Concurrency & performance
asyncio, threading, multiprocessing, and profiling-friendly performance patterns.
How to Vectorize a Function with a Pure Python Fallback
Create a decorator that calls a scalar function directly for a single value and routes list inputs to a pure-Python fallback for vectorized processing without NumPy.
import math
def fallback_vectorize(func, fallback=None):
"""Vectorize a scalar function with a pure-Python fallback for lists."""
if fallback is None:
fallback = lambda x: [func(i) for i in x]
def wrapped(*args):
if len(args) == 1 and isinstance(args[0], (list, tuple)):
retur…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.
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…How to set a timeout with asyncio.wait_for in Python
Use asyncio.wait_for to bound an async function with a timeout, catching TimeoutError when it exceeds the limit.
import asyncio
async def slow_task():
await asyncio.sleep(3)
return "finished"
async def main():
try:
result = await asyncio.wait_for(slow_task(), timeout=1)
print(result)
except asyncio.TimeoutError:
print("Task timed out")
if __name__ == "__main__":
asyncio.run(main())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.
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…How to start, join, and make daemon threads in Python
Starts one daemon and one non-daemon thread, joins the non-daemon thread, and shows how daemon threads exit when the main program ends.
import threading
import time
import logging
logging.basicConfig(level=logging.INFO, format="%(threadName)s: %(message)s")
def worker(name, delay):
for i in range(3):
time.sleep(delay)
logging.info(f"{name} step {i}")
if __name__ == "__main__":
daemon_thread = threading.Thread(
target…How to use ThreadPoolExecutor for concurrent tasks in Python
Run blocking functions in parallel with ThreadPoolExecutor and as_completed, cutting total runtime from 5 sequential sleeps to about 1 second.
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
def fetch_data(item):
"""Simulate a slow operation with a fixed delay."""
time.sleep(0.2)
return item * 2
def main():
items = [1, 2, 3, 4, 5]
start = time.perf_counter()
with ThreadPoolExecutor(max_workers=3) as ex…Limit Concurrency with asyncio.Semaphore in Python
Use asyncio.Semaphore to cap how many async tasks run at once, throttling a batch of coroutines to a set concurrency limit.
import asyncio
import random
async def fetch_data(i: int, semaphore: asyncio.Semaphore) -> str:
async with semaphore:
print(f"Task {i} starts")
await asyncio.sleep(random.uniform(0.1, 0.5))
print(f"Task {i} finishes")
return f"Result {i}"
async def main() -> None:
semaphore …Mocking Trio's open_nursery and spawn with asyncio.TaskGroup
Show how to mock Trio's nursery pattern using Python's asyncio.TaskGroup to simulate task spawning and completion.
import asyncio
class MockSpawner:
async def spawn(self, nursery):
print("Spawning mock task...")
await asyncio.sleep(1)
print("Mock task completed")
async def open_nursery():
async with asyncio.TaskGroup() as nursery:
mock = MockSpawner()
nursery.create_task(mock.spawn…asyncio sleep cooperative scheduling demo in Python
This demo shows how asyncio.sleep yields control between concurrent tasks, letting multiple workers interleave their ticks.
import asyncio
async def worker(name, delay):
for i in range(3):
print(f"{name}: tick {i}")
await asyncio.sleep(delay)
return f"{name} done"
async def main():
tasks = [
asyncio.create_task(worker("A", 0.1)),
asyncio.create_task(worker("B", 0.2)),
asyncio.create_tas…Browse by section
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Concurrency & performance — Python code examples
What you will find here
This page collects concurrency & performance snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
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Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.