How can you achieve concurrent execution of \'cat | zgrep\' commands in Python while efficiently managing individual output for further processing?

Python: Concurrent Execution of 'cat' Subprocesses

In parallel processing scenarios, sequential execution can be a bottleneck. To circumvent this issue, explore how to execute multiple 'cat | zgrep' commands simultaneously in Python while retaining the individual output for further processing.

Concurrency with subprocess Module

For concurrent subprocess execution without resorting to multiprocessing or threading, consider the following approach:

<code class="python">#!/usr/bin/env python
from subprocess import Popen

# Initialize processes
processes = [Popen("echo {i:d}; sleep 2; echo {i:d}".format(i=i), shell=True) for i in range(5)]

# Gather execution statuses
exitcodes = [p.wait() for p in processes]</code>

This code launches five shell commands in parallel without requiring '&' or explicit '.wait()' calls.

Concurrency with Thread Pool

For concurrent subprocess output collection, threads can be employed:

<code class="python">#!/usr/bin/env python
from multiprocessing.dummy import Pool
from subprocess import Popen, PIPE, STDOUT

# Create processes
processes = [Popen("echo {i:d}; sleep 2; echo {i:d}".format(i=i), shell=True,
                   stdin=PIPE, stdout=PIPE, stderr=STDOUT, close_fds=True)
             for i in range(5)]

# Collect output
def get_lines(process):
    return process.communicate()[0].splitlines()

outputs = Pool(len(processes)).map(get_lines, processes)</code>

This code gathers subprocess output in parallel using a thread pool.

Asynchronous Output Collection (Python 3.8 )

In Python 3.8 , asyncio can be utilized for concurrent output collection in a single thread:

<code class="python">#!/usr/bin/env python3
import asyncio
import sys
from subprocess import PIPE, STDOUT


async def get_lines(shell_command):
    p = await asyncio.create_subprocess_shell(
        shell_command, stdin=PIPE, stdout=PIPE, stderr=STDOUT
    )
    return (await p.communicate())[0].splitlines()


async def main():
    # Concurrent command execution
    coros = [
        get_lines(
            f'"{sys.executable}" -c "print({i:d}); import time; time.sleep({i:d})"'
        )
        for i in range(5)
    ]
    print(await asyncio.gather(*coros))


if __name__ == "__main__":
    asyncio.run(main())</code>

This code executes the subprocesses and collects their output asynchronously, eliminating the need for multiprocessing or threading.

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