如何使用线程并行压缩迭代器？

Question

假设我有N 个生成器，可以生成项目流gs = [..] # list of generators。

我可以轻松地将它们组合在一起，从:zip中的每个相应生成器中获取元组生成器。gstuple_gen = zip(*gs)

这会按顺序调用next(g)每个并将结果收集到一个元组中。但如果每个项目的生产成本都很高，我们可能希望在多个线程上并行化工作。ggsnext(g)

我怎样才能实现pzip(..)这个功能呢？

Answer 1

您所要求的可以通过创建一个生成器来实现，该生成器从apply_asyncThreadPool 上的调用生成结果。

仅供参考，我使用pandas.read_csv通过指定参数获得的迭代器对这种方法进行了基准测试chunksize。我创建了 1M 行大小的 csv 文件的八个副本，并指定 chunksize=100_000。

其中四个文件是使用您提供的顺序方法读取的，其中四个文件使用mt_gen以下函数，使用四个线程池：

• 单线程 ~ 3.68 s
• 多线程 ~ 1.21 s

但这并不意味着它会改善每个硬件和数据设置的结果。

import time
import threading
from multiprocessing.dummy import Pool  # dummy uses threads


def _load_sim(x = 10e6):
    for _ in range(int(x)):
        x -= 1
    time.sleep(1)


def gen(start, stop):
    for i in range(start, stop):
        _load_sim()
        print(f'{threading.current_thread().name} yielding {i}')
        yield i


def multi_threaded(gens):
    combi_g = mt_gen(gens)
    for item in combi_g:
        print(item)


def mt_gen(gens):
    with Pool(N_WORKERS) as pool:
        while True:
            async_results = [pool.apply_async(next, args=(g,)) for g in gens]
            try:
                results = [r.get() for r in async_results]
            except StopIteration:  # needed for Python 3.7+, PEP 479, bpo-32670
                return
            yield results


if __name__ == '__main__':

    N_GENS = 10
    N_WORKERS = 4
    GEN_LENGTH = 3

    gens = [gen(x * GEN_LENGTH, (x + 1) * GEN_LENGTH) for x in range(N_GENS)]
    multi_threaded(gens)

输出：

Thread-1 yielding 0
Thread-2 yielding 3
Thread-4 yielding 6
Thread-3 yielding 9
Thread-1 yielding 12
Thread-2 yielding 15
Thread-4 yielding 18
Thread-3 yielding 21
Thread-1 yielding 24
Thread-2 yielding 27
[0, 3, 6, 9, 12, 15, 18, 21, 24, 27]
Thread-3 yielding 7
Thread-1 yielding 10
Thread-2 yielding 4
Thread-4 yielding 1
Thread-3 yielding 13
Thread-1 yielding 16
Thread-4 yielding 22
Thread-2 yielding 19
Thread-3 yielding 25
Thread-1 yielding 28
[1, 4, 7, 10, 13, 16, 19, 22, 25, 28]
Thread-1 yielding 8
Thread-4 yielding 2
Thread-3 yielding 11
Thread-2 yielding 5
Thread-1 yielding 14
Thread-4 yielding 17
Thread-3 yielding 20
Thread-2 yielding 23
Thread-1 yielding 26
Thread-4 yielding 29
[2, 5, 8, 11, 14, 17, 20, 23, 26, 29]

Process finished with exit code 0