IP | Country | PORT | ADDED |
---|---|---|---|
23.81.45.202 | jp | 5258 | 32 minutes ago |
208.65.90.21 | us | 4145 | 32 minutes ago |
194.219.134.234 | gr | 80 | 32 minutes ago |
72.195.34.59 | us | 4145 | 32 minutes ago |
161.35.70.249 | de | 80 | 32 minutes ago |
49.207.36.81 | in | 80 | 32 minutes ago |
182.155.254.159 | tw | 80 | 32 minutes ago |
68.71.254.6 | 4145 | 32 minutes ago | |
98.152.200.61 | us | 8081 | 32 minutes ago |
62.99.138.162 | at | 80 | 32 minutes ago |
94.103.86.110 | ru | 13485 | 32 minutes ago |
67.201.33.10 | us | 25283 | 32 minutes ago |
203.99.240.179 | jp | 80 | 32 minutes ago |
50.55.52.50 | us | 80 | 32 minutes ago |
64.202.184.249 | us | 46528 | 32 minutes ago |
113.108.13.120 | cn | 8083 | 32 minutes ago |
83.1.176.118 | pl | 80 | 32 minutes ago |
128.140.113.110 | de | 4145 | 32 minutes ago |
83.168.75.202 | pl | 8081 | 32 minutes ago |
103.118.46.174 | kh | 8080 | 32 minutes ago |
Our proxies work perfectly with all popular tools for web scraping, automation, and anti-detect browsers. Load your proxies into your favorite software or use them in your scripts in just seconds:
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Scraping without libraries in Python typically involves making HTTP requests, parsing HTML (or other markup languages), and extracting data using basic string manipulation or regular expressions. However, it's important to note that using established libraries like requests for making HTTP requests and BeautifulSoup or lxml for parsing HTML is generally recommended due to their ease of use, reliability, and built-in features.
Here's a simple example of scraping without libraries, where we use Python's built-in urllib for making an HTTP request and then perform basic string manipulation to extract data. In this example, we'll scrape the title of a website:
import urllib.request
def scrape_website(url):
try:
# Make an HTTP request
response = urllib.request.urlopen(url)
# Read the HTML content
html_content = response.read().decode('utf-8')
# Extract the title using string manipulation
title_start = html_content.find('') + len('')
title_end = html_content.find(' ', title_start)
title = html_content[title_start:title_end].strip()
return title
except Exception as e:
print(f"Error: {e}")
return None
# Replace 'https://example.com' with the URL you want to scrape
url_to_scrape = 'https://example.com'
scraped_title = scrape_website(url_to_scrape)
if scraped_title:
print(f"Scraped title: {scraped_title}")
else:
print("Scraping failed.")
Keep in mind that scraping without libraries can quickly become complex as you need to handle various aspects such as handling redirects, managing cookies, dealing with different encodings, and more. Libraries like requests and BeautifulSoup abstract away many of these complexities and provide a more robust solution.
Using established libraries is generally recommended for web scraping due to the potential pitfalls and challenges involved in handling various edge cases on the web. Always ensure that your scraping activities comply with the website's terms of service and legal requirements.
It refers to a proxy that changes its IP address according to a set algorithm. This is done to minimize the risk of the proxy being recognized by web applications and to better ensure privacy.
A reverse proxy is mainly used by administrators and is responsible for balancing workload and high availability. The reverse proxy redirects received requests to one of its web servers. From the outside it is completely invisible and looks as if all required resources are concentrated directly in the proxy.
Open "Options" and then, under "Network", click on "Network Proxy". Now enter in the appropriate fields the IP address of the proxy and its port, based on the type of your proxy: HTTP/HTTPS or SOCKS. In case you suddenly need authorization, enter the authorization data in the appropriate field of the IP address.
Text parsing is the collection of text information, which is then converted either to form a log file or to perform the task set by the developer.
What else…