3 回答

TA贡献1966条经验 获得超4个赞
问题在于该counter变量未在您的进程之间共享:每个单独的进程都在创建它自己的本地实例并对其进行递增。
有关可用于在进程之间共享状态的某些技术,请参阅文档的本部分。在您的情况下,您可能希望Value在工作人员之间共享一个实例
这是示例的工作版本(带有一些虚拟输入数据)。请注意,它使用的是全局值,在实践中我会尽量避免使用这些值:
from multiprocessing import Pool, Value
from time import sleep
counter = None
def init(args):
''' store the counter for later use '''
global counter
counter = args
def analyze_data(args):
''' increment the global counter, do something with the input '''
global counter
# += operation is not atomic, so we need to get a lock:
with counter.get_lock():
counter.value += 1
print counter.value
return args * 10
if __name__ == '__main__':
#inputs = os.listdir(some_directory)
#
# initialize a cross-process counter and the input lists
#
counter = Value('i', 0)
inputs = [1, 2, 3, 4]
#
# create the pool of workers, ensuring each one receives the counter
# as it starts.
#
p = Pool(initializer = init, initargs = (counter, ))
i = p.map_async(analyze_data, inputs, chunksize = 1)
i.wait()
print i.get()

TA贡献1775条经验 获得超8个赞
没有竞争条件错误的计数器类:
class Counter(object):
def __init__(self):
self.val = multiprocessing.Value('i', 0)
def increment(self, n=1):
with self.val.get_lock():
self.val.value += n
@property
def value(self):
return self.val.value
添加回答
举报