Python 中 Bash 子程序的平行處理
順序運行子程序可能會影響應用程式的效能。若要同時執行多個 bash 指令，您可以利用 Python 中的執行緒和子程序模組。
直接使用子程序
雖然執行緒對於平行處理似乎是必要的，但事實並非如此必需的。您可以使用subprocess.Popen 函數並行啟動進程：
<code class="python">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 commands in parallel
processes = [Popen(cmd, shell=True) for cmd in commands]
# Perform other tasks while processes run
# Wait for completion
for p in processes:
p.wait()</code>限制並發子進程
要限制並發進程的數量，請考慮使用多處理.dummy>
要限制並發進程的數量，請考慮使用多處理.dummy .Pool 模組，使用執行緒模擬多重處理：<code class="python">from functools import partial
from multiprocessing.dummy import Pool
from subprocess import call
pool = Pool(2) # Limit to two concurrent commands
# Iterate over commands and return codes
for i, returncode in enumerate(pool.imap(partial(call, shell=True), commands)):
if returncode != 0:
print("%d command failed: %d" % (i, returncode))</code>無池限制
您也可以在沒有執行緒池的情況下限制並發：<code class="python">from subprocess import Popen
from itertools import islice
max_workers = 2
processes = (Popen(cmd, shell=True) for cmd in commands)
running_processes = list(islice(processes, max_workers)) # Start initial processes
while running_processes:
for i, process in enumerate(running_processes):
if process.poll() is not None: # 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</code>以上是如何在 Python 中同時執行多個 Bash 指令？的詳細內容。更多資訊請關注PHP中文網其他相關文章！
