911 SOCKS Proxy

Most users use A-Parser for this purpose. It is one of the best applications for checking web applications. There is a corresponding tab, "Proxy server", in the standard menu of A-Parser. It is where you can specify the settings for the connection. And in the "Tools" section you can use parameters for parsing.

In Node.js, you can parse JSON using the built-in JSON object or the JSON.parse() method. Here's a simple example:

// JSON string
const jsonString = '{"name": "John", "age": 30, "city": "New York"}';

// Parse JSON using JSON.parse()
try {
  const jsonData = JSON.parse(jsonString);
  console.log('Parsed JSON:', jsonData);

  // Access individual properties
  console.log('Name:', jsonData.name);
  console.log('Age:', jsonData.age);
  console.log('City:', jsonData.city);
} catch (error) {
  console.error('Error parsing JSON:', error.message);
}

In this example:

• The jsonString contains a JSON-formatted string.
• JSON.parse() is used to parse the JSON string into a JavaScript object.
• The properties of the resulting object can be accessed just like any other JavaScript object.

If the JSON string is not valid, JSON.parse() will throw an error. To handle potential errors, it's a good practice to use a try...catch block.

If you have a JSON file and want to read and parse it in Node.js, you can use the fs (file system) module along with JSON.parse(). Here's an example:

const fs = require('fs');

// Read JSON file
fs.readFile('path/to/your/file.json', 'utf8', (err, data) => {
  if (err) {
    console.error('Error reading file:', err.message);
    return;
  }

  // Parse JSON data
  try {
    const jsonData = JSON.parse(data);
    console.log('Parsed JSON from file:', jsonData);
  } catch (error) {
    console.error('Error parsing JSON:', error.message);
  }
});

Replace 'path/to/your/file.json' with the actual path to your JSON file.

Remember to handle errors appropriately, especially when dealing with file I/O operations or parsing potentially malformed JSON data.

Here are some general guidelines to approach scraping protected sites:

1. Check Terms of Service:

   • Review the terms of service, robots.txt file, and any other usage policies provided by the website. Some websites explicitly prohibit scraping.

2. Contact the Website Owner:

   • If you have a legitimate reason for scraping and the website provides contact information, consider reaching out to the website owner or administrator to request permission.

3. Use Official APIs:

   • Many websites offer official APIs that allow controlled access to their data. Using an API is a sanctioned and structured way to obtain information.

4. Simulate Human Behavior:

   • Mimic human behavior by setting appropriate headers, handling cookies, and introducing delays between requests. This helps avoid detection mechanisms that may identify automated bots.

5. Handle CAPTCHAs:

   • Some sites may use CAPTCHAs to prevent automated access. Implement mechanisms to handle CAPTCHAs if they are encountered.

6. Use Proxy Servers:

   • Rotate IP addresses using proxy servers to avoid IP-based blocking. However, be aware that some sites may block common proxy server IP ranges.

7. Avoid Aggressive Scraping:

   • Limit the frequency and volume of your requests to avoid overloading the server. Implement rate limiting and throttling to mimic human browsing behavior.

8. Stay Informed:

   • Monitor the website for changes in its structure or policies. Adjust your scraping strategy accordingly to adapt to any modifications.

To run GUI autotests in GitLab CI\CD using Docker, Selenium, and PyTest, you can follow these steps:

1. Create a .gitlab-ci.yml file in the root directory of your project. This file will define the pipeline and the jobs for your CI\CD process.

2. Configure the pipeline to use the appropriate image for your tests. In this case, you can use a Python image with the required dependencies installed.

3. Define the before_script section to set up the environment for the tests, including installing the necessary packages and downloading the required drivers for Selenium.

4. Define the test job to run the PyTest tests using the Selenium WebDriver.

Here's an example of a .gitlab-ci.yml file:

stages:
  - test

variables:
  SELENIUM_CHROME_DRIVER: '102.0.5005.62'
  SELENIUM_FIREFOX_DRIVER: '0.26.0'

image: python:3.8

cache:
  paths:
    - .venv
    - requirements.txt

before_script:
  - apt-get update -qq
  - apt-get install -y --no-install-recommends \
      build-essential \
      wget \
      xvfb \
      xvfb-run
  - pip install --upgrade pip
  - pip install --quiet --upgrade pytest
  - pip install --quiet selenium
  - pip install --quiet webdriver-manager
  - wget https://github.com/SeleniumHQ/selenium/releases/download/v${SELENIUM_CHROME_DRIVER}/chromedriver_linux64.zip
  - unzip chromedriver_linux64.zip chromedriver
  - wget https://github.com/SeleniumHQ/selenium/releases/download/v${SELENIUM_FIREFOX_DRIVER}/geckodriver-v${SELENIUM_FIREFOX_DRIVER}
  - mv geckodriver-v${SELENIUM_FIREFOX_DRIVER} geckodriver

test:
  stage: test
  script:
    - pytest tests/
  tags:
    - selenium
  artifacts:
    reports:
      - html
  only:
    - master
    - merge_requests

This .gitlab-ci.yml file defines a single stage called test that runs the PyTest tests in the tests/ directory. The before_script section installs the necessary dependencies, downloads the Selenium WebDriver for Chrome and Firefox, and sets up the environment for running the tests.

The tags: - selenium line ensures that the job runs on a runner with the selenium tag, which should have the appropriate Selenium WebDriver installed. The artifacts: reports: - html line enables the generation of HTML reports for the test results.

The only: - master - merge_requests line specifies that the tests should be run on every commit to the master branch and on every merge request.

Once you've set up the .gitlab-ci.yml file, commit and push it to your repository. Then, create a new merge request or push to the master branch to trigger the CI\CD pipeline and run the GUI autotests using Docker, Selenium, and PyTest.

To determine if your computer is using a proxy server, you can follow these steps for Windows and macOS:

For Windows:
- Press the Windows key + R to open the Run dialog box.
- Type "inetcpl.cpl" (without quotes) in the Run dialog box and press Enter.
- In the Internet Properties window, go to the Connections tab.
- Click on the "LAN settings" button.
- In the LAN Settings window, if there is a checkmark in the "Use a proxy server for your LAN" box, it means your computer is using a proxy server.

For macOS:
- Click on the Apple menu in the top-left corner of your screen.
- Select "System Preferences" from the dropdown menu.
- Click on "Network" in the System Preferences window.
- Select the network connection you are using (e.g., Wi-Fi, Ethernet) from the left pane.
- Click on the "Advanced" button.
- In the Advanced window, go to the "Proxies" tab to see if there is any proxy settings configured for your network connection. If there are settings, it means your computer is using a proxy server.