Reference library

Concurrency & performance

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

1 match
Concurrency & performance easy

How to Time Code Performance with timeit in Python

Benchmark two implementations of the same logic using Python's timeit module and compare their execution speeds.

timeit performance benchmark
Python
import timeit

# Implementation 1: Using a list comprehension
def list_comprehension_squares(n):
    return [i ** 2 for i in range(n)]

# Implementation 2: Using a for loop with append
def loop_squares(n):
    result = []
    for i in range(n):
        result.append(i ** 2)
    return result

if __name__ == "__main__"…
12 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.