Python多处理与硒陷入困境

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Python多处理与硒陷入困境

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So I have code that spins up 4 selenium chrome drivers and scrapes data from an element on the web pages. The code can be simplified to something like this:

import json import multiprocessing as mp from selenium import webdriver from selenium.webdriver.common.by import By from selenium.webdriver.support.ui import WebDriverWait class scraper(): def __init__(self,list_of_urls, process_num): self.urls = list_of_urls self.process_num = process_num def scrape_urls(self): driver = webdriver.Chrome(driver_dir) data = [] for url in self.urls: driver.get(url) element = WebDriverWait(driver, timeout=7).until(lambda d: d.find_element(by=By.CLASS_NAME, value="InterestingData")) data.append(element.text) print("Scraper # ", self.process_num," got data from: ",url) return data if __name__ == '__main__': with open('array_of_urls', 'r') as infile: urls = json.load(infile) number_of_processes=4 length_of_urls = len(urls) partition_into = math.ceil(length_of_urls/number_of_processes) scrapers = [] start = 0 end = start + partition_into for num in range(number_of_processes): new_scraper = scraper(urls[start:end],num) scrapers.append(new_scraper) start = end end = start + partition_into if end > length_of_urls: end = length_of_urls-1 with mp.Pool(processes=number_of_processes) as pool: result_array = [] for num in range(number_of_processes): result_array.append(pool.apply_async(scrapers[num].scrape_urls)) pool.close() pool.join()

The problem I am running into is that after 5-10 minutes one of the scrapers would just stop, the only thing that would wake it back up is to manually refresh the page on the browser. If I leave it for an hour or so, 3 of the 4 stop and only one is running. They don't error out or print anything it just stops running. I've tried it on 2 different laptops and they both have the same issue. I've also tried doing this with 4 different mp.Process() running scrape_url and that also does the same thing. Has anyone else run into this issue or am I doing something wrong here?

推荐答案

For one thing, Selenium is already creating a process so it is far better to be using multithreading instead of multiprocessing since each thread will be starting a process anyway. Also, in scrape_urls after your driver = webdriver.Chrome(driver_dir) statement, the rest of the function should be enclosed in a try/finally statement where the finally block contains driver.quit() to ensure that the driver process is terminated whether there is an exception or not. Right now you are leaving all the driver processes running.

You might also consider using the following technique that creates a thread pool of size 4 (or less depending on how many URLs there are to process), but each thread in the pool automatically reuses the driver that has been allocated to its thread, which is kept in thread local storage. You might wish to change the options used to create the driver (currently "headless" mode):

import json from selenium import webdriver from selenium.webdriver.common.by import By from selenium.webdriver.support.ui import WebDriverWait from multiprocessing.pool import ThreadPool import threading import gc threadLocal = threading.local() class Driver: def __init__(self): options = webdriver.ChromeOptions() options.add_argument("--headless") options.add_experimental_option('excludeSwitches', ['enable-logging']) 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".') @classmethod def create_driver(cls): the_driver = getattr(threadLocal, 'the_driver', None) if the_driver is None: print('Creating new driver.') the_driver = cls() threadLocal.the_driver = the_driver driver = the_driver.driver the_driver = None return driver def scraper(url): """ This now scrapes a single URL. """ driver = Driver.create_driver() driver.get(url) element = WebDriverWait(driver, timeout=7).until(lambda d: d.find_element(by=By.CLASS_NAME, value="InterestingData")) print("got data from: ", url) return element.text with open('array_of_urls', 'r') as infile: urls = json.load(infile) number_of_processes = min(4, len(urls)) with ThreadPool(processes=number_of_processes) as pool: result_array = pool.map(scraper, urls) # Must ensure drivers are quitted before threads are destroyed: del threadLocal # This should ensure that the __del__ method is run on class Driver: gc.collect() pool.close() pool.join()

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Python多处理与硒陷入困境

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