IP | Country | PORT | ADDED |
---|---|---|---|
50.175.123.230 | us | 80 | 17 minutes ago |
50.175.212.72 | us | 80 | 17 minutes ago |
85.89.184.87 | pl | 5678 | 17 minutes ago |
41.207.187.178 | tg | 80 | 17 minutes ago |
50.175.123.232 | us | 80 | 17 minutes ago |
125.228.143.207 | tw | 4145 | 17 minutes ago |
213.143.113.82 | at | 80 | 17 minutes ago |
194.158.203.14 | by | 80 | 17 minutes ago |
50.145.138.146 | us | 80 | 17 minutes ago |
82.119.96.254 | sk | 80 | 17 minutes ago |
85.8.68.2 | de | 80 | 17 minutes ago |
72.10.160.174 | ca | 12031 | 17 minutes ago |
203.99.240.182 | jp | 80 | 17 minutes ago |
212.69.125.33 | ru | 80 | 17 minutes ago |
125.228.94.199 | tw | 4145 | 17 minutes ago |
213.157.6.50 | de | 80 | 17 minutes ago |
203.99.240.179 | jp | 80 | 17 minutes ago |
213.33.126.130 | at | 80 | 17 minutes ago |
122.116.29.68 | tw | 4145 | 17 minutes ago |
83.1.176.118 | pl | 80 | 17 minutes ago |
Simple tool for complete proxy management - purchase, renewal, IP list update, binding change, upload lists. With easy integration into all popular programming languages, PapaProxy API is a great choice for developers looking to optimize their systems.
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Checking proxies for spam is necessary to make sure that they are absolutely clean and are not included in any blacklists and spam databases. You can do it with the help of online checkers, which provide full information related to safety and anonymity of a proxy.
To scrape tags from XML with Python, you can use the xml.etree.ElementTree module, which is part of the Python standard library. Here's an example of how to extract tags from an XML document
Assuming you have an XML file named example.xml like this:
-
Item 1
10.99
-
Item 2
19.99
You can use the following Python code to extract tags:
import xml.etree.ElementTree as ET
# Load the XML file
xml_file_path = 'path/to/example.xml'
tree = ET.parse(xml_file_path)
root = tree.getroot()
# Extract tags
tags = set()
for element in root.iter():
tags.add(element.tag)
# Print the extracted tags
print("Extracted Tags:")
for tag in tags:
print(tag)
This example uses xml.etree.ElementTree to parse the XML file, iterates over the elements, and adds each tag to a set to ensure uniqueness. You can modify this example based on your specific needs.
If you want to extract tags with attributes, you can modify the code accordingly. For example:
import xml.etree.ElementTree as ET
# Load the XML file
xml_file_path = 'path/to/example.xml'
tree = ET.parse(xml_file_path)
root = tree.getroot()
# Extract tags with attributes
tags_with_attributes = set()
for element in root.iter():
tag_with_attributes = element.tag
if element.attrib:
attributes = ', '.join([f"{key}={value}" for key, value in element.attrib.items()])
tag_with_attributes += f" ({attributes})"
tags_with_attributes.add(tag_with_attributes)
# Print the extracted tags with attributes
print("Extracted Tags with Attributes:")
for tag in tags_with_attributes:
print(tag)
This example includes attributes in the extracted tags, displaying them in a format like tag_name (attribute1=value1, attribute2=value2). Adjust the code based on your XML structure and specific requirements.
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.
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.
It depends on how you plan to log in to Facebook. For example, if on a PC, just specify the proxy server settings in the connection properties or in the browser settings. If on a mobile (site or application), you need to specify the proxy data in the settings of the phone itself. Or you can install an application that allows you to automatically set up a VPN connection.
What else…