Proxy for Auction.com

In Android to disable the proxy, you need to go to "Settings", then - "Connection and sharing", then - to "VPN". And then just deactivate the item. Many phones also provide for automatic disabling of proxies and VPNs when the device is rebooted. That is, if the user is difficult to understand the settings of the gadget, then you can trivially restart it through a long press the lock button (forced reboot).

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.

Scraping business contacts using regular expressions can be challenging and error-prone, especially considering the variations in contact information formats. Instead of using regular expressions directly, a better approach is to use a dedicated HTML parser like DOMDocument or a library like Simple HTML DOM Parser in PHP. This allows you to navigate the HTML structure and extract relevant information more reliably.

Here's an example using Simple HTML DOM Parser to scrape business contact information

Install Simple HTML DOM Parser:

You can download it from sourceforge and include it in your project, or use Composer:

composer require sunra/php-simple-html-dom-parser

Scraping Script:

find('span.phone-number') as $phoneElement) {
        $contacts[] = $phoneElement->plaintext;
    }

    // Example: Extracting email addresses
    foreach ($html->find('a.email') as $emailElement) {
        $contacts[] = $emailElement->plaintext;
    }

    // Add more logic to extract other types of contact information

    return $contacts;
}

// Example usage
$url = 'https://example.com/business-page';
$businessContacts = scrapeBusinessContacts($url);

// Print the extracted contacts
print_r($businessContacts);

2. Adjust the HTML element selectors (span.phone-number, a.email, etc.) based on the structure of the business contacts on the target website.

Remember:

• Web scraping might violate the terms of service of some websites, so always check and comply with the website's policies.
• The HTML structure of a webpage can change, so your scraping code might need adjustments if the website updates its design.
• Web scraping may be subject to legal and ethical considerations. Ensure you have the right to scrape and use the data.

If Selenium in Python is not able to find the ChromeDriver executable on Linux, there are several common reasons and solutions. Here's a step-by-step guide to troubleshoot and resolve the issue

1. Check ChromeDriver Installation

Ensure that ChromeDriver is installed on your Linux machine. You can download the latest version from the ChromeDriver Downloads page.

2. Specify ChromeDriver Path in Your Script

Explicitly specify the path to ChromeDriver in your Python script using the executable_path argument when initializing the webdriver.Chrome() instance.

from selenium import webdriver

chrome_path = "/path/to/chromedriver"  # Replace with the actual path
driver = webdriver.Chrome(executable_path=chrome_path)

# Your Selenium script...

driver.quit()

3. Add ChromeDriver to System PATH

Add the directory containing ChromeDriver to your system's PATH environment variable. This allows Selenium to automatically locate the ChromeDriver executable.

export PATH=$PATH:/path/to/directory/containing/chromedriver

Alternatively, you can add this line to your shell configuration file (e.g., ~/.bashrc or ~/.bash_profile) to make the change permanent.

4. Check File Permissions

Ensure that the ChromeDriver executable has the necessary execute permissions. You can use the chmod command to add execute permissions if needed.

chmod +x /path/to/chromedriver

5. Use a Virtual Environment

If you are using a virtual environment, ensure that ChromeDriver is installed within the virtual environment. Activate the virtual environment before running your script.

6. Update Selenium and ChromeDriver

Make sure you are using the latest versions of both Selenium and ChromeDriver. Outdated versions may not be compatible with each other.

pip install --upgrade selenium

Download the latest ChromeDriver version from the ChromeDriver Downloads page.

7. Check Chrome Browser Version

Ensure that the version of ChromeDriver you are using is compatible with the version of the Chrome browser installed on your machine. ChromeDriver versions and Chrome browser versions should be in sync.

8. Run in Headless Mode

If you are running your script in headless mode, ensure that your machine has the necessary dependencies for headless browsing.

from selenium import webdriver

chrome_path = "/path/to/chromedriver"  # Replace with the actual path
options = webdriver.ChromeOptions()
options.add_argument('--headless')

driver = webdriver.Chrome(executable_path=chrome_path, options=options)

# Your Selenium script...

driver.quit()

9. Check for Typos

Double-check for any typos or syntax errors in the path to ChromeDriver. Ensure that the path is correct and matches the actual location of the executable.

By addressing these points, you should be able to resolve the issue of Selenium not finding ChromeDriver on Linux. If the problem persists, providing additional details about error messages or behavior would be helpful for further assistance.