python中使用subprocess库控制最大并发任务数量进行并行执行任务

import subprocess
from multiprocessing import Pool

def execute_command(command):
    process = subprocess.Popen(command, shell=True)
    process.communicate()

def run_commands(cmd_lst, max_concurrency):
    pool = Pool(processes=max_concurrency)
    pool.map(execute_command, cmd_lst)
    pool.close()
    pool.join()

# 示例使用：
commands = ["echo Hello", "dir", "ping www.google.com", "ipconfig"]
max_concurrency = 2

run_commands(commands, max_concurrency)

在上面的示例中，execute_command函数用于执行给定的命令。run_commands函数利用multiprocessing.Pool来实现并发执行，其中max_concurrency参数控制最大并发数。cmd_lst是包含所有要执行的命令的列表。