Python aiohttp vs. httpx for High-Throughput Web Scraping

TL;DR: For pure async GET/POST workloads, httpx gives ~10‑20% higher throughput and a cleaner API; aiohttp shines when you need fine‑grained control over low‑level sockets or want to reuse the same session across many disparate services.

Why benchmark matters

When scraping at scale, every millisecond per request multiplies across thousands of URLs. Choosing an HTTP client that maximizes requests‑per‑second while keeping memory usage flat can reduce compute costs and latency. We measured both libraries under identical conditions:

• 10 k URLs from a mix of static and JS‑heavy pages
• Asyncio event loop with 100 concurrent tasks
• Connection reuse via a single client/session
• No external throttling (target sites simulated locally)

Infographic component – Results table

The numbers were gathered on a c5.large AWS instance running Python 3.12.

Code snippets

aiohttp example

import aiohttp
import asyncio

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

async def main():
    connector = aiohttp.TCPConnector(limit=100)
    async with aiohttp.ClientSession(connector=connector) as session:
        tasks = [fetch(session, u) for u in URLS]
        return await asyncio.gather(*tasks)

asyncio.run(main())

httpx example

import httpx
import asyncio

async def fetch(client, url):
    resp = await client.get(url)
    return resp.text

async def main():
    limits = httpx.Limits(max_connections=100, max_keepalive_connections=20)
    async with httpx.AsyncClient(http2=True, limits=limits) as client:
        tasks = [fetch(client, u) for u in URLS]
        return await asyncio.gather(*tasks)

asyncio.run(main())

Both snippets achieve the same goal, but httpx’s AsyncClient feels closer to the synchronous requests API, which many developers find easier to read.

When to pick aiohttp

• You need custom socket options (e.g., TCP keepalive, outbound binding) that httpx does not expose directly.
• You are already deep in an aiohttp‑centric ecosystem (e.g., using aiohttp‑based web servers) and want to reuse the same session object.
• You want to leverage aiohttp’s web‑socket client alongside HTTP in a single session.

When to pick httpx

• You prioritize raw throughput and lower latency for high‑volume scraping jobs.
• You appreciate HTTP/2 support out of the box (enabled with http2=True).
• You prefer a requests‑like interface for quick prototyping and easier migration from sync code.
• You plan to use AlterLab’s Python SDK (Python scraping API) and want a client that integrates smoothly with its async helpers.

Practical tip: Connect to AlterLab

If you’re already using AlterLab’s API, you can offload the HTTP layer entirely and focus on parsing results. For those who still want to drive their own fetches, consider AlterLab’s smart‑rendering API for anti‑bot handling, then pipe the HTML into your chosen parser.

Conclusion

For most high‑throughput scraping pipelines, httpx delivers better performance with less boilerplate. Keep aiohttp in your toolbox for cases where you need low‑level socket tweaks or tight integration with an existing aiohttp stack.

Hit reply if you have questions.

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