Reference library

Concurrency & performance

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

3 matches

How to Profile CPU Hot Path in Python with cProfile and sort_stats cumtime

Profile a Python function's CPU usage by running cProfile, sorting stats by cumulative time, and printing a readable report to stdout.

cprofile profiling performance

Python

import cProfile
import pstats
import io


def slow_function():
    total = 0
    for i in range(100_000):
        total += i * i
    return total


def fast_function():
    return sum(i for i in range(100))


def main():
    slow_function()
    fast_function()


if __name__ == "__main__":
    profiler = cProfile.Profi…

13 0 Open

Concurrency & performance easy

How to Use ThreadPoolExecutor and ProcessPoolExecutor in Python

Compares ThreadPoolExecutor and ProcessPoolExecutor by running CPU-bound and I/O-tolerant tasks over a large list, printing elapsed times and first results.

concurrency threadpool processpool

Python

import time
from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor
import math

numbers = list(range(1, 1000001))


def compute_square(n):
    return n * n


def compute_sqrt(n):
    return math.sqrt(n)


def run_executor(executor, func, data):
    start = time.perf_counter()
    results = list(executo…

15 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

Browse by section

Each section groups closely related Python snippets.