Reference library

Concurrency & performance

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

1 match
Concurrency & performance medium

How to Use threading.local for Per-Thread Data in Python

Use threading.local to keep thread-specific data — each thread gets its own copy of the attribute, so values don't leak between threads.

threading thread-local concurrency
Python 
import threading
import time

local_storage = threading.local()

def worker(name):
    local_storage.name = name
    time.sleep(0.1)
    print(f"Thread {threading.current_thread().name}: {local_storage.name}")

if __name__ == "__main__":
    threads = []
    for i in range(3):
        t = threading.Thread(target=worke…
14 0 Open

Browse by section

Each section groups closely related Python snippets.

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.

Related coding tools

Free online Python IDE Write and run Python in your browser — no install. Free Python code formatter Format with autopep8 — side-by-side PEP 8 cleanup. Python code samples Copy-ready snippets to study and run in the IDE.