In this blog post, we will explore how to perform parallel scraping using the requests-html library in Python. Scraping websites can be a time-consuming task, especially when dealing with multiple pages or large amounts of data. Parallel scraping allows us to speed up the process by making multiple requests simultaneously.

Introduction to requests-html

requests-html is a Python library that combines the power of both the requests and beautifulsoup4 libraries. It provides a convenient way to make HTTP requests and parse HTML content. The library also includes several useful features like JavaScript rendering, session management, and CSS selectors.

To get started, let’s install the requests-html library:

pip install requests-html

Parallel scraping with requests-html

To demonstrate parallel scraping, let’s imagine we have a list of URLs that we want to scrape simultaneously.

First, we need to import the necessary modules:

from requests_html import HTMLSession
from concurrent.futures import ThreadPoolExecutor

Next, we define a function to scrape a single URL:

def scrape_url(url):
    session = HTMLSession()
    response = session.get(url)
    # Perform scraping operations here
    ...

Inside the scrape_url function, we create an instance of HTMLSession and use it to make a request to the specified URL. We can then perform our scraping operations on the response object.

To scrape multiple URLs in parallel, we can use the ThreadPoolExecutor class from the concurrent.futures module:

urls = ["https://example.com", "https://example.org", "https://example.net"]

with ThreadPoolExecutor() as executor:
    executor.map(scrape_url, urls)

In the example above, we create a list of URLs to scrape and pass it to the executor.map() method along with the scrape_url function. The executor.map() method automatically distributes the tasks across multiple threads and executes them in parallel.

Conclusion

Parallel scraping using requests-html can significantly speed up the process of scraping websites. By leveraging the ThreadPoolExecutor class, we can make simultaneous requests and retrieve data from multiple URLs efficiently.

Remember to respect the website’s terms of service and use parallel scraping responsibly. Additionally, be mindful of any rate limits or concurrency limitations set by the website to avoid causing any issues.

Happy scraping!