Tumblr Proxy

In the ps4 settings, go to "Network" and click on "Establish an Internet connection". In the window that appears, select "How to connect to the network" and check your option: Wi-Fi or Lan. When selecting the connection method, check "Special", and when setting the IP address, click on "Automatic". After that, under "Proxy Server", select "Use", enter the IP address, the port of the proxy server and press "Enter".

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

Parsing huge XML files can be challenging due to their size. Here are some tips for efficient XML parsing:

1. Use Streaming Parsers:

   • Streaming parsers, like SAX (Simple API for XML) or StAX (Streaming API for XML), process XML data sequentially. They don't load the entire XML document into memory, making them memory-efficient for large files.

2. XPath for Selective Parsing:

   • XPath is a query language for XML that allows you to navigate through elements and attributes. Use XPath to selectively parse only the parts of the XML document that you need, rather than parsing the entire file.

3. Incremental Parsing:

   • Break the XML document into smaller chunks and parse them incrementally. This can be useful when dealing with extremely large files. Process one chunk at a time instead of loading the entire file into memory.

4. Memory Management:

   • If using a DOM (Document Object Model) parser, be mindful of memory usage. Large XML files can consume a significant amount of memory when loaded into a DOM. Consider using a streaming approach instead.

5. Parallel Processing:

   • If the XML document is partitioned into multiple sections, you can leverage parallel processing to parse different sections concurrently. Be cautious with synchronization to avoid conflicts.

6. Compression:

   • If the XML files are too large, consider compressing them before parsing. This can reduce the file size and speed up the parsing process. Remember to decompress the file before parsing.

7. Optimize Code and Libraries:

   • Ensure that you are using an efficient XML parsing library. Some libraries are better optimized for large files. Additionally, optimize your code for performance by minimizing unnecessary operations.

8. Use Memory-Mapped Files:

   • Memory-mapped files allow parts of a file to be mapped directly into memory. This can be beneficial for random access to different parts of a large XML file.

9. Consider External Tools:

   • In some cases, using external tools specifically designed for processing large XML files might be a good option. These tools are often optimized for performance and memory usage.

Remember that the optimal approach may vary depending on the specific requirements of your application and the characteristics of the XML files you are dealing with.

Go to settings, find the "Security" menu and click on "Unblock security settings". You will be prompted to agree to the changes, which you will need to confirm by clicking "Yes", which will unlock the "Allow unsupervised access" item. Now click on the text or checkbox to activate the function. On the computer from which you plan to connect remotely, you will need to enter the ID of the first computer and click on "Connect".

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.