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Concurrency & performance

asyncio, threading, multiprocessing, and profiling-friendly performance patterns.

3 matches

How to Use as_completed to Process Futures in Order of Completion

Submit multiple tasks to a ThreadPoolExecutor and process each result as soon as it finishes using as_completed.

from concurrent.futures import ThreadPoolExecutor, as_completed
import time


def fetch_data(item_id):
    time.sleep(1)
    return f"item-{item_id}"


def main():
    with ThreadPoolExecutor(max_workers=3) as executor:
        future_map = {executor.submit(fetch_data, i): i for i in range(1, 6)}
        for future in…

14 0 Open

Concurrency & performance easy

How to Wait for the First Future to Complete in Python

Use concurrent.futures.wait with FIRST_COMPLETED to pause until any task finishes and inspect the remaining pending futures.

concurrent.futures wait threading

Python

import concurrent.futures
import time


def task(name, delay):
    time.sleep(delay)
    return f"{name} done"


if __name__ == "__main__":
    with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor:
        futures = [
            executor.submit(task, "task1", 2),
            executor.submit(task, "ta…

13 0 Open

Concurrency & performance easy

How to spawn multiple worker processes in Python with multiprocessing.Process

Spawns three separate worker processes using multiprocessing.Process, runs them concurrently, and waits for all to finish before printing a completion message.

multiprocessing parallel concurrency

Python

import multiprocessing
import time

def worker(name):
    print(f"Worker {name} started")
    time.sleep(1)
    print(f"Worker {name} finished")
    return name

if __name__ == "__main__":
    processes = []
    for i in range(3):
        p = multiprocessing.Process(target=worker, args=(i,))
        processes.append(p…

14 0 Open

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