IP | Country | PORT | ADDED |
---|---|---|---|
50.168.72.113 | us | 80 | 28 minutes ago |
50.218.208.14 | us | 80 | 28 minutes ago |
50.168.72.117 | us | 80 | 28 minutes ago |
50.175.212.74 | us | 80 | 28 minutes ago |
50.174.7.153 | us | 80 | 28 minutes ago |
72.10.164.178 | ca | 12305 | 28 minutes ago |
50.217.226.40 | us | 80 | 28 minutes ago |
50.174.7.155 | us | 80 | 28 minutes ago |
50.207.199.83 | us | 80 | 28 minutes ago |
50.217.226.43 | us | 80 | 28 minutes ago |
50.175.212.79 | us | 80 | 28 minutes ago |
50.168.72.114 | us | 80 | 28 minutes ago |
72.10.160.174 | ca | 6699 | 28 minutes ago |
50.168.72.118 | us | 80 | 28 minutes ago |
50.217.226.45 | us | 80 | 28 minutes ago |
72.10.160.173 | ca | 25569 | 28 minutes ago |
50.239.72.16 | us | 80 | 28 minutes ago |
50.239.72.18 | us | 80 | 28 minutes ago |
50.218.208.13 | us | 80 | 28 minutes ago |
50.168.72.112 | us | 80 | 28 minutes ago |
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Open the "Data and memory" item in the settings, and then, under "Proxy", click "Proxy settings". In the "Connection" window that opens, select "Add proxy" and then check the SOCKS5 proxy. Next, in the "Server" field, you must enter the IP of the proxy, and in the "Port" field enter the port SOCKS5. The next step is to enter the login from the proxy and the password from the proxy. Now, all you have to do is click "Done".
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.
When performing web scraping with authorization in Python, you typically need to simulate the login process of a user by sending the necessary authentication data (such as username and password) to the website. The exact steps depend on the authentication method used by the website, and there are several common approaches
Basic Authentication (using requests library)
If the website uses HTTP Basic Authentication, you can include the authentication credentials in the request headers using the requests library.
import requests
url = 'https://example.com/data'
username = 'your_username'
password = 'your_password'
response = requests.get(url, auth=(username, password))
if response.status_code == 200:
# Successfully authenticated, you can now parse the content
print(response.text)
else:
print(f"Failed to authenticate. Status code: {response.status_code}")
Form-Based Authentication
For websites that use form-based authentication (login form), you need to send a POST request with the appropriate form data.
import requests
login_url = 'https://example.com/login'
data = {
'username': 'your_username',
'password': 'your_password',
}
# Use a session to persist the authentication across requests
with requests.Session() as session:
response = session.post(login_url, data=data)
if response.status_code == 200:
# Authentication successful, continue with subsequent requests
data_url = 'https://example.com/data'
data_response = session.get(data_url)
print(data_response.text)
else:
print(f"Failed to authenticate. Status code: {response.status_code}")
OAuth Authentication
For websites using OAuth, you might need to use an OAuth library like requests_oauthlib or oauthlib to handle the OAuth flow.
Handling Cookies
Sometimes, authentication is maintained using cookies. In such cases, you need to handle cookies in your requests.
import requests
login_url = 'https://example.com/login'
data = {
'username': 'your_username',
'password': 'your_password',
}
# Use a session to persist the authentication across requests
with requests.Session() as session:
login_response = session.post(login_url, data=data)
if login_response.status_code == 200:
# Authentication successful, continue with subsequent requests
data_url = 'https://example.com/data'
data_response = session.get(data_url)
print(data_response.text)
else:
print(f"Failed to authenticate. Status code: {login_response.status_code}")
To remove all lines with one character from a file in Python, you can read the contents of the file, filter out the lines with one character, and then write the filtered lines back to the file. Here's an example using a simple Python script:
# Input file path
input_file_path = 'your_input_file.txt'
# Output file path
output_file_path = 'your_output_file.txt'
# Read the contents of the input file
with open(input_file_path, 'r') as input_file:
lines = input_file.readlines()
# Filter out lines with one character
filtered_lines = [line for line in lines if len(line.strip()) > 1]
# Write the filtered lines to the output file
with open(output_file_path, 'w') as output_file:
output_file.writelines(filtered_lines)
Such proxy redirects requests from clients to different servers (globally or within a single local network). It can be used for load balancing in different Internet services, for testing web applications, for secured access to local network servers (all "non-client" traffic is ignored).
What else…