我正在尝试与selenium和多处理模块同时进行。 以下是我的方法:
以下是代码:
#!/usr/bin/env python
# encoding: utf-8
import time
import codecs
from selenium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
from multiprocessing import Pool
from Queue import Queue
def download_and_save(link_tuple):
link_id, link = link_tuple
print link_id
w = q.get()
w.get(link)
with codecs.open('%s.html' % link_id, 'w', encoding='utf-8') as f:
f.write(w.page_source)
time.sleep(10)
q.put(w)
def main(num_processes):
links = [
'http://openjurist.org/743/f2d/273/zwiener-v-commissioner-of-internal-revenue',
'http://www.oyez.org/advocates/z/l/lonny_f_zwiener',
'http://www.texasbar.com/attorneys/member.cfm?id=21191',
'https://www.courtlistener.com/opinion/441662/lonny-f-zwiener-and-ardith-e-zwiener-v-commissione/cited-by',
'https://www.courtlistener.com/opinion/441662/lonny-f-zwiener-and-ardith-e-zwiener-v-commissione/authorities/',
'http://www.myheritage.com/names/lonny_zwiene',
'https://law.resource.org/pub/us/case/reporter/F2/743/743.F2d.273.84-4068.htm',
'http://www.ancestry.com/1940-census/usa/Texas/Lonny-F-Zwiener_5bbff',
'http://search.ancestry.com/cgi-bin/sse.dll?gl=34&rank=1&new=1&so=3&MSAV=0&msT=1&gss=ms_f-34&gl=bmd_death&rank=1&new=1&so=1&MSAV=0&msT=1&gss=ms_f-2_s&gsfn=Lonny&gsln=Zwiener&msypn__ftp=T',
'http://www.mocavo.com/Lonny-F-Zwiener-Fredericksburg-Gillespie-Texas-1940-United-States-Census/0798164756456805432',
'http://www.taftlaw.com/attorneys/635-mark-s-yuric'
]
n = len(links)
link_tuples = [(link_id, link) for link_id, link in zip(xrange(n), links)]
pool = Pool(num_processes)
pool.map(download_and_save, link_tuples)
if __name__ == '__main__':
num_processes = 2
q = Queue()
dcap = dict(DesiredCapabilities.PHANTOMJS)
dcap["phantomjs.page.settings.userAgent"] = (
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/42.0.2311.90 Safari/537.36"
)
for i in range(num_processes):
w = webdriver.PhantomJS(desired_capabilities=dcap)
q.put(w)
main(num_processes)
此脚本会运行,但保存的html会重复或丢失。
答案 0 :(得分:0)
以下是我取得成功的另一种方法:您将工作人员保留在__main__中,工作人员从task_q中撤出。
import multiprocessing
import traceback
class scrapeWorker(multiprocessing.Process):
def __init__(self, worker_num, task_q, result_q):
super(scrapeWorker, self).__init__()
self.worker_num = worker_num
self.task_q = task_q
self.result_q = result_q
self.scraper = my_scraper_class() # this contains driver code, methods, etc.
def handleWork(self, work):
assert isinstance(work, tuple) or isinstance(work, list), "work should be a tuple or list. found {}".format(type(work))
assert len(work) == 2, "len(work) != 2. found {}".format(work)
assert isinstance(work[1], dict), "work[1] should be a dict. found {}".format(type(work[1]))
# do the work
result = getattr( self.scraper, work[0] )( **work[1] )
self.result_q.put( result )
# worker.run() is actually called via worker.start()
def run(self):
try:
self.scraper.startDriving()
while True:
work = self.task_q.get()
if work == 'KILL':
self.scraper.driver.quit()
break
self.handleWork( work )
except:
print traceback.format_exc()
raise
if __name__ == "__main__":
num_workers = 4
manager = multiprocessing.Manager()
task_q = manager.Queue()
result_q = manager.Queue()
workers = []
for worker_num in xrange(num_workers):
worker = scrapeWorker(worker_num, task_q, result_q)
worker.start()
workers.append( worker )
# you decide what job_stuff is
# work == [ 'method_name', {'kw_1': val_1, ...} ]
for work in job_stuff:
task_q.put( work )
results = []
while len(results) < len(job_stuff):
results.append( result_q.get() )
for worker in workers:
task_q.put( "KILL" )
for worker in workers:
worker.join()
print "finished!"
####