Concurrency & performance
asyncio, threading, multiprocessing, and profiling-friendly performance patterns.
How to Implement a Batch Requests Flush Interval in Python
A simple async batcher that accumulates items and flushes them either when a max batch size is reached or after a time-based flush interval.
import asyncio
from collections import deque
class Batcher:
def __init__(self, flush_interval=0.5, max_batch=5):
self.flush_interval = flush_interval
self.max_batch = max_batch
self.queue = deque()
self.lock = asyncio.Lock()
async def add(self, item):
async with self.l…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…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.