Python Async Web Scraping: Scrape 1000 Pages in Seconds

Synchronous scraping is slow - each request blocks until the server responds. With asyncio and httpx, you can fire off hundreds of requests concurrently and cut your scraping time from minutes to seconds.

Installation

pip install httpx beautifulsoup4 lxml

The Core Concept

Sync: fetch(1) -> wait -> fetch(2) -> wait -> fetch(3) -> wait ...

Async: fetch(1), fetch(2), fetch(3) all wait at the same time -> results arrive together

This is the difference between 300 seconds and 3 seconds for 1000 pages.

Complete Async Scraper with Rate Limiting

import asyncio
import httpx
from bs4 import BeautifulSoup
from datetime import datetime
import json

MAX_CONCURRENT = 20
TIMEOUT = 15

async def fetch_one(
    client: httpx.AsyncClient,
    url: str,
    semaphore: asyncio.Semaphore,
) -> dict:
    async with semaphore:
        try:
            resp = await client.get(url)
            resp.raise_for_status()
            return {"url": url, "status": resp.status_code, "html": resp.text}
        except httpx.HTTPStatusError as e:
            return {"url": url, "status": e.response.status_code, "html": "", "error": str(e)}
        except httpx.RequestError as e:
            return {"url": url, "status": 0, "html": "", "error": str(e)}

async def fetch_all(urls: list[str]) -> list[dict]:
    semaphore = asyncio.Semaphore(MAX_CONCURRENT)
    headers = {
        "User-Agent": "Mozilla/5.0 (X11; Linux x86_64; rv:120.0) Gecko/20100101 Firefox/120.0"
    }
    async with httpx.AsyncClient(
        timeout=TIMEOUT,
        follow_redirects=True,
        headers=headers,
    ) as client:
        tasks = [fetch_one(client, url, semaphore) for url in urls]
        results = await asyncio.gather(*tasks)
    return list(results)

def parse_title(html: str) -> str:
    if not html:
        return ""
    soup = BeautifulSoup(html, "lxml")
    tag = soup.find("title")
    return tag.get_text(strip=True) if tag else ""

async def scrape_urls(urls: list[str]) -> list[dict]:
    print(f"Starting async scrape of {len(urls)} URLs...")
    start = datetime.now()
    raw_results = await fetch_all(urls)
    parsed = []
    ok_count = 0
    for result in raw_results:
        title = parse_title(result["html"])
        parsed.append({
            "url": result["url"],
            "status": result["status"],
            "title": title,
            "error": result.get("error", ""),
        })
        if result["status"] == 200:
            ok_count += 1
    elapsed = (datetime.now() - start).total_seconds()
    print(f"Done: {ok_count}/{len(urls)} OK in {elapsed:.1f}s")
    print(f"Speed: {len(urls) / elapsed:.1f} pages/sec")
    return parsed

async def main():
    base = "https://docs.python.org/3/library/"
    modules = [
        "asyncio.html", "pathlib.html", "dataclasses.html",
        "typing.html", "functools.html", "itertools.html",
        "collections.html", "contextlib.html", "logging.html",
        "unittest.html", "json.html", "csv.html",
        "re.html", "os.html", "sys.html",
        "datetime.html", "hashlib.html", "base64.html",
        "urllib.request.html", "http.client.html",
        "socket.html", "ssl.html", "threading.html",
        "multiprocessing.html", "subprocess.html",
        "io.html", "struct.html", "array.html",
        "queue.html", "heapq.html",
    ]
    urls = [base + m for m in modules]
    results = await scrape_urls(urls)
    for r in results[:5]:
        icon = "OK" if r["status"] == 200 else "ERR"
        print(f"[{icon}] [{r['status']}] {r['title'][:50]}")
    with open("docs_scrape.json", "w") as f:
        json.dump(results, f, indent=2)
    print(f"Saved {len(results)} results")

if __name__ == "__main__":
    asyncio.run(main())

Retry Logic with Exponential Backoff

async def fetch_with_retry(
    client: httpx.AsyncClient,
    url: str,
    semaphore: asyncio.Semaphore,
    retries: int = 3,
) -> dict:
    async with semaphore:
        for attempt in range(retries):
            try:
                resp = await client.get(url)
                resp.raise_for_status()
                return {"url": url, "html": resp.text, "ok": True}
            except (httpx.TimeoutException, httpx.ConnectError):
                if attempt < retries - 1:
                    await asyncio.sleep(2 ** attempt)
                else:
                    return {"url": url, "html": "", "ok": False, "error": "Max retries"}
            except httpx.HTTPStatusError as e:
                if e.response.status_code >= 500:
                    await asyncio.sleep(1)
                else:
                    return {"url": url, "html": "", "ok": False,
                            "error": f"HTTP {e.response.status_code}"}
        return {"url": url, "html": "", "ok": False, "error": "Unknown"}

Practical Tips

• Start with 5-10 concurrent requests, increase only if the server allows it
• asyncio.Semaphore is your throttle - never skip it for polite scraping
• asyncio.gather(*tasks, return_exceptions=True) prevents one failure from cancelling all tasks
• Stream large responses with client.stream() to avoid memory issues
• Reuse the AsyncClient - creating one per request is slow and wastes connections

---

Follow me for more Python tips! 🐍

---

💡 Related: **Content Creator Ultimate Bundle (Save 33%)* — $30*

---

💡 Related: **Content Creator Ultimate Bundle (Save 33%)* — $29.99*