IP | Country | PORT | ADDED |
---|---|---|---|
50.175.212.74 | us | 80 | 20 minutes ago |
189.202.188.149 | mx | 80 | 20 minutes ago |
50.171.187.50 | us | 80 | 20 minutes ago |
50.171.187.53 | us | 80 | 20 minutes ago |
50.223.246.226 | us | 80 | 20 minutes ago |
50.219.249.54 | us | 80 | 20 minutes ago |
50.149.13.197 | us | 80 | 20 minutes ago |
67.43.228.250 | ca | 8209 | 20 minutes ago |
50.171.187.52 | us | 80 | 20 minutes ago |
50.219.249.62 | us | 80 | 20 minutes ago |
50.223.246.238 | us | 80 | 20 minutes ago |
128.140.113.110 | de | 3128 | 20 minutes ago |
67.43.236.19 | ca | 17929 | 20 minutes ago |
50.149.13.195 | us | 80 | 20 minutes ago |
103.24.4.23 | sg | 3128 | 20 minutes ago |
50.171.122.28 | us | 80 | 20 minutes ago |
50.223.246.239 | us | 80 | 20 minutes ago |
72.10.164.178 | ca | 16727 | 20 minutes ago |
50.232.104.86 | us | 80 | 20 minutes ago |
50.172.39.98 | us | 80 | 20 minutes ago |
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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).
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:
Ethics and Legality:
Robots.txt:
robots.txt
file to understand if scraping is allowed or restricted.Consent:
Anti-Spam Regulations:
Variability of Email Formats:
Use of APIs:
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 is not possible to set up a proxy connection in the program itself. That is, you should configure it either through the regular settings of Windows, or by using third-party utilities to forward traffic (e.g., through ProxyCap).
Install the Nginx web server and disable the virtual tail. Next, in the /etc/nginx/sites-available directory, create a reverse-proxy.conf file. The file should be saved after completing the installation and quit the editor by typing "wq. You can send information to other servers by using the ngx_http_proxy_module in the terminal. Now activate the directives and test Nginx and the reverse proxy.
What else…