pipe large amount of data to stdin while using subprocess.Popen

Your code deadlocks as soon as cat's stdout OS pipe buffer is full. If you use stdout=PIPE; you have to consume it in time otherwise the deadlock as in your case may happen.

If you don't need the output while the process is running; you could redirect it to a temporary file:

#!/usr/bin/env python3
import subprocess
import tempfile

with tempfile.TemporaryFile('r+') as output_file:
    with subprocess.Popen(['cat'],
                          stdin=subprocess.PIPE,
                          stdout=output_file,
                          universal_newlines=True) as process:
        for i in range(100000):
            print(i, file=process.stdin)
    output_file.seek(0)  # rewind (and sync with the disk)
    print(output_file.readline(), end='')  # get  the first line of the output

If the input/output are small (fit in memory); you could pass the input all at once and get the output all at once using .communicate() that reads/writes concurrently for you:

#!/usr/bin/env python3
import subprocess

cp = subprocess.run(['cat'], input='\n'.join(['%d' % i for i in range(100000)]),
                    stdout=subprocess.PIPE, universal_newlines=True)
print(cp.stdout.splitlines()[-1]) # print the last line

To read/write concurrently manually, you could use threads, asyncio, fcntl, etc. @Jed provided a simple thread-based solution. Here's asyncio-based solution:

#!/usr/bin/env python3
import asyncio
import sys
from subprocess import PIPE

async def pump_input(writer):
     try:
         for i in range(100000):
             writer.write(b'%d\n' % i)
             await writer.drain()
     finally:
         writer.close()

async def run():
    # start child process
    # NOTE: universal_newlines parameter is not supported
    process = await asyncio.create_subprocess_exec('cat', stdin=PIPE, stdout=PIPE)
    asyncio.ensure_future(pump_input(process.stdin)) # write input
    async for line in process.stdout: # consume output
        print(int(line)**2) # print squares
    return await process.wait()  # wait for the child process to exit


if sys.platform.startswith('win'):
    loop = asyncio.ProactorEventLoop() # for subprocess' pipes on Windows
    asyncio.set_event_loop(loop)
else:
    loop = asyncio.get_event_loop()
loop.run_until_complete(run())
loop.close()

On Unix, you could use fcntl-based solution:

#!/usr/bin/env python3
import sys
from fcntl import fcntl, F_GETFL, F_SETFL
from os import O_NONBLOCK
from shutil import copyfileobj
from subprocess import Popen, PIPE, _PIPE_BUF as PIPE_BUF

def make_blocking(pipe, blocking=True):
    fd = pipe.fileno()
    if not blocking:
        fcntl(fd, F_SETFL, fcntl(fd, F_GETFL) | O_NONBLOCK) # set O_NONBLOCK
    else:
        fcntl(fd, F_SETFL, fcntl(fd, F_GETFL) & ~O_NONBLOCK) # clear it


with Popen(['cat'], stdin=PIPE, stdout=PIPE) as process:
    make_blocking(process.stdout, blocking=False)
    with process.stdin:
        for i in range(100000):
            #NOTE: the mode is block-buffered (default) and therefore
            # `cat` won't see it immidiately
            process.stdin.write(b'%d\n' % i)
            # a deadblock may happen here with a *blocking* pipe
            output = process.stdout.read(PIPE_BUF)
            if output is not None:
                sys.stdout.buffer.write(output)
    # read the rest
    make_blocking(process.stdout)
    copyfileobj(process.stdout, sys.stdout.buffer)

Here's something I used to load 6G mysql dump file loads via subprocess. Stay away from shell=True. Not secure and start out of process wasting resources.

import subprocess

fhandle = None

cmd = [mysql_path,
      "-u", mysql_user, "-p" + mysql_pass],
      "-h", host, database]

fhandle = open(dump_file, 'r')
p = subprocess.Popen(cmd, stdin=fhandle, stdout=subprocess.PIPE, stderr=subprocess.PIPE)

(stdout,stderr) = p.communicate()

fhandle.close()

If you want a pure Python solution, you need to put either the reader or the writer in a separate thread. The threading package is a lightweight way to do this, with convenient access to common objects and no messy forking.

import subprocess
import threading
import sys

proc = subprocess.Popen(['cat','-'],
                        stdin=subprocess.PIPE,
                        stdout=subprocess.PIPE,
                        )
def writer():
    for i in range(100000):
        proc.stdin.write(b'%d\n' % i)
    proc.stdin.close()
thread = threading.Thread(target=writer)
thread.start()
for line in proc.stdout:
    sys.stdout.write(line.decode())
thread.join()
proc.wait()

It might be neat to see the subprocess module modernized to support streams and coroutines, which would allow pipelines that mix Python pieces and shell pieces to be constructed more elegantly.

If you don't want to keep all the data in memory, you have to use select. E.g. something like:

import subprocess
from select import select
import os

proc = subprocess.Popen(['cat'], stdin=subprocess.PIPE, stdout=subprocess.PIPE)

i = 0;
while True:
    rlist, wlist, xlist = [proc.stdout], [], []
    if i < 100000:
        wlist.append(proc.stdin)
    rlist, wlist, xlist = select(rlist, wlist, xlist)
    if proc.stdout in rlist:
        out = os.read(proc.stdout.fileno(), 10)
        print out,
        if not out:
            break
    if proc.stdin in wlist:
        proc.stdin.write('%d\n' % i)
        i += 1
        if i >= 100000:
            proc.stdin.close()