Async Web Scraping in Python: asyncio + aiohttp + httpx (Complete 2026 Guide)

Sequential scraping is slow. A scraper that fetches 10 URLs one at a time takes 10× longer than one that fetches them concurrently. Python's asyncio makes concurrent HTTP requests straightforward — here's how to use it correctly. Why asyncio for scraping Scraping is I/O-bound: you spend most of your time waiting for network responses. Asyncio lets Python do other work (like starting new requests) while waiting for responses. Synchronous (slow): import requests import time urls = [f"https://example.com/page/{i}" for i in range(100)] start = time.time() for url in urls: response = requests.get(url) # Process response print(f"Time: {time.time() - start:.1f}s") # ~100 seconds (1s per request) Async (fast): import asyncio import aiohttp import time async def fetch(session: aiohttp.ClientSession, url: str) -> str: async with session.get(url) as response: return await response.text() async def scrape_all(urls: list) -> list: async with aiohttp.ClientSession() as session: tasks = [fetch(