Concurrency & performance
asyncio, threading, multiprocessing, and profiling-friendly performance patterns.
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
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.
Samples vs tutorials and challenges
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.