Reference library

Concurrency & performance

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

1 match
Concurrency & performance medium

How to Speed Up Downloads with ThreadPoolExecutor in Python

Compare sequential and thread-pool download loops to measure real speedup when I/O s bound.

threads concurrency performance
Python
import time
import threading
from concurrent.futures import ThreadPoolExecutor

def download_file(file_id):
    """Simulate fetching a file by sleeping briefly."""
    time.sleep(0.2)  # pretend network latency
    return f"file_{file_id}"

def sequential_downloads(num_files):
    """Process files one at a time."""
  …
13 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.