Does urllib3 support asynchronous requests?

urllib3 is a powerful, user-friendly HTTP client for Python. However, as of my last update in 2023, urllib3 does not natively support asynchronous requests. urllib3 is designed to work within a synchronous programming model, which means that it waits for each request to complete before continuing to the next line of code. This can lead to inefficient use of resources when dealing with I/O-bound tasks such as making multiple HTTP requests, where the program could be doing other work while waiting for the responses.

For asynchronous HTTP requests in Python, you would typically use libraries such as aiohttp, which is built for asynchronous programming using the asyncio framework. Below is an example of how to make asynchronous HTTP requests using aiohttp:

import aiohttp
import asyncio

async def fetch(session, url):
    async with session.get(url) as response:
        return await response.text()

async def main():
    async with aiohttp.ClientSession() as session:
        html = await fetch(session, '')

loop = asyncio.get_event_loop()

If you are committed to using urllib3 but want to make asynchronous requests, you would have to use threading or multiprocessing to achieve concurrency. Here's an example of how you might use urllib3 with concurrent.futures.ThreadPoolExecutor to make concurrent requests:

import urllib3
from concurrent.futures import ThreadPoolExecutor

def fetch(url):
    http = urllib3.PoolManager()
    response = http.request('GET', url)

urls = [

with ThreadPoolExecutor(max_workers=5) as executor:
    future_to_url = {executor.submit(fetch, url): url for url in urls}
    for future in concurrent.futures.as_completed(future_to_url):
        url = future_to_url[future]
            data = future.result()
            print(f"{url} page length is {len(data)}")
        except Exception as exc:
            print(f"{url} generated an exception: {exc}")

Remember that using threads does not necessarily make your code run faster if the task is CPU-bound. Threads are best used for I/O-bound tasks such as network requests.

For true asynchronous support in Python, you would typically use asyncio with a compatible library like aiohttp, as demonstrated earlier.

In JavaScript, making asynchronous HTTP requests is a built-in feature of the language, typically using fetch API or XMLHttpRequest in a browser environment, or libraries like axios or native modules like http and https in Node.js. Here's an example using fetch in modern JavaScript:

async function fetchData(url) {
  try {
    const response = await fetch(url);
    const data = await response.text();
  } catch (error) {
    console.error('Error fetching data: ', error);

const url = '';

In this JavaScript example, the fetchData function is asynchronous and uses the await keyword to wait for the fetch call to resolve, without blocking the main thread.

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