IP | Country | PORT | ADDED |
---|---|---|---|
50.171.187.51 | us | 80 | 56 minutes ago |
189.202.188.149 | mx | 80 | 56 minutes ago |
72.10.164.178 | ca | 20987 | 56 minutes ago |
212.69.125.33 | ru | 80 | 56 minutes ago |
203.99.240.182 | jp | 80 | 56 minutes ago |
203.99.240.179 | jp | 80 | 56 minutes ago |
80.228.235.6 | de | 80 | 56 minutes ago |
213.143.113.82 | at | 80 | 56 minutes ago |
50.172.150.134 | us | 80 | 56 minutes ago |
62.99.138.162 | at | 80 | 56 minutes ago |
50.114.33.143 | kh | 8080 | 56 minutes ago |
50.217.226.47 | us | 80 | 56 minutes ago |
194.182.187.78 | at | 3128 | 56 minutes ago |
67.43.228.250 | ca | 16555 | 56 minutes ago |
50.232.104.86 | us | 80 | 56 minutes ago |
50.223.246.238 | us | 80 | 56 minutes ago |
192.111.134.10 | ca | 4145 | 56 minutes ago |
50.221.74.130 | us | 80 | 56 minutes ago |
188.40.59.208 | de | 3128 | 56 minutes ago |
50.219.249.61 | us | 80 | 56 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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In simple terms, it is a logically separated part of the main local or public network. It is through it that many users can use a proxy through a single server at the same time. Each connection is allocated to a separate subnet.
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.
To connect to a proxy server with a password, provide the proxy address, port, and authentication credentials (username and password) in your browser or application settings. For popular browsers like Google Chrome and Mozilla Firefox, follow these general steps:
Open the browser and go to its settings.
Locate the proxy settings section.
Enter the proxy server address, port, username, and password.
Save the settings.
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.
This depends directly on how the proxy server works. Some of them do not require any authorization at all, others require username and password for access, and others require you to view ads and so on. Which option will be used depends directly on the service that provides access to the proxy server.
What else…