我尝试过的所有上述解决方案都无法分离stderr和stdout输出(多个管道)，或者当操作系统管道缓冲区已满时永远阻塞，这发生在你运行输出太快的命令时(在python poll() subprocess手册上对此有警告)。我发现唯一可靠的方法是通过选择，但这是一个posix-only解决方案:

import subprocess
import sys
import os
import select
# returns command exit status, stdout text, stderr text
# rtoutput: show realtime output while running
def run_script(cmd,rtoutput=0):
    p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
    poller = select.poll()
    poller.register(p.stdout, select.POLLIN)
    poller.register(p.stderr, select.POLLIN)

    coutput=''
    cerror=''
    fdhup={}
    fdhup[p.stdout.fileno()]=0
    fdhup[p.stderr.fileno()]=0
    while sum(fdhup.values()) < len(fdhup):
        try:
            r = poller.poll(1)
        except select.error, err:
            if err.args[0] != EINTR:
                raise
            r=[]
        for fd, flags in r:
            if flags & (select.POLLIN | select.POLLPRI):
                c = os.read(fd, 1024)
                if rtoutput:
                    sys.stdout.write(c)
                    sys.stdout.flush()
                if fd == p.stderr.fileno():
                    cerror+=c
                else:
                    coutput+=c
            else:
                fdhup[fd]=1
    return p.poll(), coutput.strip(), cerror.strip()

我认为subprocess. communication方法有点误导人:它实际上填充了您在subprocess.Popen中指定的stdout和stderr。

然而，从子进程中读取。可以提供给子流程的PIPE。Popen的stdout和stderr参数最终会填满OS管道缓冲区并导致应用程序死锁(特别是当你有多个必须使用subprocess的进程/线程时)。

我建议的解决方案是提供带有文件的标准输出和标准输出-并读取文件的内容，而不是从死锁PIPE中读取。这些文件可以是tempfile.NamedTemporaryFile()——当subprocess. communication写入这些文件时，也可以访问该文件进行读取。

下面是一个示例用法:

try:
    with ProcessRunner(
        ("python", "task.py"), env=os.environ.copy(), seconds_to_wait=0.01
    ) as process_runner:
        for out in process_runner:
            print(out)
except ProcessError as e:
    print(e.error_message)
    raise

这是源代码，准备使用尽可能多的评论，因为我可以提供解释它的功能:

如果您正在使用python 2，请确保首先从pypi安装最新版本的subprocess32包。

import os
import sys
import threading
import time
import tempfile
import logging

if os.name == 'posix' and sys.version_info[0] < 3:
    # Support python 2
    import subprocess32 as subprocess
else:
    # Get latest and greatest from python 3
    import subprocess

logger = logging.getLogger(__name__)


class ProcessError(Exception):
    """Base exception for errors related to running the process"""


class ProcessTimeout(ProcessError):
    """Error that will be raised when the process execution will exceed a timeout"""


class ProcessRunner(object):
    def __init__(self, args, env=None, timeout=None, bufsize=-1, seconds_to_wait=0.25, **kwargs):
        """
        Constructor facade to subprocess.Popen that receives parameters which are more specifically required for the
        Process Runner. This is a class that should be used as a context manager - and that provides an iterator
        for reading captured output from subprocess.communicate in near realtime.

        Example usage:


        try:
            with ProcessRunner(('python', task_file_path), env=os.environ.copy(), seconds_to_wait=0.01) as process_runner:
                for out in process_runner:
                    print(out)
        except ProcessError as e:
            print(e.error_message)
            raise

        :param args: same as subprocess.Popen
        :param env: same as subprocess.Popen
        :param timeout: same as subprocess.communicate
        :param bufsize: same as subprocess.Popen
        :param seconds_to_wait: time to wait between each readline from the temporary file
        :param kwargs: same as subprocess.Popen
        """
        self._seconds_to_wait = seconds_to_wait
        self._process_has_timed_out = False
        self._timeout = timeout
        self._process_done = False
        self._std_file_handle = tempfile.NamedTemporaryFile()
        self._process = subprocess.Popen(args, env=env, bufsize=bufsize,
                                         stdout=self._std_file_handle, stderr=self._std_file_handle, **kwargs)
        self._thread = threading.Thread(target=self._run_process)
        self._thread.daemon = True

    def __enter__(self):
        self._thread.start()
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        self._thread.join()
        self._std_file_handle.close()

    def __iter__(self):
        # read all output from stdout file that subprocess.communicate fills
        with open(self._std_file_handle.name, 'r') as stdout:
            # while process is alive, keep reading data
            while not self._process_done:
                out = stdout.readline()
                out_without_trailing_whitespaces = out.rstrip()
                if out_without_trailing_whitespaces:
                    # yield stdout data without trailing \n
                    yield out_without_trailing_whitespaces
                else:
                    # if there is nothing to read, then please wait a tiny little bit
                    time.sleep(self._seconds_to_wait)

            # this is a hack: terraform seems to write to buffer after process has finished
            out = stdout.read()
            if out:
                yield out

        if self._process_has_timed_out:
            raise ProcessTimeout('Process has timed out')

        if self._process.returncode != 0:
            raise ProcessError('Process has failed')

    def _run_process(self):
        try:
            # Start gathering information (stdout and stderr) from the opened process
            self._process.communicate(timeout=self._timeout)
            # Graceful termination of the opened process
            self._process.terminate()
        except subprocess.TimeoutExpired:
            self._process_has_timed_out = True
            # Force termination of the opened process
            self._process.kill()

        self._process_done = True

    @property
    def return_code(self):
        return self._process.returncode

如果您能够使用第三方库，您可能能够使用像sarge这样的东西(披露:我是它的维护者)。这个库允许非阻塞地访问子流程的输出流——它是分层在子流程模块之上的。

Python 3的TLDR:

import subprocess
import sys

with open("test.log", "wb") as f:
    process = subprocess.Popen(your_command, stdout=subprocess.PIPE)
    for c in iter(lambda: process.stdout.read(1), b""):
        sys.stdout.buffer.write(c)
        f.buffer.write(c)

你有两种方法来做到这一点，要么从read或readline函数创建一个迭代器，然后做:

import subprocess
import sys

# replace "w" with "wb" for Python 3
with open("test.log", "w") as f:
    process = subprocess.Popen(your_command, stdout=subprocess.PIPE)
    # replace "" with b'' for Python 3
    for c in iter(lambda: process.stdout.read(1), ""):
        sys.stdout.write(c)
        f.write(c)

or

import subprocess
import sys

# replace "w" with "wb" for Python 3
with open("test.log", "w") as f:
    process = subprocess.Popen(your_command, stdout=subprocess.PIPE)
    # replace "" with b"" for Python 3
    for line in iter(process.stdout.readline, ""):
        sys.stdout.write(line)
        f.write(line)

或者您可以创建一个读取器和一个写入器文件。将写入器传递给Popen并从读取器读取

import io
import time
import subprocess
import sys

filename = "test.log"
with io.open(filename, "wb") as writer, io.open(filename, "rb", 1) as reader:
    process = subprocess.Popen(command, stdout=writer)
    while process.poll() is None:
        sys.stdout.write(reader.read())
        time.sleep(0.5)
    # Read the remaining
    sys.stdout.write(reader.read())

通过这种方式，您可以将数据写入test.log和标准输出中。

文件方法的唯一优点是代码不会阻塞。因此，您可以在此期间做任何您想做的事情，并以无阻塞的方式随时从阅读器读取。当您使用PIPE时，read和readline函数将阻塞，直到分别将一个字符写入管道或将一行字符写入管道。

遇到了同样的问题，并使用process.sdtout.read1()得出了一个简单而干净的解决方案，它完全满足了我在python3中的需求。

下面是一个使用ping命令的演示(需要网络连接):

from subprocess import Popen, PIPE

cmd = "ping 8.8.8.8"
proc = Popen([cmd], shell=True, stdout=PIPE)
while True:
    print(proc.stdout.read1())

当ping命令实时报告其数据时，大约每秒钟就会在python控制台中打印一行新行。

除了这些答案之外，一个简单的方法也可以如下:

process = subprocess.Popen(your_command, stdout=subprocess.PIPE)

while process.stdout.readable():
    line = process.stdout.readline()

    if not line:
        break

    print(line.strip())

循环可读流，只要它是可读的，如果它得到一个空的结果，停止。

这里的关键是，readline()返回一行(结尾是\n)，只要有输出，如果确实在末尾，则返回空行。

希望这能帮助到一些人。