如何在流程之间共享课程? [英] How can I share a class between processes?
问题描述
我希望所有进程共享和更新的全局对象具有最小的锁定.
I want to have global object which is shared and updated by all processes with minimum locking.
import multiprocessing
class Counter(object):
def __init__(self):
self.value = 0
def update(self, value):
self.value += value
def update(counter_proxy, thread_id):
counter_proxy.value.update(1)
print counter_proxy.value.value, 't%s' % thread_id, \
multiprocessing.current_process().name
return counter_proxy.value.value
def main():
manager = multiprocessing.Manager()
counter = manager.Value(Counter, Counter())
pool = multiprocessing.Pool(multiprocessing.cpu_count())
for i in range(10):
pool.apply(func = update, args = (counter, i))
pool.close()
pool.join()
print 'Should be 10 but is %s.' % counter.value.value
if __name__ == '__main__':
main()
结果是这样-不是10,而是零.看起来该对象的共享值未更新.如何锁定和更新该值?
The result is this - not 10 but zero. It looks like the object's shared value is not updated. How can I lock and update such value?
0 t0 PoolWorker-2
0 t1 PoolWorker-3
0 t2 PoolWorker-5
0 t3 PoolWorker-8
0 t4 PoolWorker-9
0 t5 PoolWorker-2
0 t6 PoolWorker-7
0 t7 PoolWorker-4
0 t8 PoolWorker-6
0 t9 PoolWorker-3
Should be 10 but is 0.
@dano是目前最好的解决方案-我将自定义管理器与类代理混合在一起.
Current the best solution by @dano - I mixed custom manager with class proxy.
import multiprocessing
from multiprocessing.managers import BaseManager, NamespaceProxy
class Counter(object):
def __init__(self):
self.value = 0
def update(self, value):
self.value += value
def update(counter_proxy, thread_id):
counter_proxy.update(1)
class CounterManager(BaseManager):
pass
class CounterProxy(NamespaceProxy):
_exposed_ = ('__getattribute__', '__setattr__', '__delattr__', 'update')
def update(self, value):
callmethod = object.__getattribute__(self, '_callmethod')
return callmethod(self.update.__name__, (value,))
CounterManager.register('Counter', Counter, CounterProxy)
def main():
manager = CounterManager()
manager.start()
counter = manager.Counter()
pool = multiprocessing.Pool(multiprocessing.cpu_count())
for i in range(10):
pool.apply(func = update, args = (counter, i))
pool.close()
pool.join()
print 'Should be 10 but is %s.' % counter.value
if __name__ == '__main__':
main()
推荐答案
multiprocessing.Value
不适用于自定义类,它应该类似于自定义管理器并注册您的课程用它.如果您不直接访问value
,而是通过方法进行修改/访问,您的生活也将更加轻松,默认情况下,该方法将为您的班级创建的默认Proxy
导出.常规属性(例如Counter.value
)不是,因此,如果没有其他自定义项,就无法访问它们.这是一个工作示例:
multiprocessing.Value
isn't designed to be used with custom classes, it's supposed to be similar to a multiprocessing.sharedctypes.Value
. Instead, you need to create a custom manager and register your class with it. Your life will also be easier if you don't access value
directly, but modify/access it via methods, which will get exported by the default Proxy
created for your class by default. Regular attributes (like Counter.value
) aren't, so they aren't accessible without additional customization. Here's a working example:
import multiprocessing
from multiprocessing.managers import BaseManager
class MyManager(BaseManager): pass
def Manager():
m = MyManager()
m.start()
return m
class Counter(object):
def __init__(self):
self._value = 0
def update(self, value):
self._value += value
def get_value(self):
return self._value
MyManager.register('Counter', Counter)
def update(counter_proxy, thread_id):
counter_proxy.update(1)
print counter_proxy.get_value(), 't%s' % thread_id, \
multiprocessing.current_process().name
return counter_proxy
def main():
manager = Manager()
counter = manager.Counter()
pool = multiprocessing.Pool(multiprocessing.cpu_count())
for i in range(10):
pool.apply(func=update, args=(counter, i))
pool.close()
pool.join()
print 'Should be 10 but is %s.' % counter.get_value()
if __name__ == '__main__':
main()
输出:
1 t0 PoolWorker-2
2 t1 PoolWorker-8
3 t2 PoolWorker-4
4 t3 PoolWorker-5
5 t4 PoolWorker-6
6 t5 PoolWorker-7
7 t6 PoolWorker-3
8 t7 PoolWorker-9
9 t8 PoolWorker-2
10 t9 PoolWorker-8
Should be 10 but is 10.
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