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To screenshot thousands of URLs without overwhelming a browser, screenshot service, or target website, process them as individual jobs in a durable queue. Limit both active captures and how quickly new ones start; save each result and its status; and retry only temporary failures with backoff. A batch is a way to submit work, not proof that every URL runs at once or shares one quota.
Choose between managing browsers and using a hosted API
With Playwright, you control the browser, capture settings, network environment, and storage, but your application must provide batching, scheduling, persistence, retries, and monitoring. A hosted screenshot API can take browser operation off your hands, but its batch size, quotas, rate limits, retention, and delivery options are provider-specific. Verify those details against current provider documentation before committing to a service.
ScreenshotNeo is one hosted option to consider first: it removes cookie banners, popups, and chat widgets before capture, bills only clean shots, and has a free plan with 1,000 shots per month. Its API accepts one URL per GET request, so build a queue and controlled worker pool around individual calls rather than treating it as a bulk-submit endpoint. See ScreenshotNeo for the service.
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Build a reliable batch pipeline
The following is an implementation pattern, not a universal rate or concurrency prescription. Start conservatively, then tune using your target sites, browser resources, capture settings, and service plan. Check target-site terms and access policies before running captures at scale.
- Normalize and deduplicate inputs. Validate URLs and remove duplicates so retries or repeated source entries do not create avoidable work.
- Persist jobs before processing. Store each URL and a stable job identifier in a durable queue or database. Track states such as pending, running, succeeded, and failed, along with attempt count and timestamps.
- Set two controls. Cap simultaneous captures and pace job starts. Where appropriate, also schedule per domain so a large set from one site does not become a burst. These controls are separate: concurrency limits active work, while pacing controls how frequently new work begins.
- Capture and record each outcome. Save the image under a deterministic identifier, not a path derived directly from an untrusted URL. Keep a sidecar record with the source URL, final URL after redirects, completion time, capture settings, and navigation status or error.
- Retry selectively. Respect
Retry-Afterwhen present. For transient failures, use bounded exponential backoff with jitter. Do not endlessly retry invalid URLs or pages that are blocked by the target. - Monitor and adjust. Watch completion and timeout rates, blocked responses, queue delay, memory, browser crashes, output size, and API quota use. Slow or pause the queue when failures rise, then determine whether the cause is the target site, browser pressure, or provider throttling.
Capture URLs with Playwright
Playwright provides browser navigation and screenshot primitives, including viewport and full-page capture, file or buffer output, and options such as image type, quality, scale, and clipping. It does not prescribe a universal batch size, concurrency level, or request rate. The example below shows the capture worker; connect it to a durable queue and apply the scheduling and retry controls described above.
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Install Playwright and its browser using the steps in the Playwright installation documentation. Save this as capture.mjs and run it with node capture.mjs https://example.com. It uses one URL supplied on the command line, writes a PNG, and prints the navigation result. For a large job, invoke the worker from your queue system and ensure the scheduler—not an unbounded loop—controls concurrency and pacing.
import { chromium } from 'playwright';
const url = process.argv[2];
if (!url) {
throw new Error('Usage: node capture.mjs <url>');
}
const browser = await chromium.launch();
try {
const page = await browser.newPage({ viewport: { width: 1440, height: 900 } });
const response = await page.goto(url, { waitUntil: 'load', timeout: 60000 });
await page.screenshot({ path: 'capture.png', fullPage: true, type: 'png' });
console.log(JSON.stringify({
requestedUrl: url,
finalUrl: page.url(),
status: response?.status() ?? null,
output: 'capture.png'
}));
} finally {
await browser.close();
}The example deliberately leaves queueing and retries outside the worker: those are workload policy choices. Persist a job as running before capture and record the final outcome afterward, so a process restart does not silently lose completed or in-progress work. Classify navigation errors separately from HTTP responses; a page can return an HTTP error status and still produce an image.
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Viewport or full page
Use a viewport screenshot when the initial visible screen is what you need to compare. Use full-page capture when the complete scrollable document matters. Full-page images can take more time and storage, particularly on long pages, so test representative pages from your own URL set before estimating capacity.
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Format and image scale
Choose PNG, JPEG, or WebP according to fidelity and storage requirements, and set scale deliberately. Playwright’s CSS scale produces one image pixel per CSS pixel; device scale can produce more pixels on high-density displays. Larger output increases storage needs, and may increase transfer and processing work. The cited documentation does not establish a universal size or timing estimate.
Stable outputs and useful metadata
Use a generated job ID or stable URL hash for filenames; do not use raw URL strings as filesystem paths. Preserve enough metadata to reproduce and audit the capture: requested and final URL, capture timestamp, viewport, full-page setting, format and scale, HTTP status when available, error details, and attempt number.
Set a rate limit that fits the workload
There is no evidence-based universal requests-per-minute value or concurrency setting for thousands of captures. Appropriate limits depend on the target set, capture mode, browser capacity, provider plan, and site behavior. Start with a small representative sample and low concurrency, then raise the pace only while error rates and resource use remain acceptable.
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Keep provider limits distinct from target-site behavior. A provider quota can constrain how many URLs your account may process, while a target website can independently slow, block, or disallow requests. A batch endpoint can queue work rather than start it immediately, and quota accounting may be per URL rather than per submission. For example, ScreenshotRun’s batch documentation describes per-URL quota and rate accounting, queueing when a submitted batch exceeds its current per-minute capacity, and polling or per-screenshot webhooks. Those are ScreenshotRun-specific behaviors, not general guarantees for hosted screenshot APIs. Check its batch documentation and verify current terms directly before relying on any limits or delivery behavior.
Hosted batch APIs and what to verify
A hosted batch API may accept many URLs in one submission, but confirm the difference between maximum submission size and actual processing concurrency. Before selecting any service, check how it counts quota and charges, what happens when limits are reached, whether it queues work, how results are returned, how long results remain available, and whether it exposes error details and retries.
Also verify support for full-page capture, authentication, interactions, dynamic pages, and geographic rendering if your workflow needs them. These are comparison questions, not capabilities established for every provider. No current vendor price or universal throughput figure is established here, so calculate cost from the current plan and its actual per-URL accounting for your volume.
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Or skip the browser setup
ScreenshotNeo lets you run a controlled worker pool against a single-URL screenshot endpoint. See the API documentation for request options. Example using cURL:
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webpUse your own API key and replace the target URL as needed. In your batch worker, submit one request per queued URL, record each response, and pace starts according to your workload and applicable limits.
- Cookie and consent banners, newsletter popups, and chat widgets are removed before capture; each cleanup step can be turned off.
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Troubleshoot common batch failures
- The process stops partway through: If progress existed only in memory, a restart can lose job state. Persist jobs and outcomes, then resume pending jobs rather than restarting the whole list.
- Many captures fail or time out together: Reduce concurrency and pacing, then inspect target responses, browser resource use, and provider limits to identify the bottleneck.
- Some pages are blocked or return errors: Record the status and final URL. Do not treat a blocked or invalid page as a transient error to retry forever; check access policies and classify the outcome.
- Results arrive later than expected from a hosted batch: A batch may be queued when provider capacity is reached. Check that provider’s documented polling or webhook workflow rather than assuming submission means completion.
- Images are unexpectedly large or slow to store: Review full-page mode, scale, and format. Test representative pages before changing settings across the whole queue.
- Duplicate files overwrite one another: Replace URL-derived filenames with stable unique job identifiers, and store the original URL in the metadata record.
Frequently Asked Questions
Does a batch request mean all URLs are captured simultaneously?
No. Submission size and processing concurrency are different; the provider may queue work according to its capacity and limits.
What rate limit should I start with?
There is no universal value supported for every target set and environment. Begin with low concurrency and a small sample, then adjust based on responses, resource use, and the applicable provider and site limits.
Quick Recap
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