Python 多处理被 selenium 卡住了

Question

所以我有代码可以启动 4 个 selenium chrome 驱动程序并从网页上的元素中抓取数据。代码可以简化成这样：

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()

我运行遇到的问题是，在 5-10 分钟后，其中一个抓取器会停止，唯一能唤醒它的是在浏览器上手动刷新页面。如果我离开它一个小时左右，4 个中的 3 个停止，只有一个是运行ning。他们不会出错或打印任何它只是停止运行ning 的东西。我在两台不同的笔记本电脑上试过，它们都有同样的问题。我也试过用 4 个不同的 mp.Process() 运行ning scrape_url 来做这件事，这也做同样的事情。有其他人运行解决这个问题还是我做错了什么？

Answer 1

一方面，Selenium 已经在创建一个进程，因此使用多线程而不是多处理要好得多，因为无论如何每个线程都会启动一个进程。此外，在 scrape_urls 中，在 driver = webdriver.Chrome(driver_dir) 语句之后，函数的其余部分应包含在 try/finally 语句中，其中 finally 块包含 driver.quit() 以确保驱动程序进程终止，无论是否有异常。现在您将离开所有驱动程序进程运行.

您也可以考虑使用以下技术创建大小为 4 的线程池（或更小，具体取决于要处理的 URL 数量），但池中的每个线程都会自动重用已分配给的驱动程序它的线程，保存在线程本地存储中。您可能希望更改用于创建驱动程序的选项（当前为“无头”模式）：

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()

Python 多处理被 selenium 卡住了

Python Multiprocessing gets stuck with selenium

python

selenium

multiprocessing

python-multiprocessing