如何使用线程和子进程模块生成并行bash进程?当我在第一个答案开始线程时:How to use threading in Python?,bash进程按顺序而不是并行运行。
答案 0 :(得分:55)
您不需要线程并行运行子进程:
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()
要限制并发命令的数量,可以使用multiprocessing.dummy.Pool
使用线程并提供与使用进程的multiprocessing.Pool
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))
This answer demonstrates various techniques to limit number of concurrent subprocesses:它显示了multiprocessing.Pool,concurrent.futures,threading +基于队列的解决方案。
您可以在不使用线程/进程池的情况下限制并发子进程的数量:
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
在Unix上,你可以避免忙碌循环和block on os.waitpid(-1, 0)
, to wait for any child process to exit。
答案 1 :(得分:6)
一个简单的线程示例:
import threading
import Queue
import commands
import time
# thread class to run a command
class ExampleThread(threading.Thread):
def __init__(self, cmd, queue):
threading.Thread.__init__(self)
self.cmd = cmd
self.queue = queue
def run(self):
# execute the command, queue the result
(status, output) = commands.getstatusoutput(self.cmd)
self.queue.put((self.cmd, output, status))
# queue where results are placed
result_queue = Queue.Queue()
# define the commands to be run in parallel, run them
cmds = ['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',
]
for cmd in cmds:
thread = ExampleThread(cmd, result_queue)
thread.start()
# print results as we get them
while threading.active_count() > 1 or not result_queue.empty():
while not result_queue.empty():
(cmd, output, status) = result_queue.get()
print('%s:' % cmd)
print(output)
print('='*60)
time.sleep(1)
请注意,有更好的方法可以做到这一点,但这并不复杂。该示例为每个命令使用一个线程。当您想要执行诸如使用有限数量的线程来处理未知数量的命令之类的事情时,复杂性开始蔓延。一旦掌握了线程基础知识,那些更高级的技术似乎并不太复杂。一旦掌握了这些技术,多处理就会变得更容易。
答案 2 :(得分:0)
这是因为它应该这样做,你要做的事情不是多线程,而是多处理看到这个stack page