你不需要线程来并行运行子流程：

from subprocess import Popen

commands = [
    'date; ls -l; sleep 1; date',
    'date; sleep 5; date',
    'date; df -h; sleep 3; date',
    'date; hostname; sleep 2; date',
    'date; uname -a; date',
]
# run in parallel
processes = [Popen(cmd, shell=True) for cmd in commands]
# do other things here..
# wait for completion
for p in processes: p.wait()

为了限制并发命令的数量，可以使用multiprocessing.dummy.Pool线程并提供与multiprocessing.Pool使用进程相同的接口：

from functools import partial
from multiprocessing.dummy import Pool
from subprocess import call

pool = Pool(2) # two concurrent commands at a time
for i, returncode in enumerate(pool.imap(partial(call, shell=True), commands)):
    if returncode != 0:
       print("%d command failed: %d" % (i, returncode))

该答案演示了限制并发子进程数的各种技术：它显示了multiprocessing.Pool，concurrent.futures，线程+基于队列的解决方案。

你可以限制并发子进程的数量，而无需使用线程/进程池：

from subprocess import Popen
from itertools import islice

max_workers = 2  # no more than 2 concurrent processes
processes = (Popen(cmd, shell=True) for cmd in commands)
running_processes = list(islice(processes, max_workers))  # start new processes
while running_processes:
    for i, process in enumerate(running_processes):
        if process.poll() is not None:  # the process has finished
            running_processes[i] = next(processes, None)  # start new process
            if running_processes[i] is None: # no new processes
                del running_processes[i]
                break