Emory Proxy

JSON scraping typically involves extracting data from a JSON response obtained from an API. When you mention doing JSON scraping sequentially, it could mean processing items in the JSON response one after another. Below is a simple example in Python that demonstrates sequential processing of JSON data:

import requests

def fetch_data(url):
    response = requests.get(url)
    return response.json()

def process_item(item):
    # Replace this with your actual processing logic
    print("Processing item:", item)

def scrape_sequentially(api_url):
    data = fetch_data(api_url)

    # Assuming the JSON response is a list of items
    if isinstance(data, list):
        for item in data:
            process_item(item)
    else:
        print("Invalid JSON format. Expected a list of items.")

# Replace 'https://example.com/api/data' with the actual API URL
api_url = 'https://example.com/api/data'
scrape_sequentially(api_url)

In this example:

1. The fetch_data function sends a GET request to the specified API URL and returns the JSON response.
2. The process_item function represents the logic you want to apply to each item in the JSON response.
3. The scrape_sequentially function fetches the JSON data, checks if it's a list, and then iterates through each item, applying the processing logic sequentially.

Make sure to replace the placeholder URL 'https://example.com/api/data' with the actual URL of the API you want to scrape.

In Selenium, you can find out the URL of a newly opened window by switching to that window and retrieving its URL. Here's a step-by-step guide in Python:

1. Switch to the New Window

After opening a new window, you need to switch the focus of the WebDriver to that window.

from selenium import webdriver

driver = webdriver.Chrome()
driver.get("https://example.com")

# Open a new window (e.g., by clicking a link)
new_window_link = driver.find_element_by_link_text("Open New Window")
new_window_link.click()

# Switch to the new window
new_window_handle = driver.window_handles[-1]
driver.switch_to.window(new_window_handle)

In this example, replace "Open New Window" with the actual link text or locator that opens the new window.

2. Retrieve the URL of the New Window

Once you have switched to the new window, you can retrieve its URL using current_url.

new_window_url = driver.current_url
print("URL of the new window:", new_window_url)

This will print the URL of the new window. You can then store it in a variable or use it as needed in your script.

3. Switch Back to the Original Window (Optional)

If you need to switch back to the original window after retrieving the URL from the new window, you can do so using a similar process.

original_window_handle = driver.window_handles[0]
driver.switch_to.window(original_window_handle)

Replace 0 with the index of the original window's handle in the window_handles list.

Here's the complete example:

from selenium import webdriver

driver = webdriver.Chrome()
driver.get("https://example.com")

# Open a new window (replace with the actual link or action)
new_window_link = driver.find_element_by_link_text("Open New Window")
new_window_link.click()

# Switch to the new window
new_window_handle = driver.window_handles[-1]
driver.switch_to.window(new_window_handle)

# Retrieve the URL of the new window
new_window_url = driver.current_url
print("URL of the new window:", new_window_url)

# Switch back to the original window (optional)
original_window_handle = driver.window_handles[0]
driver.switch_to.window(original_window_handle)

# Continue with your script...

# Close the browser when done
driver.quit()

Make sure to adjust the code based on the actual actions and elements in your application that trigger the opening of a new window.

Extreme RAM consumption in Firefox Selenium can be caused by a variety of factors. Here are some steps you can take to troubleshoot and resolve the issue:

1. Update Firefox and Selenium: Ensure you are using the latest versions of Firefox and Selenium, as updates often include performance improvements and bug fixes.

2. Use Firefox Options: When initializing the Firefox WebDriver, pass the -marionette option to use the Marionette protocol, which can help reduce memory usage.

from selenium import webdriver

driver = webdriver.Firefox(executable_path, options=["-marionette"])

3. Use Firefox Profile: Create a custom Firefox profile and use it with Selenium to limit memory usage.

from selenium import webdriver
from selenium.webdriver.firefox.options import Options
from selenium.webdriver.firefox.firefox_profile import FirefoxProfile

profile = FirefoxProfile()
profile.set_preference("browser.sessionstore.max_tabs_undoc", 0)
profile.set_preference("browser.sessionstore.max_windows_undoc", 0)
profile.set_preference("browser.sessionstore.max_windows", 0)
profile.set_preference("browser.sessionstore.max_tabs", 0)

options = Options()
options.profile = profile

driver = webdriver.Firefox(executable_path, options=options)

4. Limit Browser Tabs: If you are using multiple tabs, try to limit the number of tabs open at the same time, as each tab consumes additional memory.

5. Disable Extensions: Disable any unnecessary browser extensions, as they can consume memory and slow down the browser.

6. Close Unused Windows: Close any unnecessary browser windows to free up memory.

7. Adjust Timeouts: Increase the implicit and explicit wait timeouts to reduce the frequency of operations that might cause memory leaks.

driver.implicitly_wait(10)
driver.set_page_load_timeout(10)

8. Use Headless Mode: Run Firefox in headless mode to reduce memory usage by not rendering the UI.

options.add_argument("--headless")

9. Monitor Memory Usage: Use tools like Task Manager (Windows) or Activity Monitor (macOS) to monitor memory usage and identify any specific tests or operations that are causing high memory consumption.

10. Profile Memory Usage: Use Firefox's built-in performance profiling tools to identify memory leaks and optimize your code.

If none of these steps resolve the issue, consider using a different browser or WebDriver, such as Chrome or Edge, which may have better memory management.

To configure a Socks5 proxy for Chrome in Selenium using Python, you can use the --proxy-server command-line option with the Socks5 proxy address. Here's an example using the webdriver.Chrome class in Python:

from selenium import webdriver
from selenium.webdriver.chrome.service import Service as ChromeService

# Socks5 proxy configuration
socks5_proxy = "socks5://127.0.0.1:1080"  # Replace with your actual Socks5 proxy address

# Configure Chrome options with proxy settings
chrome_options = webdriver.ChromeOptions()
chrome_options.add_argument(f'--proxy-server={socks5_proxy}')

# Create a Chrome WebDriver instance with the configured options
chrome_service = ChromeService(executable_path="path/to/chromedriver")  # Replace with the actual path
driver = webdriver.Chrome(service=chrome_service, options=chrome_options)

# Example: Navigate to a website using the configured proxy
driver.get("https://www.example.com")

# Perform other actions with the WebDriver as needed

# Close the browser window
driver.quit()

- Replace "socks5://127.0.0.1:1080" with the actual Socks5 proxy address you want to use.
- Download the ChromeDriver executable from the official ChromeDriver download page and provide the path to the executable in the executable_path parameter of ChromeService.
- Update the driver.get() method to navigate to the website you want.

Make sure to have the selenium library installed (pip install selenium) and ensure that the ChromeDriver version is compatible with the Chrome browser installed on your system.

The basic configuration is written in nginx.conf file in the program directory. You need to create a server article and specify there the port number and the place for cached data. Thus, for example, by using port 8080 you may organize a local proxy to test your own sites.