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。

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。

看起来行缓冲输出对您来说是可行的，在这种情况下，下面的代码可能适合您。(注意:它未经测试。)这只会实时给出子进程的标准输出。如果您希望实时同时拥有stderr和stdout，则必须使用select执行更复杂的操作。

proc = subprocess.Popen(run_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)
while proc.poll() is None:
    line = proc.stdout.readline()
    print line
    log_file.write(line + '\n')
# Might still be data on stdout at this point.  Grab any
# remainder.
for line in proc.stdout.read().split('\n'):
    print line
    log_file.write(line + '\n')
# Do whatever you want with proc.stderr here...

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)

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

解决方案1:实时并发记录stdout和stderr

一种简单的解决方案，可以将stdout和stderr同时记录，逐行实时地记录到日志文件中。

import subprocess as sp
from concurrent.futures import ThreadPoolExecutor


def log_popen_pipe(p, stdfile):

    with open("mylog.txt", "w") as f:

        while p.poll() is None:
            f.write(stdfile.readline())
            f.flush()

        # Write the rest from the buffer
        f.write(stdfile.read())


with sp.Popen(["ls"], stdout=sp.PIPE, stderr=sp.PIPE, text=True) as p:

    with ThreadPoolExecutor(2) as pool:
        r1 = pool.submit(log_popen_pipe, p, p.stdout)
        r2 = pool.submit(log_popen_pipe, p, p.stderr)
        r1.result()
        r2.result()

解决方案2:函数read_popen_pipes()，它允许同时实时遍历两个管道(stdout/stderr)

import subprocess as sp
from queue import Queue, Empty
from concurrent.futures import ThreadPoolExecutor


def enqueue_output(file, queue):
    for line in iter(file.readline, ''):
        queue.put(line)
    file.close()


def read_popen_pipes(p):

    with ThreadPoolExecutor(2) as pool:
        q_stdout, q_stderr = Queue(), Queue()

        pool.submit(enqueue_output, p.stdout, q_stdout)
        pool.submit(enqueue_output, p.stderr, q_stderr)

        while True:

            if p.poll() is not None and q_stdout.empty() and q_stderr.empty():
                break

            out_line = err_line = ''

            try:
                out_line = q_stdout.get_nowait()
                err_line = q_stderr.get_nowait()
            except Empty:
                pass

            yield (out_line, err_line)

# The function in use:

with sp.Popen(["ls"], stdout=sp.PIPE, stderr=sp.PIPE, text=True) as p:

    for out_line, err_line in read_popen_pipes(p):
        print(out_line, end='')
        print(err_line, end='')

    p.poll()