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Concurrency & performance

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

3 matches

How to Send and Receive Messages Between Processes with multiprocessing.Pipe in Python

Use multiprocessing.Pipe to create a two-way connection between two processes, send a message from parent to child, and receive a reply back.

multiprocessing pipe interprocess-communication

Python

import multiprocessing


def child_process(conn):
    """Receive from parent and send back a response."""
    message = conn.recv()
    print(f"Child received: {message}")
    conn.send("Hello from child!")


if __name__ == "__main__":
    parent_conn, child_conn = multiprocessing.Pipe()

    process = multiprocessing…

14 0 Open

Concurrency & performance easy

How to Use pool.map for CPU-Bound Tasks in Python

Distribute CPU-intensive functions across processes with multiprocessing.Pool.map and measure the performance gain.

multiprocessing pool cpu-bound

Python

from multiprocessing import Pool
import time

def cpu_bound_task(n):
    """Mock CPU-bound work: compute sum of squares."""
    total = 0
    for i in range(n):
        total += i * i
    return total

if __name__ == "__main__":
    numbers = [10_000_000, 12_000_000, 8_000_000, 15_000_000]

    start = time.perf_count…

11 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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