Do these 3 things before closing this tab:
1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsPut a concurrency limit around each complete screenshot job—not just the screenshot call. For Playwright Test, set its workers limit; for a standalone batch script, use a bounded queue or semaphore around navigation, readiness checks, capture, and cleanup. There is no source-backed universal safe number: start low, measure your actual workload, then adjust.
Choose the control that matches your setup
| Setup | Concurrency control | What it limits |
|---|---|---|
| Playwright Test | workers in the configuration or --workers N on the command line |
Worker processes in that test run |
| Custom screenshot batch | An application queue or semaphore around each URL job | Jobs within the scheduler’s scope; usually one process unless coordination is shared |
A page screenshot method captures a page; it does not schedule a list of URLs. The Playwright parallelism guide documents the test-runner worker control. The Playwright Page API and Puppeteer screenshot API document capture operations, not a universal bulk-job limit.
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Limit parallelism in Playwright Test
Set workers in Playwright Test’s configuration, or pass --workers N when running the test command. For a single worker, use --workers 1. For example, the Playwright guide shows npx playwright test --workers 4; that is a configuration example, not a recommendation for screenshot throughput.
The cap applies to worker processes in that test run. Each Playwright Test worker is a separate operating-system process and starts its own browser, so raising the worker count can raise total resource use. It does not mean one worker equals exactly one page, one screenshot, or a fixed amount of memory.
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Playwright also documents environment-dependent worker configuration and CI considerations in its Continuous Integration guide. Treat the default behavior and any example count as runner behavior, not as a generally safe limit for your machine or workload.
Bound a custom screenshot batch
A standalone script needs its own scheduler unless it hands work to a runner or service with an equivalent limit. Put the whole lifecycle of each URL inside the bounded job: navigation, any readiness condition, screenshot generation, and page cleanup. Otherwise, slow navigation or delayed cleanup can leave more browser work active than the intended cap.
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import PQueue from 'p-queue';
const limit = 3; // Starting point only; benchmark your workload.
const queue = new PQueue({ concurrency: limit });
await Promise.all(urls.map((url, index) => queue.add(async () => {
const page = await context.newPage();
try {
await page.goto(url, { waitUntil: 'networkidle' });
await page.screenshot({ path: `screenshots/${index}.png` });
} finally {
await page.close();
}
})));This illustrates the scheduling pattern; the example count is not a tested or benchmarked recommendation. Choose a queue library that suits your runtime and error-handling needs. Assign unique output paths, and record failures so a timeout or navigation error does not silently drop a URL. If networkidle is unsuitable for pages with persistent network activity, use a readiness condition that matches the page and workload rather than letting jobs wait indefinitely.
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A queue or semaphore in one process cannot cap work started by other processes, containers, or machines. If multiple producers share a target site or service, use a shared queue or distributed coordination layer for a true cross-host ceiling. Otherwise, each process may respect its own limit while the combined workload exceeds the intended rate.
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Playwright BrowserContexts isolate browser state, such as cookies, between contexts; they do not coordinate independent runs. See the Browser contexts guide. Puppeteer documents that, while a screenshot is running in a BrowserContext, operations such as creating or closing a page wait for it to finish. That same-context synchronization prevents interference; it is not a cap across independent jobs or machines. See Puppeteer’s screenshot method documentation.
Tune the limit by measuring your workload
No cited official documentation establishes a universal safe count of simultaneous screenshots, captures per worker, or optimal throughput. Test with representative URLs on the same class of machine you plan to use, then raise the cap gradually. Track:
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- Wall-clock completion time and completed URLs per interval.
- CPU and memory use, along with browser crashes.
- Navigation and screenshot timeouts, failed outputs, and retries.
- Target-site throttling or other signs that requests are arriving too aggressively.
Reduce concurrency if resource pressure, errors, or target-site throttling rise. Repeat the measurement when the page mix, browser configuration, or machine changes; a limit that works for lightweight pages may not suit pages with large assets or expensive rendering.
Troubleshoot common failures
- More jobs run than the configured limit: Check whether the limit covers only screenshot calls rather than navigation and cleanup, or whether multiple processes are each running a local queue. Move the full capture lifecycle inside the job and use shared coordination if the cap must span processes or hosts.
- Memory or CPU pressure rises after increasing Playwright workers: Remember that each worker is a separate process and starts a browser. Lower
workersor--workers, then remeasure. - Jobs hang during navigation: A readiness condition such as
networkidlemay not be reached by every page. Select an appropriate readiness check and ensure the job’s failure path records the URL and closes its page. - Some URLs have no output: Give every job a unique destination and capture failures explicitly. A failed navigation or screenshot should be visible in the batch results rather than disappearing from the final output set.
- Page state leaks between captures: Use separate BrowserContexts when isolation is needed. Context isolation does not replace a concurrency scheduler.
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