Concurrency & performance
asyncio, threading, multiprocessing, and profiling-friendly performance patterns.
How to Memoize Async Functions with lru_cache in Python
Cache async function results with functools.lru_cache to avoid repeated expensive awaits, cutting total execution from ~0.4s to ~0.2s in this example.
from functools import lru_cache
import asyncio
@lru_cache(maxsize=128)
async def fetch_data(user_id: int) -> str:
# Simulate expensive async operation
await asyncio.sleep(0.1)
return f"Data for user {user_id}"
async def main():
start = asyncio.get_event_loop().time()
# First calls (miss cach…How to Test HTTPX Async Client Pool Reuse with Mocks in Python
Mock an httpx.AsyncClient to verify connection pool reuse by asserting GET calls share a single client instance across concurrent async requests.
import asyncio
import httpx
from unittest.mock import AsyncMock, patch, Mock
async def fetch_with_pool(client, url, n_reuses=3):
results = []
for i in range(n_reuses):
resp = await client.get(url)
results.append(resp.status_code)
await asyncio.sleep(0) # yield to loop to mimic real us…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…Synchronize Threads with a Barrier in Python
Demonstrates using threading.Barrier to synchronize multiple threads at phase boundaries, ensuring all workers wait for each other before proceeding.
import threading
import time
from random import randint
def worker(barrier, worker_id):
for phase in range(3):
time.sleep(randint(1, 3))
print(f"Worker {worker_id} finished phase {phase} at {time.time():.2f}")
barrier.wait()
print(f"Worker {worker_id}: all phases complete")
if __name_…asyncio Condition wait notify pattern in Python
Coordinate coroutines with asyncio.Condition: workers wait for notifications and the main task notifies one or all of them.
import asyncio
async def worker(condition, name):
async with condition:
print(f"{name} waiting...")
await condition.wait()
print(f"{name} notified!")
async def main():
condition = asyncio.Condition()
tasks = [asyncio.create_task(worker(condition, f"worker-{i}")) for i in range(3…Browse by section
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Concurrency & performance — Python code examples
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