这是我的主要分解程序,我在pool.apply_async(findK, args=(N,begin,end))
中添加了一个回调函数,当分解结束时,prime factorization is over
会提示出一条消息,它工作得很好。
import math
import multiprocessing
def findK(N,begin,end):
for k in range(begin,end):
if N% k == 0:
print(N,"=" ,k ,"*", N/k)
return True
return False
def prompt(result):
if result:
print("prime factorization is over")
def mainFun(N,process_num):
pool = multiprocessing.Pool(process_num)
for i in range(process_num):
if i ==0 :
begin =2
else:
begin = int(math.sqrt(N)/process_num*i)+1
end = int(math.sqrt(N)/process_num*(i+1))
pool.apply_async(findK, args=(N,begin,end) , callback = prompt)
pool.close()
pool.join()
if __name__ == "__main__":
N = 684568031001583853
process_num = 16
mainFun(N,process_num)
现在我想更改apply_async中的回调函数,将prompt更改为shutdown函数,以杀死所有其他进程。
def prompt(result):
if result:
pool.terminate()
未在prompt作用域中定义池实例或未将其传入prompt中。
pool.terminate()
不能在提示函数中工作。
如何将multiprocessing.Pool实例传递给apply_async的回调函数?
(我已经用类的格式做了,只要添加一个类方法,调用self.pool.terminate就可以杀死所有其他进程,怎么做函数格式的工作呢?)
如果没有将pool设置为全局变量,那么pool是否可以传入回调函数?
发布于 2017-09-01 15:52:00
不支持向回调函数传递额外的参数。然而,您有很多优雅的方法来解决这个问题。
您可以将池逻辑封装到一个对象中:
class Executor:
def __init__(self, process_num):
self.pool = multiprocessing.Pool(process_num)
def prompt(self, result):
if result:
print("prime factorization is over")
self.pool.terminate()
def schedule(self, function, args):
self.pool.apply_async(function, args=args, callback=self.prompt)
def wait(self):
self.pool.close()
self.pool.join()
def main(N,process_num):
executor = Executor(process_num)
for i in range(process_num):
...
executor.schedule(findK, (N,begin,end))
executor.wait()
或者,您可以使用返回Future
对象的concurrent.futures.Executor实现。在设置回调之前,只需将池附加到Future
对象即可。
def prompt(future):
if future.result():
print("prime factorization is over")
future.pool_executor.shutdown(wait=False)
def main(N,process_num):
executor = concurrent.futures.ProcessPoolExecutor(max_workers=process_num)
for i in range(process_num):
...
future = executor.submit(findK, N,begin,end)
future.pool_executor = executor
future.add_done_callback(prompt)
发布于 2017-09-01 15:18:17
您可以简单地将本地close
函数定义为回调:
import math
import multiprocessing
def findK(N, begin, end):
for k in range(begin, end):
if N % k == 0:
print(N, "=", k, "*", N / k)
return True
return False
def mainFun(N, process_num):
pool = multiprocessing.Pool(process_num)
def close(result):
if result:
print("prime factorization is over")
pool.terminate()
for i in range(process_num):
if i == 0:
begin = 2
else:
begin = int(math.sqrt(N) / process_num * i) + 1
end = int(math.sqrt(N) / process_num * (i + 1))
pool.apply_async(findK, args=(N, begin, end), callback=close)
pool.close()
pool.join()
if __name__ == "__main__":
N = 684568031001583853
process_num = 16
mainFun(N, process_num)
您还可以使用functool
中的partial
函数,
import functools
def close_pool(pool, results):
if result:
pool.terminate()
def mainFun(N, process_num):
pool = multiprocessing.Pool(process_num)
close = funtools.partial(close_pool, pool)
....
发布于 2017-08-30 10:11:11
你需要让pool
在prompt
的环境中结束。一种可能性是将pool
移到全局作用域中(尽管这不是真正的最佳实践)。这似乎是可行的:
import math
import multiprocessing
pool = None
def findK(N,begin,end):
for k in range(begin,end):
if N% k == 0:
print(N,"=" ,k ,"*", N/k)
return True
return False
def prompt(result):
if result:
print("prime factorization is over")
pool.terminate()
def mainFun(N,process_num):
global pool
pool = multiprocessing.Pool(process_num)
for i in range(process_num):
if i ==0 :
begin =2
else:
begin = int(math.sqrt(N)/process_num*i)+1
end = int(math.sqrt(N)/process_num*(i+1))
pool.apply_async(findK, args=(N,begin,end) , callback = prompt)
pool.close()
pool.join()
if __name__ == "__main__":
N = 684568031001583853
process_num = 16
mainFun(N,process_num)
https://stackoverflow.com/questions/45950741
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