your XSD contains namespaces or more intricate structures, you might need to adjust the code accordingly.

Always check the documentation of the XML parsing library you choose for specific details on usage and features. Additionally, be aware that XML schema parsing in C++ is not as standardized as XML parsing itself, and the approach may vary based on the specific requirements of your application.

In Scrapy, you can control the caching behavior of requests made by rules in your spider by adjusting the dont_cache attribute in the Rule object. The dont_cache attribute, when set to True, indicates that the requests matched by the rule should not be cached.

Here's an example of how you can use dont_cache in a CrawlSpider:

from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule

class MySpider(CrawlSpider):
    name = 'my_spider'
    allowed_domains = ['example.com']
    start_urls = ['http://example.com']

    rules = (
        # Example Rule with dont_cache set to True
        Rule(LinkExtractor(allow=('/page/')), callback='parse_page', follow=True, dont_cache=True),
    )

    def parse_page(self, response):
        # Your parsing logic for individual pages goes here
        pass

- The spider is defined as a CrawlSpider.
- The Rule is created with LinkExtractor to match URLs that contain '/page/' in them.
- The dont_cache=True attribute is set to True in the Rule, indicating that requests matched by this rule should not be cached.

By setting dont_cache to True, Scrapy will make sure that requests matched by this rule will be fetched without considering the cache. This is useful when you want to ensure that each request to the specified URLs results in a fresh response, bypassing any cached data.

It is necessary to go to "Settings", select "WiFi", then specify the network for which you want to disable the proxy. After that, tap on "Proxy settings" and check "Off". This option is valid for iOS version 10 and higher.