如何在并行处理期间重用 selenium 驱动程序实例? [英] How to reuse a selenium driver instance during parallel processing?

问题描述

为了抓取 URL 池，我使用 joblib 并行处理 selenium.在这种情况下，我面临两个挑战:

To scrape a pool of URLs, I am paralell processing selenium with joblib. In this context, I am facing two challenges:

• 挑战 1 是加快这一过程.目前，我的代码为每个 URL 打开和关闭一个驱动程序实例(理想情况下每个进程一个)
• 挑战 2 是摆脱 CPU 密集型 while 循环，我认为我需要在空结果上continue(我知道这很可能是错误的)

• Challenge 1 is to speed up this process. In the moment, my code opens and closes a driver instance for every URL (ideally would be one for every process)
• Challenge 2 is to get rid of the CPU-intensive while loop that I think I need to continue on empty results (I know that this is most likely wrong)

伪代码:

URL_list = [URL1, URL2, URL3, ..., URL100000]                 # List of URLs to be scraped

def scrape(URL):
  while True:                                                 # Loop needed to use continue
          try:                                                # Try scraping
             driver = webdriver.Firefox(executable_path=path) # Set up driver
             website = driver.get(URL)                        # Get URL
             results = do_something(website)                  # Get results from URL content                                                
             driver.close()                                   # Close worker
             if len(results) == 0:                            # If do_something() failed:                                                                  
                continue                                      # THEN Worker to skip URL                          
             else:                                            # If do_something() worked:
                safe_results("results.csv")                   # THEN Save results               
                break                                         # Go to next worker/URL
          except Exception as e:                              # If something weird happens:  
                save_exception(URL, e)                        # THEN Save error message
                break                                         # Go to next worker/URL

Parallel(n_jobs = 40)(delayed(scrape)(URL) for URL in URL_list))) # Run in 40 processes

我的理解是，为了在迭代中重用驱动程序实例，#Set up driver 行需要放置在 scrape(URL) 之外.但是，scrape(URL) 之外的所有内容都无法到达 joblib 的 Parallel(n_jobs = 40).这意味着您不能在使用 joblib 进行抓取时重用驱动程序实例，这不正确.

My understanding is that in order to re-use a driver instance across iterations, the # Set up driver-line needs to be placed outside scrape(URL). However, everything outside scrape(URL) will not find its way to joblib's Parallel(n_jobs = 40). This would imply that you can't reuse driver instances while scraping with joblib which can't be true.

Q1:上面例子中如何在并行处理过程中重用驱动程序实例?

问题 2:如何在保持上述示例中的功能的同时摆脱 while 循环?

注意:firefox_profile 中禁用 Flash 和图像加载(代码未显示)

Note: Flash and image loading is disabled in firefox_profile (code not shown)

推荐答案

1) 您应该首先创建一组驱动程序:每个进程一个.并将实例传递给工作人员.我不知道如何将驱动程序传递给 Prallel 对象，但您可以使用 threading.current_thread().name 键来识别驱动程序.为此，请使用 backend="threading".所以现在每个线程都有自己的驱动程序.

1) You should first create a bunch of drivers: one for each process. And pass an instance to the worker. I don't know how to pass drivers to an Prallel object, but you could use threading.current_thread().name key to identify drivers. To do that, use backend="threading". So now each thread will has its own driver.

2) 你根本不需要循环.并行对象本身会遍历您的所有网址(我希望我真的理解您使用循环的意图)

2) You don't need a loop at all. Parallel object itself iter all your urls (I hope I realy understend your intentions to use a loop)

import threading
from joblib import Parallel, delayed
from selenium import webdriver

def scrape(URL):
    try:
        driver = drivers[threading.current_thread().name]
    except KeyError:
        drivers[threading.current_thread().name] = webdriver.Firefox()
        driver = drivers[threading.current_thread().name]
    driver.get(URL)
    results = do_something(driver)
    if results:
        safe_results("results.csv")

drivers = {}
Parallel(n_jobs=-1, backend="threading")(delayed(scrape)(URL) for URL in URL_list)
for driver in drivers.values():
    driver.quit()

但我真的不认为使用 n_job 比使用 CPU 获得的利润更多.所以 n_jobs=-1 是最好的(当然我可能错了，试试吧).

But I don't realy think you get profit in using n_job more than you have CPUs. So n_jobs=-1 is the best (of course I may be wrong, try it).

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