Groovy HTTPBuilder Proxy

To deactivate the proxy server on Windows 10, you need to perform the following steps:
Open the "Windows Settings" menu.
Go to the "Network and Internet" tab.
Open the "Proxy Server" section.
Deactivate the "Use setup script" option.
Deactivate "Use proxy server" option. Reboot your computer. If the proxy server option has not been disabled, deactivate the "Define parameters automatically" option in the "Proxy server" section. After that you have to restart your PC again.

To scrape tags from XML with Python, you can use the xml.etree.ElementTree module, which is part of the Python standard library. Here's an example of how to extract tags from an XML document

Assuming you have an XML file named example.xml like this:

    
        Item 1
        10.99
    
    
        Item 2
        19.99
    

You can use the following Python code to extract tags:

import xml.etree.ElementTree as ET

# Load the XML file
xml_file_path = 'path/to/example.xml'
tree = ET.parse(xml_file_path)
root = tree.getroot()

# Extract tags
tags = set()
for element in root.iter():
    tags.add(element.tag)

# Print the extracted tags
print("Extracted Tags:")
for tag in tags:
    print(tag)

This example uses xml.etree.ElementTree to parse the XML file, iterates over the elements, and adds each tag to a set to ensure uniqueness. You can modify this example based on your specific needs.

If you want to extract tags with attributes, you can modify the code accordingly. For example:

import xml.etree.ElementTree as ET

# Load the XML file
xml_file_path = 'path/to/example.xml'
tree = ET.parse(xml_file_path)
root = tree.getroot()

# Extract tags with attributes
tags_with_attributes = set()
for element in root.iter():
    tag_with_attributes = element.tag
    if element.attrib:
        attributes = ', '.join([f"{key}={value}" for key, value in element.attrib.items()])
        tag_with_attributes += f" ({attributes})"
    tags_with_attributes.add(tag_with_attributes)

# Print the extracted tags with attributes
print("Extracted Tags with Attributes:")
for tag in tags_with_attributes:
    print(tag)

This example includes attributes in the extracted tags, displaying them in a format like tag_name (attribute1=value1, attribute2=value2). Adjust the code based on your XML structure and specific requirements.

SQLite is a relational database management system, and XML is a markup language for encoding structured data. SQLite itself doesn't inherently support XML parsing. However, if you have XML data that you want to store in SQLite or retrieve from SQLite, you can follow a process of converting between XML and SQLite data.

Here's a general approach:

Storing XML in SQLite:

1. Convert XML to a Text Representation: Convert your XML data into a text representation, for example, by serializing it as a string. This can be done using XML serialization libraries available in your programming language.

2. Store the Text in a SQLite Table: Create a table in SQLite with a column to store the serialized XML text. Insert the XML data into this table.

CREATE TABLE xml_data (id INTEGER PRIMARY KEY, xml_text TEXT);
INSERT INTO xml_data (xml_text) VALUES ('value');

Retrieving XML from SQLite:

1. Retrieve the Text from the SQLite Table: Query the SQLite table to retrieve the stored XML text.

SELECT xml_text FROM xml_data WHERE id = 1;

Convert Text to XML: Deserialize the retrieved text back into XML using XML parsing libraries.

Example in Python using the xml.etree.ElementTree module:

import xml.etree.ElementTree as ET

# Retrieve XML text from SQLite (replace with actual retrieval logic)
xml_text = "value"

# Parse XML text
root = ET.fromstring(xml_text)

# Access XML elements as needed
element_value = root.find('element').text
print("Element value:", element_value)

This is a basic approach, and the exact steps may depend on the programming language you're using and the tools available in that language for XML serialization and deserialization.

If you're working with XML data frequently, consider exploring databases designed for handling XML, such as XML databases or document-oriented databases, which may offer more native support for XML storage and retrieval. SQLite, being a relational database, is optimized for relational data rather than XML.

To implement a constant scraping process, you can use a combination of a loop and a delay to periodically scrape data from a website. This process is often referred to as "web scraping with intervals" or "periodic scraping." Here's an example using Node.js and the axios library for making HTTP requests

Install Dependencies

Install the required npm packages:

npm install axios

Write the Scraping Script

Create a Node.js script (e.g., constant_scraping.js) with the following code:

const axios = require('axios');

async function scrapeData() {
    try {
        // Replace with your scraping logic
        const response = await axios.get('https://example.com'); // Replace with the URL you want to scrape
        console.log('Scraped data:', response.data);

        // Add additional scraping logic as needed
        // ...

    } catch (error) {
        console.error('Error during scraping:', error.message);
    }
}

// Function to perform constant scraping with a specified interval
async function constantScraping(interval) {
    while (true) {
        await scrapeData();
        await sleep(interval); // Sleep for the specified interval before the next scrape
    }
}

// Function to introduce a delay using setTimeout
function sleep(ms) {
    return new Promise(resolve => setTimeout(resolve, ms));
}

// Set the interval (in milliseconds) for constant scraping
const scrapingInterval = 60000; // 60 seconds

// Start the constant scraping process
constantScraping(scrapingInterval);

Replace 'https://example.com' with the URL you want to scrape.

Adjust the scraping logic within the scrapeData function to meet your specific requirements.

Run the Script:

Run the script using Node.js:

node constant_scraping.js

This script defines a constantScraping function that continuously calls the scrapeData function at a specified interval using a loop and the sleep function. Adjust the interval (scrapingInterval) based on your scraping needs.

Open the control panel of your computer, find and select the item "Network connection", and then click "Show network connections", "Local network connections" and "Properties". If there is a tick next to "Obtain an IP address automatically", then no dedicated proxy has been used. If you see numbers there, it will be your address.