I am bulk recompiling edits to a c-like language which uses an external compiler.exe. The compiler takes the file paths as arguments and does the processing, nothing needs to be synchronized simply speed up the de/compilation of multiple files by using workers, when a worker finishes it should be recycled and the executable should be started again with the next set of arguments.

I was able to create some working code, but I believe there is a much more pythonic way to do this but I cant seem to find info on the right high level functions to Bulk start, await, and restart external processes with n workers while a generator is not exhausted.

I created a simple C# console app to simulate the compiler along with some fake files to be processed by the fake compiler. Can be downloaded here.

To run a test, create a folder to work out of, place the fake_files folder and the python script into your working folder, then run the script.

namespace ConsoleApp3
    class Program
        static void Main(string[] args)
            String InFile = args[0];
            String OutFile = args[1];
            Console.WriteLine($"Compiling file: {InFile}");
            Int32 ProcessingTime = new Random().Next(3, 25);
            Thread.Sleep(ProcessingTime * 1000);
            Console.WriteLine($"Compiling complete! Outfile: {OutFile}");
import asyncio
import functools
import logging
import string
import subprocess
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path
from typing import Generator

# create logger
log = logging.getLogger(__name__)

fh = logging.FileHandler('debug.log', mode='w')

ch = logging.StreamHandler()

formatter = logging.Formatter('[%(asctime)s][%(name)s][%(levelname)s]: %(message)s')



SCRIPT_COMP_EXE = './fake_files/fake_compiler.exe'

async def signal_end_of_generator(complete_event: asyncio.Future):
    """This function waits for the tasks that are still compiling
    and is awaiting on the subprocess.run inside the executor.
    I did not see a built-in async way to do this, only sync with shutdown"""
    for t in asyncio.all_tasks():
        if t.get_coro().__name__ == 'recompile_script_async':
            await t


async def recompile_script_async(file_generator: Generator,
                                 loop: asyncio.AbstractEventLoop,
                                 pool: ThreadPoolExecutor,
                                 complete_event: asyncio.Future,
                                 stop_iteration: asyncio.Event,
                                 worker: int):

    # Check file iterator
        fqp = next(file_generator)
    except StopIteration:
        if not stop_iteration.is_set():
    log.debug(f'Worker {worker}, has started.')

    # Compile
    outfile = Path(str(fqp).removesuffix('.c'))

    result = await loop.run_in_executor(pool, functools.partial(
        [SCRIPT_COMP_EXE, '-c', fqp, outfile],
        capture_output=True, text=False

    # Recycle Worker
    log.debug(f'Worker {worker}, has completed.')
    if not stop_iteration.is_set():
        log.debug(f'Recycling Worker {worker}.')
            recompile_script_async(file_generator, loop, pool, complete_event, stop_iteration, worker))

def recompile_scripts_parallel(root, max_workers=4):
    log.info('Recompiling Scripts in parallel...')
    loop = asyncio.new_event_loop()
    with ThreadPoolExecutor(max_workers=max_workers) as pool:
        stop_iteration = asyncio.Event()
        complete_event = loop.create_future()
        file_generator = Path(root).rglob('*.bin.c')

        for worker in range(0, max_workers):
            log.debug(f'Starting parallel worker: {worker}')
                recompile_script_async(file_generator, loop, pool, complete_event, stop_iteration, worker))


if __name__ == '__main__':

For example, the way that I use task recursion that starts a new task, and the way I safely await the processes once the generator is exhausted and the low level loop access just seems like a lot of low level code to achieve this.

  • \$\begingroup\$ Have you considered multiprocessing instead of asyncio? \$\endgroup\$ Oct 15, 2022 at 6:47
  • \$\begingroup\$ The main reason I avoided ProcessPoolExecutor and multiprocessing was because it forked the entire python script and starts a new python interpreter. I am needing to await on the compiling process of external tools then continue one instance of the python script. \$\endgroup\$
    – 0xKate
    Oct 15, 2022 at 6:55
  • \$\begingroup\$ The other reason is most of the stuff in multiprocessing seems to be about message queues and synchronization of the multiple processes. I don't need the processes synchronized or to share any data, just need another instance to start up with the next set of data whenever one finishes. Using a set number of worker tasks that use recursion to start the next task was the best I could come up with. Ideally though there would be some high level api that takes a generator and a function, and keeps n number of workers alive while the generator gets processed. \$\endgroup\$
    – 0xKate
    Oct 15, 2022 at 7:20

1 Answer 1


Combining concurrent.futures and subprocess libraries, seems to be the shortest sync way to achieve the same results. This spawns n number of threads that call subprocess.run which waits on the subprocess to finish. The ThreadPoolExecutor will automatically queue up any submited requests beyond its max_workers, only spawning as many as max_workers threads to work through the submited requests.

import logging
import subprocess
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path

logging.basicConfig(format='[%(asctime)s][%(name)s][%(thread)s][%(levelname)s]: %(message)s', level=logging.DEBUG)

def launch_compiler(file):
    outfile = Path(str(file).removesuffix('.c'))
    logging.info(f"Compiling: {file}")
    subprocess.run(['./fake_files/fake_compiler.exe', file, outfile], capture_output=True, text=False)
    logging.info(f"finished: {file}")

def compile_with_workers(max_workers):
    # When ThreadPoolExecutor is used as context-manager
    # .shutdown is called on exit which blocks until all background threads complete
    with ThreadPoolExecutor(max_workers=max_workers) as pool:
        for fqp in Path('./fake_files').rglob('*.bin.c'):
            pool.submit(launch_compiler, fqp)

    # Execution will block until Executor completes all submitted requests
    logging.info('All processes finished.')

if __name__ == '__main__':

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