IP | Country | PORT | ADDED |
---|---|---|---|
192.252.211.193 | us | 4145 | 57 minutes ago |
122.151.54.147 | au | 80 | 57 minutes ago |
62.182.204.81 | ru | 88 | 57 minutes ago |
185.93.89.146 | ir | 14567 | 57 minutes ago |
50.63.12.101 | us | 54885 | 57 minutes ago |
139.59.1.14 | in | 8080 | 57 minutes ago |
98.170.57.231 | us | 4145 | 57 minutes ago |
67.201.58.190 | us | 4145 | 57 minutes ago |
128.140.113.110 | de | 8080 | 57 minutes ago |
68.1.210.189 | us | 4145 | 57 minutes ago |
103.118.46.176 | kh | 8080 | 57 minutes ago |
72.211.46.124 | us | 4145 | 57 minutes ago |
80.228.235.6 | de | 80 | 57 minutes ago |
203.95.198.35 | kh | 8080 | 57 minutes ago |
79.110.202.184 | pl | 8081 | 57 minutes ago |
175.34.36.22 | au | 8888 | 57 minutes ago |
50.171.122.27 | us | 80 | 57 minutes ago |
72.195.34.59 | us | 4145 | 57 minutes ago |
192.252.215.2 | us | 4145 | 57 minutes ago |
87.120.103.205 | it | 8080 | 57 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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You need to go to "Settings", click on "WiFi", select the current network to which the smartphone is connected, tap on "Proxy settings". And then - deactivate the item.
When using BeautifulSoup in Python to parse HTML or XML with identical tags, you can use various methods to extract the desired information. One common approach is to use the find_all method along with additional criteria to narrow down the selection.
Here's an example of how you can parse identical tags with BeautifulSoup:
from bs4 import BeautifulSoup
html_content = """
First paragraph
Second paragraph
Third paragraph
"""
soup = BeautifulSoup(html_content, 'html.parser')
# Find all paragraphs within the div with class="example"
div_example = soup.find('div', class_='example')
if div_example:
paragraphs = div_example.find_all('p')
# Print the text content of each paragraph
for paragraph in paragraphs:
print(paragraph.text)
else:
print("Div with class='example' not found.")
In this example, find is used to locate the div with class "example," and then find_all is used to retrieve all paragraph tags within that div. The text content of each paragraph is then printed.
You can adapt this approach to your specific HTML or XML structure. If the identical tags are nested within a specific parent element, use that parent element as a starting point for your search.
Keep in mind that identifying the elements you want to extract may involve inspecting the HTML structure and adapting your code accordingly.
In Selenium, you can load a cookie using the add_cookie() method of the WebDriver object. Here's an example of how to do it:
from selenium import webdriver
# Initialize the WebDriver (e.g., Chrome)
driver = webdriver.Chrome()
# Define the cookie you want to load
cookie = {
"name": "username",
"value": "testuser",
"domain": ".example.com",
"path": "/",
"secure": True,
}
# Add the cookie to the WebDriver
driver.add_cookie(cookie)
# Navigate to the page you want to load with the cookie
driver.get("http://example.com")
In this example, we're using the Chrome WebDriver to add a cookie named "username" with the value "testuser" to the domain ".example.com". The add_cookie() method accepts a dictionary representing the cookie, which includes the name, value, domain, path, secure flag, and other attributes.
After adding the cookie, you can navigate to the desired page using the get() method. The WebDriver will now send the cookie along with each request made to the server.
When creating a Scrapy project in a Docker container, the project files are often placed in the /usr/src/app directory by default. This is a common practice in Docker images for Python projects to keep the source code organized.
Here's a simple example of creating a Scrapy project within a Docker container:
Create a Dockerfile:
Create a file named Dockerfile with the following content:
FROM python:3.8
# Set the working directory
WORKDIR /usr/src/app
# Install dependencies
RUN pip install scrapy
# Create a Scrapy project
RUN scrapy startproject myproject
# Set the working directory to the Scrapy project
WORKDIR /usr/src/app/myproject
Build and Run the Docker Image:
Build the Docker image and run a container:
docker build -t scrapy-container .
docker run -it scrapy-container
This will create a Docker image with Scrapy installed and a new Scrapy project named myproject in the /usr/src/app directory.
Check Project Directory:
When you are inside the container, you can check the contents of the /usr/src/app directory using the ls command:
ls /usr/src/app
You should see the myproject directory among the listed items.
By setting the working directory to /usr/src/app and using it as the base directory for the Scrapy project, it helps keep the project files organized within the container. You can modify the Dockerfile according to your project structure and requirements.
Open the Chrome preferences screen, and then, expanding the advanced settings menu, click on the "Advanced" section. Open the "System" item, then on the tab that opens, click on "Open proxy settings for computer". The proxy settings interface will appear in front of you. This will be either the "System Settings" application or the "Browser Properties" application, depending on your operating system.
What else…