並發模型 - python將進程池放在裝飾器裡為什麼不生效也沒報錯
我想把進程池封裝在裝飾器裡，但它既沒生效也沒報錯
# coding:utf-8
import multiprocessing
import tornado
from tornado.httpclient import AsyncHTTPClient
process_num = 20 # 进程数
url = "https://www.baidu.com"
def handle_request(response):
print str(response)
def run_in_process(process_num):
def _run_in_process(f):
def __run_in_process(*args, **kwargs):
pool = multiprocessing.Pool(processes=process_num)
for i in range(process_num):
pool.apply_async(f, args=args, kwds=kwargs, callback=kwargs.get("callback"))
pool.close()
pool.join()
return __run_in_process
return _run_in_process
@run_in_process(process_num)
def main():
http_client = AsyncHTTPClient()
http_client.fetch(url, callback=handle_request)
global loop
loop = tornado.ioloop.IOLoop.instance()
if loop._running is False:
loop.start()
if __name__ == '__main__':
main()結果如下
/usr/bin/python2.7 /home/xxx/workspace/py_project/crawler/center/sample.py
Process finished with exit code 0但是奇怪的是，我用多進程的方式重寫一次，發現是可以生效的
# coding:utf-8
import multiprocessing
import tornado
from tornado.httpclient import AsyncHTTPClient
process_num = 20 # 进程数
url = "https://www.baidu.com"
def handle_request(response):
print str(response)
def run_in_process(process_num):
def _run_in_process(f):
def __run_in_process(*args, **kwargs):
_processes = []
for i in xrange(process_num):
p = multiprocessing.Process(target=f, args=args, kwargs=kwargs)
p.start()
_processes.append(p)
for p in _processes:
p.join()
return __run_in_process
return _run_in_process
@run_in_process(process_num)
def main():
http_client = AsyncHTTPClient()
http_client.fetch(url, callback=handle_request)
global loop
loop = tornado.ioloop.IOLoop.instance()
if loop._running is False:
loop.start()
if __name__ == '__main__':
main()日誌如下
/usr/bin/python2.7 /home/shufeng/workspace/private_project/jobscrawler/center/sample.py
HTTPResponse(_body=None,buffer=<_io.BytesIO object at 0x7f2fdaa21ef0>,code=200,effective_url='http://www.baidu.com',error=None,headers=<tornado.httputil.HTTPHeaders object at 0x7f2fdaa425d0>,reason='OK',request=<tornado.httpclient.HTTPRequest object at 0x7f2fdaa42250>,request_time=0.014312028884887695,time_info={})
HTTPResponse(_body=None,buffer=<_io.BytesIO object at 0x7f2fdaa21ef0>,code=200,effective_url='http://www.baidu.com',error=None,headers=<tornado.httputil.HTTPHeaders object at 0x7f2fdaa43450>,reason='OK',request=<tornado.httpclient.HTTPRequest object at 0x7f2fdaa430d0>,request_time=0.02327895164489746,time_info={})
HTTPResponse(_body=None,buffer=<_io.BytesIO object at 0x7f2fdaa21ef0>,code=200,effective_url='http://www.baidu.com',error=None,headers=<tornado.httputil.HTTPHeaders object at 0x7f2fdaa43510>,reason='OK',request=<tornado.httpclient.HTTPRequest object at 0x7f2fdaa43190>,request_time=0.026951074600219727,time_info={})
HTTPResponse(_body=None,buffer=<_io.BytesIO object at 0x7f2fdaa21ef0>,code=200,effective_url='http://www.baidu.com',error=None,headers=<tornado.httputil.HTTPHeaders object at 0x7f2fdaa42690>,reason='OK',request=<tornado.httpclient.HTTPRequest object at 0x7f2fdaa42310>,request_time=0.0552978515625,time_info={})
HTTPResponse(_body=None,buffer=<_io.BytesIO object at 0x7f2fdaa24ef0>,code=200,effective_url='http://www.baidu.com',error=None,headers=<tornado.httputil.HTTPHeaders object at 0x7f2fdaa39e10>,reason='OK',request=<tornado.httpclient.HTTPRequest object at 0x7f2fdaa39a90>,request_time=0.05612993240356445,time_info={})同樣的情況也會出現在線程池跟協程的使用上，有人知道這是怎麼回事嗎？
