I'm using a python script as a driver for a hydrodynamics code. When it comes time to run the simulation, I use subprocess.Popen to run the code, collect the output from stdout and stderr into a subprocess.PIPE --- then I can print (and save to a log-file) the output information, and check for any errors. The problem is, I have no idea how the code is progressing. If I run it directly from the command line, it gives me output about what iteration its at, what time, what the next time-step is, etc.

是否有一种方法既存储输出(用于日志记录和错误检查),又产生实时流输出?

我的代码的相关部分:

ret_val = subprocess.Popen( run_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True )
output, errors = ret_val.communicate()
log_file.write(output)
print output
if( ret_val.returncode ):
    print "RUN failed\n\n%s\n\n" % (errors)
    success = False

if( errors ): log_file.write("\n\n%s\n\n" % errors)

最初,我将run_command通过tee输送,以便将副本直接发送到日志文件,流仍然直接输出到终端——但这样我就不能存储任何错误(据我所知)。


目前我的临时解决方案是:

ret_val = subprocess.Popen( run_command, stdout=log_file, stderr=subprocess.PIPE, shell=True )
while not ret_val.poll():
    log_file.flush()

然后,在另一个终端上运行tail -f log.txt (s.t. log_file = 'log.txt')。


当前回答

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)

其他回答

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。

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



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。

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()

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()