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I've written a script in python in combination with selenium to scrape the links of different posts from its landing page and finally get the title of each post by tracking the url leading to its inner page. Although the content I parsed here are static ones, I used selenium to see how it works in multiprocessing.

However, my intention is to do the scraping using multiprocessing. So far I know that selenium doesn't support multiprocessing but it seems I was wrong.

My question: how can I reduce the execution time using selenium when it is made to run using multiprocessing?

This is my try (it's a working one):

import requests from urllib.parse import urljoin from multiprocessing.pool import ThreadPool from bs4 import BeautifulSoup from selenium import webdriver def get_links(link): res = requests.get(link) soup = BeautifulSoup(res.text,"lxml") titles = [urljoin(url,items.get("href")) for items in soup.select(".summary .question-hyperlink")] return titles def get_title(url): chromeOptions = webdriver.ChromeOptions() chromeOptions.add_argument("--headless") driver = webdriver.Chrome(chrome_options=chromeOptions) driver.get(url) sauce = BeautifulSoup(driver.page_source,"lxml") item = sauce.select_one("h1 a").text print(item) if __name__ == '__main__': url = "https://stackoverflow.com/questions/tagged/web-scraping" ThreadPool(5).map(get_title,get_links(url))
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    Anytime multiprocessing comes into play it becomes a good opportunity to consider switching from selenium to headless chrome. Commented Nov 26, 2018 at 7:48
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    @Qharr - there are node libraries like puppeteer and nightmarejs that are more suited to things like this than selenium. Selenium is more popular because it's been around forever but it's a bit of a dinosaur and mostly suited to simpler scripts. IMHO at least. Commented Nov 26, 2018 at 8:47
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    No, actually I was suggesting switching from python to node. Commented Nov 26, 2018 at 9:39
  • @pguardiario Thanks. Also learning JS at moment so that is handy. Commented Nov 26, 2018 at 9:41
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    Selenium ist the wrong tool for web scraping. Use the opensource Scrapy Python package instead. It does multiprocessing out of the box, it is easy to write new scripts and store the data in files or a database. Commented Nov 28, 2018 at 8:47

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how can I reduce the execution time using selenium when it is made to run using multiprocessing

A lot of time in your solution is spent on launching the webdriver for each URL. You can reduce this time by launching the driver only once per thread:

(... skipped for brevity ...) threadLocal = threading.local() def get_driver(): driver = getattr(threadLocal, 'driver', None) if driver is None: chromeOptions = webdriver.ChromeOptions() chromeOptions.add_argument("--headless") driver = webdriver.Chrome(chrome_options=chromeOptions) setattr(threadLocal, 'driver', driver) return driver def get_title(url): driver = get_driver() driver.get(url) (...) (...)

On my system this reduces the time from 1m7s to just 24.895s, a ~35% improvement. To test yourself, download the full script.

Note: ThreadPool uses threads, which are constrained by the Python GIL. That's ok if for the most part the task is I/O bound. Depending on the post-processing you do with the scraped results, you may want to use a multiprocessing.Pool instead. This launches parallel processes which as a group are not constrained by the GIL. The rest of the code stays the same.

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7 Comments

Now your solution looks very promising @miraculixx. If you care to paste the full script I'would be very glad to accept your answer because I highly doubt I can implement it myself. This answer definitely deserves upvotes.
@robots.txt glad you like it :-) link to the full script as a gist added (this way the answer here can stay brief i.e. point out only the differences to your script)
Let's wait as long as the bounty is on. Accepted your solution already @miraculixx.
Why did you decide to use threading.local instead of a Queue?
Thread-local data is data whose values are thread specific (source: python3 docs) -- that's what we want here to store the driver instance once per thread. A queue would not help as we don't want to pass data between multiple processes, in fact the opposite.
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The one potential problem I see with the clever one-driver-per-thread answer is that it omits any mechanism for "quitting" the drivers and thus leaving the possibility of processes hanging around. I would make the following changes:

  1. Use instead class Driver that will crate the driver instance and store it on the thread-local storage but also have a destructor that will quit the driver when the thread-local storage is deleted:
class Driver: def __init__(self): options = webdriver.ChromeOptions() options.add_argument("--headless") self.driver = webdriver.Chrome(options=options) def __del__(self): self.driver.quit() # clean up driver when we are cleaned up #print('The driver has been "quitted".')
  1. create_driver now becomes:
threadLocal = threading.local() def create_driver(): the_driver = getattr(threadLocal, 'the_driver', None) if the_driver is None: the_driver = Driver() setattr(threadLocal, 'the_driver', the_driver) return the_driver.driver
  1. Finally, after you have no further use for the ThreadPool instance but before it is terminated, add the following lines to delete the thread-local storage and force the Driver instances' destructors to be called (hopefully):
del threadLocal import gc gc.collect() # a little extra insurance
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My question: how can I reduce the execution time?

Selenium seems the wrong tool for web scraping - though I appreciate YMMV, in particular if you need to simulate user interaction with the web site or there is some JavaScript limitation/requirement.

For scraping tasks without much interaction, I have had good results using the opensource Scrapy Python package for large-scale scrapying tasks. It does multiprocessing out of the box, it is easy to write new scripts and store the data in files or a database -- and it is really fast.

Your script would look something like this when implemented as a fully parallel Scrapy spider (note I did not test this, see documentation on selectors).

import scrapy class BlogSpider(scrapy.Spider): name = 'blogspider' start_urls = ['https://stackoverflow.com/questions/tagged/web-scraping'] def parse(self, response): for title in response.css('.summary .question-hyperlink'): yield title.get('href')

To run put this into blogspider.py and run 

$ scrapy runspider blogspider.py

See the Scrapy website for a complete tutorial.

Note that Scrapy also supports JavaScript through scrapy-splash, thanks to the pointer by @SIM. I didn't have any exposure with that so far so can't speak to this other than it looks well integrated with how Scrapy works.

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I'm overly startled to see that I've got a solution on scrapy. Ain't the title of my post explicit enough what I wish to accomplish?
Selenium ist the wrong tool for web scraping. Use the opensource Scrapy is it though?
@robots.txt no, your question is how can I reduce execution time. As I asked in a previous comment, please specify results of your attempt vv expectations, you may get better answers.
Why Selenium is the wrong tool? How to handle javascript with scrapy?
Selenium definitely is not the wrong tool when it comes to scrape content from websites irrespective of the same being dynamic or not. However, in case of scrapy there is a lightweight tool splash available out there to do the trick as well.
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