The Tool Desk
Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Use asyncio with an asynchronous HTTP client such as aiohttp when the data you need is available from ordinary web requests. Use an async browser automation library such as Playwright when the result depends on browser rendering, interaction, or browser-visible output. If your project needs a crawling framework, consider Scrapy and check its event-loop requirements before combining it with Playwright.
How do I use asyncio for web scraping?
asyncio is Python’s library for writing concurrent code with async and await. It is often useful for IO-bound work such as waiting for network responses: while one request waits, the event loop can run other eligible tasks. It also provides APIs for network I/O, subprocesses, queues, and synchronization. See the Python asyncio documentation.
For a scraper, the common pattern is to create asynchronous request tasks, await their responses, and parse the returned content. Concurrency does not make CPU-heavy parsing or blocking synchronous calls non-blocking. Keep blocking work out of the event loop or move it to an appropriate worker mechanism if it becomes a bottleneck.
Runnable example: fetch several pages with aiohttp
aiohttp is an asyncio-based HTTP client/server library. Its client flow uses a ClientSession, awaits a request, then reads the response body. Install it with python -m pip install aiohttp, save the following as scrape.py, then run python scrape.py:
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import asyncio
import aiohttp
URLS = [
"https://example.com/",
"https://www.iana.org/domains/reserved",
]
async def fetch(session, url):
async with session.get(url) as response:
response.raise_for_status()
html = await response.text()
return url, response.status, html
async def main():
timeout = aiohttp.ClientTimeout(total=30)
connector = aiohttp.TCPConnector(limit=10)
async with aiohttp.ClientSession(
timeout=timeout,
connector=connector,
) as session:
results = await asyncio.gather(
*(fetch(session, url) for url in URLS)
)
for url, status, html in results:
print(f"{status} {url}: {len(html)} characters")
if __name__ == "__main__":
asyncio.run(main())The connector limit and timeout in this example are explicit example settings, not universal tuning recommendations. Choose limits and timeouts based on the target, your workload, and the site’s rules. raise_for_status() makes unsuccessful HTTP responses visible instead of treating their bodies as successful page data.
Why reuse a session?
A ClientSession owns client-side state and connection-pooling behavior. Reusing one session across a batch is the ordinary aiohttp pattern; creating a new session for every URL adds unnecessary setup and forfeits reuse. Close the session with an asynchronous context manager as shown so its resources are released.
Bound work and handle failures
Launching an unbounded task for every URL can overwhelm your machine or place an unnecessary load on a site. Set a deliberate concurrency limit, and consider a semaphore or bounded queue when the number of inputs is large. Decide how your crawler should handle timeouts, network errors, non-success status codes, retries, and malformed content. Retry only errors that are plausibly transient, and use a limit and delay policy rather than retrying indefinitely. There is no single concurrency or retry setting that is appropriate for every target.
Should I use aiohttp or Playwright?
Choose based on where the information comes from and what output you need. A page that happens to use JavaScript does not automatically require a browser: if its data is available through reproducible HTTP requests, direct fetching may still be the simpler route. A browser is warranted when browser execution or interaction is part of the requirement.
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| Need | Likely approach | Why |
|---|---|---|
| Data is present in ordinary HTTP responses | asyncio with aiohttp |
Fetch responses directly and parse the data you need. |
| Browser rendering, interaction, or a browser-visible artifact | Playwright’s async API | Drive a real browser engine to perform actions or observe the rendered result. |
| A crawler needs crawling-framework components | Scrapy, with its asyncio support as appropriate | Use the framework when its crawling components suit the project, while checking reactor and event-loop compatibility. |
Scrapy recommends reproducing a page’s underlying data requests when practical: doing so can reduce parsing time and network transfer while yielding structured, complete data. A headless browser is useful when browser behavior is required, including when you need a screenshot as seen in a browser. Read Scrapy’s guide to selecting dynamically loaded content before deciding which route fits a site.
How do I automate a browser with Python asyncio?
Playwright’s async Python API drives Chromium, Firefox, and WebKit. Its driver runs in a subprocess, so browser automation has more operational setup and resource overhead than fetching response bodies directly. Install Playwright and its browser binaries using the current instructions in the Playwright Python documentation. The following standalone pattern opens a page and prints its title:
import asyncio
from playwright.async_api import async_playwright
async def main():
async with async_playwright() as playwright:
browser = await playwright.chromium.launch()
page = await browser.new_page()
await page.goto("https://example.com/", wait_until="domcontentloaded")
print(await page.title())
await browser.close()
if __name__ == "__main__":
asyncio.run(main())asyncio.run(main()) is the standard entry point for a standalone coroutine program. If a framework, notebook, or other host already manages an event loop, do not start a second one blindly; integrate with the host’s async model instead. Use await at asynchronous boundaries, and select page navigation and waiting conditions that match the behavior you need. A navigation event alone does not guarantee that every application-specific request or widget has finished.
Prefer the request behind a page when possible
When a browser page obtains structured data from an ordinary endpoint, inspect the page’s network behavior and determine whether the same request can be made directly. Reproducing that request can avoid launching a browser and transferring or parsing a full rendered page. Use Playwright instead if the data or artifact genuinely depends on browser execution, client-side interactions, or rendered state that you cannot reliably reproduce with requests.
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Scrapy is a crawling framework; its asyncio support does not mean every Playwright and Scrapy configuration can share any event loop. For integration, Scrapy recommends scrapy-playwright when you want browser handling while retaining more Scrapy components. Check the integration’s current installation and usage instructions alongside the Scrapy version and reactor your project uses.
Windows event-loop compatibility
On Windows, Playwright’s documentation requires ProactorEventLoop because its driver runs in a subprocess. Scrapy’s Windows asyncio reactor uses SelectorEventLoop. Those requirements conflict when combined in that configuration. Before adopting the combination, verify the configured reactor and loop for the versions and environment you will actually run.
Scrapy documents running without its Twisted reactor as a way to avoid this particular conflict, but that choice comes with feature limitations. It is not a universal fix: check which reactor-dependent components your project needs and confirm the current Scrapy guidance at Scrapy’s asyncio documentation.
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Performance, reliability, and responsible crawling
Async concurrency is not a speed guarantee
Async code can overlap time spent waiting on network I/O, but it does not guarantee a specific speedup or throughput. Actual results depend on the target, connection behavior, response sizes, parsing work, and concurrency choices. Measure your own workload; do not raise concurrency simply because the program uses asyncio.
Make failures observable
- Set a total request timeout and handle timeout exceptions.
- Check response status before parsing a body as valid page data.
- Record the URL and failure type so one bad response does not disappear silently.
- Limit retries and distinguish transient network failures from persistent errors.
- Validate extracted fields; a successful HTTP response can still contain an error page or unexpected markup.
- For browser automation, close pages and browsers reliably, including on exceptions, and wait for the specific state your task needs rather than adding arbitrary sleeps by default.
Respect access rules
Concurrency does not bypass access controls or grant permission to collect data. Review the target site’s applicable terms, access policies, and legal requirements, and keep request rates appropriate. The technical documentation cited here does not determine what is permitted for any particular site.
Troubleshooting common problems
“RuntimeError: asyncio.run() cannot be called from a running event loop”
Your environment already owns an event loop. In a notebook or async framework, call and await the coroutine through that environment’s supported mechanism instead of invoking asyncio.run() again.
Playwright works alone but fails with Scrapy on Windows
Check whether the configured Scrapy reactor uses SelectorEventLoop while Playwright needs ProactorEventLoop. Review Scrapy’s documented no-Twisted-reactor option and its limitations, or use the recommended Scrapy integration after confirming its requirements for your environment.
A page is blank or missing data after a successful request
Inspect the response status, body, and network requests. The requested URL may return a shell whose data is loaded separately, a redirect, or a different response than expected. Reproduce the underlying data request if practical; otherwise use a browser and wait for the required rendered state.
Requests hang or the crawler consumes too many resources
Set finite timeouts, bound the number of in-flight requests, and ensure sessions and browser resources are closed. Large batches should not become one unbounded gather of tasks; feed work through a bounded queue or process it in controlled batches.
Retries keep failing
Confirm whether the failure is transient before retrying. Persistent status errors, changed page structure, access denial, and invalid URLs will not be repaired by an endless retry loop. Surface the failure and decide whether to skip, stop, or investigate it.
Frequently Asked Questions
Does a JavaScript website always require Playwright?
No. Use direct HTTP requests if they expose the required data; use a browser when the required result depends on browser execution or interaction.
Can I use aiohttp and Playwright in the same Python project?
Yes, but when Scrapy is also involved, event-loop and reactor compatibility matters, particularly on Windows. Verify the configuration and integration guidance for the versions you use.
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