Intercepting Proxy Server

Go to "Settings" of the torrent, and then in the settings menu, select the subsection "Connection", which contains network connection settings. Under "Proxy" choose the type of your proxy (Socks5 proxy is recommended), then enter the IP address and proxy port in the appropriate fields, then click "Change". Now everything is ready - the torrent works through a proxy server.

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.

The easiest way to set up a home proxy server is to install a router that supports this function. Then get the proxy data (provided by the service in which it is "rented") and enter it in the router settings. If there is no need for a common proxy (for all devices at once), then it should be configured separately for each device with the help of the utilities integrated in the OS for changing the connection properties.

In web development, the style.left property refers to the left offset position of an element within its containing element. The value of style.left is a string that represents the distance from the element's left edge to the left edge of its containing element. This distance can be specified using various units, such as pixels, percentages, or other length units.

When you retrieve style.left in JavaScript, you get a string representation of this distance. For example:

var element = document.getElementById('exampleElement');
var leftValue = element.style.left; // Returns a string like "10px" or "50%"

To perform numerical calculations or comparisons with the left offset, you might want to parse this string and extract the numeric value. Parsing involves removing the unit (e.g., "px" or "%") and converting the remaining part to a numeric value.

Here's an example of how you can parse the style.left value in JavaScript:

var element = document.getElementById('exampleElement');
var leftValue = element.style.left;

// Parse the numeric value
var parsedLeft = parseFloat(leftValue);

// Now parsedLeft is a numeric value representing the left offset
console.log(parsedLeft);

By parsing the value, you can use it in mathematical operations or make comparisons. Keep in mind that parsing might return NaN (Not a Number) if the value is not a valid number, so it's important to handle such cases appropriately.

To scrape Binance courses data in Python, you can use web scraping libraries such as BeautifulSoup and requests. Here's an example using BeautifulSoup to scrape Binance courses

Install required libraries:

pip install beautifulsoup4 requests

Write the scraping code:

import requests
from bs4 import BeautifulSoup

def scrape_binance_courses():
    url = 'https://www.binance.com/en/academy/courses'

    # Send a GET request to the URL
    response = requests.get(url)

    # Check if the request was successful (status code 200)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')

        # Find the container containing course information
        course_container = soup.find('div', {'class': 'css-7sfsgn'})

        if course_container:
            # Extract course details
            courses = course_container.find_all('div', {'class': 'css-1jiwjuo'})
            
            for course in courses:
                course_title = course.find('div', {'class': 'css-1mg41yd'}).text
                course_description = course.find('div', {'class': 'css-1q62c8m'}).text

                print(f"Title: {course_title}\nDescription: {course_description}\n")

        else:
            print("Course container not found.")
    else:
        print(f"Failed to retrieve the webpage. Status code: {response.status_code}")

# Run the scraping function
scrape_binance_courses()

This example sends a GET request to the Binance Academy courses page, parses the HTML content using BeautifulSoup, and extracts course details such as title and description.

Run the code:

python your_script_name.py