python - 如何使用 Python 为不同的前缀同时运行 AWS S3 sync 命令

Question

我正在尝试编写一个 python 脚本，它使用子进程模块将文件从一个 s3 存储桶复制到另一个存储桶。但是，为了提高性能，我尝试并行运行具有不同前缀的单独同步命令。

到目前为止我已经尝试过脚本没有终止，我不确定子进程是否同时运行。

import subprocess

prefix = ['prefix1','prefix2','prefix3']
source_bucket = 's3://source'
dest_bucket = 's3://dest'
commands = []

for p in prefix:
   command = 'aws s3 sync source_bucket' + p + ' dest_bucket'
   commands.append(command)

procs = [subprocess.Popen(i, shell=True, stdout=subprocess.PIPE) for i in commands]

for p in procs:
   p.wait()

有更好的方法吗？感谢您的帮助。

Answer 1

因为您要传入 subprocess.PIPE，不同的进程将在等待输出时阻塞。您需要运行一个单独的进程来与每个 aws 实例进行通信。一种可能性是使用 Python 的多处理:

import subprocess
import multiprocessing

def worker(command, queue):
    # Don't use shell here, we can avoid the overhead
    proc = subprocess.Popen(command, stdout=subprocess.PIPE, bufsize=1, universal_newlines=True)
    # Read from the aws command output and send it off the queue as soon
    # as it's available
    for line in proc.stdout:
        queue.put(line.rstrip("\r\n"))
    
    # Notify the listener that we're done
    queue.put(None)


def main():
    # Move all work to a function so it's multiprocessing safe, see
    # https://docs.python.org/3/library/multiprocessing.html#multiprocessing-programming
    # Note: Adding trailing slash so "source_bucket" + "prefix" is a valid S3 URI
    prefixes = ['prefix1/', 'prefix2/', 'prefix3/']
    source_bucket = 's3://source/'
    dest_bucket = 's3://dest/'

    # Create a queue to gather final messages from each worker
    queue = multiprocessing.Queue()
    procs = []

    for p in prefixes:
        # Pass in --no-progress so the progress messages aren't shown
        # displaying those messages is complicated, and requires quite a bit
        # of work to make sure they don't interfer with each other
        # Correct the command syntax here to use all the variables
        # Need to pass in the prefix to the dest URI as well so the same structure is
        # maintained
        # Use a argv style call here so we can avoid bringing the shell into this
        command = ['aws', 's3', 'sync', '--no-progress', source_bucket + p, dest_bucket + p]
        # Hand off the work to a worker to read from the pipe to prevent each
        # spawned aws instance from blocking
        proc = multiprocessing.Process(target=worker, args=(command, queue))
        proc.start()
        procs.append(proc)

    # Read from the Queue to show the output
    left = len(procs)
    while left > 0:
        msg = queue.get()
        if msg is None:
            # This means a worker is done
            left -= 1
        else:
            # Just print out the output, doing it in one process to prevent any
            # collision possibilities
            print(msg)
    
    # Clean up
    for proc in procs:
        proc.join()

if __name__ == "__main__":
    main()