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

我发现如何以流的方式读取子进程的输出(同时也在一个变量中捕获它)在Python中(对于多个输出流，即stdout和stderr)是通过传递子进程一个命名的临时文件来写入，然后在单独的读取句柄中打开相同的临时文件。

注意:这是针对Python 3的

    stdout_write = tempfile.NamedTemporaryFile()
    stdout_read = io.open(stdout_write.name, "r")
    stderr_write = tempfile.NamedTemporaryFile()
    stderr_read = io.open(stderr_write.name, "r")

    stdout_captured = ""
    stderr_captured = ""

    proc = subprocess.Popen(["command"], stdout=stdout_write, stderr=stderr_write)
    while True:
        proc_done: bool = cli_process.poll() is not None

        while True:
            content = stdout_read.read(1024)
            sys.stdout.write(content)
            stdout_captured += content
            if len(content) < 1024:
                break

        while True:
            content = stderr_read.read(1024)
            sys.stderr.write(content)
            stdout_captured += content
            if len(content) < 1024:
                break

        if proc_done:
            break

        time.sleep(0.1)

    stdout_write.close()
    stdout_read.close()
    stderr_write.close()
    stderr_read.close()

但是，如果您不需要捕获输出，那么您可以简单地传递sys。Stdout和sys。stderr流从你的Python脚本到被调用的子进程，正如xaav在他的回答中建议的那样:

subprocess.Popen(["command"], stdout=sys.stdout, stderr=sys.stderr)

为什么不直接将stdout设置为sys.stdout?如果你也需要输出到日志，那么你可以简单地重写f的write方法。

import sys
import subprocess

class SuperFile(open.__class__):

    def write(self, data):
        sys.stdout.write(data)
        super(SuperFile, self).write(data)

f = SuperFile("log.txt","w+")       
process = subprocess.Popen(command, stdout=f, stderr=f)

python的解决方案对我都不起作用。 原来proc.stdout.read()或类似的可能永远阻塞。

因此，我这样使用tee:

subprocess.run('./my_long_running_binary 2>&1 | tee -a my_log_file.txt && exit ${PIPESTATUS}', shell=True, check=True, executable='/bin/bash')

如果你已经在使用shell=True，这个解决方案很方便。

${PIPESTATUS}捕获整个命令链的成功状态(仅在Bash中可用)。 如果我省略&&退出${PIPESTATUS}，那么这将总是返回零，因为tee从未失败过。

Unbuffer对于立即将每一行打印到终端可能是必要的，而不是等待太长时间，直到“管道缓冲区”被填满。 然而，unbuffer吞下了assert的退出状态(SIG Abort)…

2>&1也记录文件的标准错误。

一个好的但“重量级”的解决方案是使用Twisted -见底部。

如果你愿意只使用stdout，那么下面这些代码应该可以工作:

import subprocess
import sys
popenobj = subprocess.Popen(["ls", "-Rl"], stdout=subprocess.PIPE)
while not popenobj.poll():
   stdoutdata = popenobj.stdout.readline()
   if stdoutdata:
      sys.stdout.write(stdoutdata)
   else:
      break
print "Return code", popenobj.returncode

(如果你使用read()，它会尝试读取整个“文件”，这是没有用的，我们真正可以在这里使用的是读取管道中当前所有数据的东西)

你也可以尝试用线程来解决这个问题，例如:

import subprocess
import sys
import threading

popenobj = subprocess.Popen("ls", stdout=subprocess.PIPE, shell=True)

def stdoutprocess(o):
   while True:
      stdoutdata = o.stdout.readline()
      if stdoutdata:
         sys.stdout.write(stdoutdata)
      else:
         break

t = threading.Thread(target=stdoutprocess, args=(popenobj,))
t.start()
popenobj.wait()
t.join()
print "Return code", popenobj.returncode

现在我们可以通过两个线程来添加stderr。

但是请注意，子进程文档不鼓励直接使用这些文件，并建议使用communication()(主要涉及死锁，我认为这不是上面的问题)，解决方案有点笨，所以看起来子进程模块不太适合这项工作(也请参阅:http://www.python.org/dev/peps/pep-3145/)，我们需要看看其他东西。

一个更复杂的解决方案是使用Twisted，如下所示:https://twistedmatrix.com/documents/11.1.0/core/howto/process.html

Twisted的方法是使用reactor.spawnprocess()创建进程，并提供一个ProcessProtocol，然后异步处理输出。Twisted示例Python代码在这里:https://twistedmatrix.com/documents/11.1.0/core/howto/listings/process/process.py

Here is a class which I'm using in one of my projects. It redirects output of a subprocess to the log. At first I tried simply overwriting the write-method but that doesn't work as the subprocess will never call it (redirection happens on filedescriptor level). So I'm using my own pipe, similar to how it's done in the subprocess-module. This has the advantage of encapsulating all logging/printing logic in the adapter and you can simply pass instances of the logger to Popen: subprocess.Popen("/path/to/binary", stderr = LogAdapter("foo"))

class LogAdapter(threading.Thread):

    def __init__(self, logname, level = logging.INFO):
        super().__init__()
        self.log = logging.getLogger(logname)
        self.readpipe, self.writepipe = os.pipe()

        logFunctions = {
            logging.DEBUG: self.log.debug,
            logging.INFO: self.log.info,
            logging.WARN: self.log.warn,
            logging.ERROR: self.log.warn,
        }

        try:
            self.logFunction = logFunctions[level]
        except KeyError:
            self.logFunction = self.log.info

    def fileno(self):
        #when fileno is called this indicates the subprocess is about to fork => start thread
        self.start()
        return self.writepipe

    def finished(self):
       """If the write-filedescriptor is not closed this thread will
       prevent the whole program from exiting. You can use this method
       to clean up after the subprocess has terminated."""
       os.close(self.writepipe)

    def run(self):
        inputFile = os.fdopen(self.readpipe)

        while True:
            line = inputFile.readline()

            if len(line) == 0:
                #no new data was added
                break

            self.logFunction(line.strip())

如果您不需要日志记录，而只是想使用print()，显然可以删除大部分代码并使类更短。你也可以通过__enter__和__exit__方法来扩展它，并在__exit__中调用finished，这样你就可以很容易地将它用作上下文。