Python：concurrent.futures如何使其可取消？

Python concurrent.futures和ProcessPoolExecutor提供了一个简洁的界面来安排和监视任务.期货甚至provide一个.cancel()方法：

cancel(): Attempt to cancel the call. If the call is currently being executed and cannot be cancelled then the method will return False, otherwise the call will be cancelled and the method will return True.

不幸的是,在simmilar question(关于asyncio)中,回答声称运行任务是不可取消的,使用这个剪切的文档,但文档不要说,只有它们运行和不可解决.

向进程提交multiprocessing.Events也是不可能的(通过参数执行此操作,如在multiprocess.Process中返回RuntimeError)

我想做什么？我想分区搜索空间并为每个分区运行任务.但它足以拥有一个解决方案,而且这个过程是CPU密集型的.那么有一种实际的舒适方式可以通过使用ProcessPool开始来抵消收益吗？

例：

from concurrent.futures import ProcessPoolExecutor, FIRST_COMPLETED, wait

# function that profits from partitioned search space
def m_run(partition):
    for elem in partition:
        if elem == 135135515:
            return elem
    return False

futures = []
# used to create the partitions
steps = 100000000
with ProcessPoolExecutor(max_workers=4) as pool:
    for i in range(4):
        # run 4 tasks with a partition, but only *one* solution is needed
        partition = range(i*steps,(i+1)*steps)
        futures.append(pool.submit(m_run, partition))

    done, not_done = wait(futures, return_when=FIRST_COMPLETED)
    for d in done:
        print(d.result())

    print("---")
    for d in not_done:
        # will return false for Cancel and Result for all futures
        print("Cancel: "+str(d.cancel()))
        print("Result: "+str(d.result()))

解决方法:

不幸的是,运行期货无法取消.我认为核心原因是在不同的实现上确保相同的API(不可能中断正在运行的线程或协同程序).

Pebble库旨在克服这一限制和其他限制.

from pebble import ProcessPool

def function(foo, bar=0):
    return foo + bar

with ProcessPool() as pool:
    future = pool.schedule(function, args=[1])

    # if running, the container process will be terminated 
    # a new process will be started consuming the next task
    future.cancel()  

标签：concurrent-futures,python,multiprocess
来源： https://codeday.me/bug/20191001/1840651.html