我使用subprocess模块启动子流程并连接到其输出流(标准输出)。我希望能够对其标准输出执行非阻塞读取。是否有一种方法使.readline非阻塞或在我调用.readline之前检查流上是否有数据?我希望这是可移植的,或者至少可以在Windows和Linux下工作。

下面是我现在怎么做的(如果没有数据可用,它会阻塞在.readline上):

p = subprocess.Popen('myprogram.exe', stdout = subprocess.PIPE)
output_str = p.stdout.readline()

当前回答

下面是我的代码,用于捕获子进程ASAP的每个输出,包括部分行。它同时泵浦,stdout和stderr的顺序几乎是正确的。

在Python 2.7 linux和windows上测试并正确工作。

#!/usr/bin/python
#
# Runner with stdout/stderr catcher
#
from sys import argv
from subprocess import Popen, PIPE
import os, io
from threading import Thread
import Queue
def __main__():
    if (len(argv) > 1) and (argv[-1] == "-sub-"):
        import time, sys
        print "Application runned!"
        time.sleep(2)
        print "Slept 2 second"
        time.sleep(1)
        print "Slept 1 additional second",
        time.sleep(2)
        sys.stderr.write("Stderr output after 5 seconds")
        print "Eol on stdin"
        sys.stderr.write("Eol on stderr\n")
        time.sleep(1)
        print "Wow, we have end of work!",
    else:
        os.environ["PYTHONUNBUFFERED"]="1"
        try:
            p = Popen( argv + ["-sub-"],
                       bufsize=0, # line-buffered
                       stdin=PIPE, stdout=PIPE, stderr=PIPE )
        except WindowsError, W:
            if W.winerror==193:
                p = Popen( argv + ["-sub-"],
                           shell=True, # Try to run via shell
                           bufsize=0, # line-buffered
                           stdin=PIPE, stdout=PIPE, stderr=PIPE )
            else:
                raise
        inp = Queue.Queue()
        sout = io.open(p.stdout.fileno(), 'rb', closefd=False)
        serr = io.open(p.stderr.fileno(), 'rb', closefd=False)
        def Pump(stream, category):
            queue = Queue.Queue()
            def rdr():
                while True:
                    buf = stream.read1(8192)
                    if len(buf)>0:
                        queue.put( buf )
                    else:
                        queue.put( None )
                        return
            def clct():
                active = True
                while active:
                    r = queue.get()
                    try:
                        while True:
                            r1 = queue.get(timeout=0.005)
                            if r1 is None:
                                active = False
                                break
                            else:
                                r += r1
                    except Queue.Empty:
                        pass
                    inp.put( (category, r) )
            for tgt in [rdr, clct]:
                th = Thread(target=tgt)
                th.setDaemon(True)
                th.start()
        Pump(sout, 'stdout')
        Pump(serr, 'stderr')

        while p.poll() is None:
            # App still working
            try:
                chan,line = inp.get(timeout = 1.0)
                if chan=='stdout':
                    print "STDOUT>>", line, "<?<"
                elif chan=='stderr':
                    print " ERROR==", line, "=?="
            except Queue.Empty:
                pass
        print "Finish"

if __name__ == '__main__':
    __main__()

其他回答

我有最初提问者的问题,但不希望调用线程。我将Jesse的解决方案与来自管道的直接read()和我自己的行读取缓冲处理程序混合在一起(然而,我的子进程- ping -总是写入<系统页面大小的整行)。我通过读入一个gobject-registered io watch来避免忙碌的等待。这些天我通常在gobject MainLoop中运行代码以避免线程。

def set_up_ping(ip, w):
    # run the sub-process
    # watch the resultant pipe
    p = subprocess.Popen(['/bin/ping', ip], stdout=subprocess.PIPE)
    # make stdout a non-blocking file
    fl = fcntl.fcntl(p.stdout, fcntl.F_GETFL)
    fcntl.fcntl(p.stdout, fcntl.F_SETFL, fl | os.O_NONBLOCK)
    stdout_gid = gobject.io_add_watch(p.stdout, gobject.IO_IN, w)
    return stdout_gid # for shutting down

观察者是

def watch(f, *other):
    print 'reading',f.read()
    return True

主程序建立一个ping,然后调用gobject邮件循环。

def main():
    set_up_ping('192.168.1.8', watch)
    # discard gid as unused here
    gobject.MainLoop().run()

任何其他工作都附加到gobject中的回调。

You can do this really easily in Twisted. Depending upon your existing code base, this might not be that easy to use, but if you are building a twisted application, then things like this become almost trivial. You create a ProcessProtocol class, and override the outReceived() method. Twisted (depending upon the reactor used) is usually just a big select() loop with callbacks installed to handle data from different file descriptors (often network sockets). So the outReceived() method is simply installing a callback for handling data coming from STDOUT. A simple example demonstrating this behavior is as follows:

from twisted.internet import protocol, reactor

class MyProcessProtocol(protocol.ProcessProtocol):

    def outReceived(self, data):
        print data

proc = MyProcessProtocol()
reactor.spawnProcess(proc, './myprogram', ['./myprogram', 'arg1', 'arg2', 'arg3'])
reactor.run()

Twisted文档在这方面有一些很好的信息。

如果您围绕Twisted构建整个应用程序,它可以与其他进程(本地或远程)进行异步通信,就像这样非常优雅。另一方面,如果您的程序不是构建在Twisted之上,那么这真的不会有多大帮助。希望这能对其他读者有所帮助,即使它不适用于您的特定应用程序。

在现代Python中,情况要好得多。

下面是一个简单的子程序"hello.py":

#!/usr/bin/env python3

while True:
    i = input()
    if i == "quit":
        break
    print(f"hello {i}")

以及一个与之交互的程序:

import asyncio


async def main():
    proc = await asyncio.subprocess.create_subprocess_exec(
        "./hello.py", stdin=asyncio.subprocess.PIPE, stdout=asyncio.subprocess.PIPE
    )
    proc.stdin.write(b"bob\n")
    print(await proc.stdout.read(1024))
    proc.stdin.write(b"alice\n")
    print(await proc.stdout.read(1024))
    proc.stdin.write(b"quit\n")
    await proc.wait()


asyncio.run(main())

打印出来:

b'hello bob\n'
b'hello alice\n'

请注意,实际的模式(几乎所有前面的回答,包括这里和相关的问题)是将子进程的stdout文件描述符设置为非阻塞,然后在某种选择循环中轮询它。当然,现在这个循环是由asyncio提供的。

试试asyncproc模块。例如:

import os
from asyncproc import Process
myProc = Process("myprogram.app")

while True:
    # check to see if process has ended
    poll = myProc.wait(os.WNOHANG)
    if poll != None:
        break
    # print any new output
    out = myProc.read()
    if out != "":
        print out

该模块负责S.Lott建议的所有线程。

该解决方案使用select模块从IO流中“读取任何可用数据”。这个函数一开始会阻塞,直到数据可用,但随后只读取可用的数据,不再进一步阻塞。

鉴于它使用了select模块,这只适用于Unix。

该代码完全符合pep8。

import select


def read_available(input_stream, max_bytes=None):
    """
    Blocks until any data is available, then all available data is then read and returned.
    This function returns an empty string when end of stream is reached.

    Args:
        input_stream: The stream to read from.
        max_bytes (int|None): The maximum number of bytes to read. This function may return fewer bytes than this.

    Returns:
        str
    """
    # Prepare local variables
    input_streams = [input_stream]
    empty_list = []
    read_buffer = ""

    # Initially block for input using 'select'
    if len(select.select(input_streams, empty_list, empty_list)[0]) > 0:

        # Poll read-readiness using 'select'
        def select_func():
            return len(select.select(input_streams, empty_list, empty_list, 0)[0]) > 0

        # Create while function based on parameters
        if max_bytes is not None:
            def while_func():
                return (len(read_buffer) < max_bytes) and select_func()
        else:
            while_func = select_func

        while True:
            # Read single byte at a time
            read_data = input_stream.read(1)
            if len(read_data) == 0:
                # End of stream
                break
            # Append byte to string buffer
            read_buffer += read_data
            # Check if more data is available
            if not while_func():
                break

    # Return read buffer
    return read_buffer