Capture a Full-Height Screenshot of a Webpage
In just a few lines of JSON inlined in a single cURL command, you can automate:
Dismissing Wikipedia’s EU cookie consent banner (if present)
Waiting for the main heading on the Artificial Intelligence article
Scrolling through every section (lazy-loaded images and all)
Capturing a full-page PNG for archiving, visual regression, or documentation
All without installing Playwright or managing headless browsers, Gaffa handles it for you server-side via the Browser Requests API.
Prerequisites
A valid Gaffa API key
A simple HTTP client (cURL, Postman, axios, etc.).
Familiarity with the API Playground for testing browser requests.
Target URL for this tutorial, for this we'll use wikipedia: https://en.wikipedia.org/wiki/Artificial_intelligence
Execute the Request
Use cURL with the full JSON payload inlined to ensure Gaffa receives exactly what you intend:
curl https://api.gaffa.dev/v1/browser/requests \
--request POST \
--header 'Content-Type: application/json' \
--header 'X-API-Key: YOUR_API_KEY' \
--data '{
"url": "https://en.wikipedia.org/wiki/Artificial_intelligence",
"async": false,
"max_cache_age": 0,
"settings": {
"actions": [
{
"type": "wait",
"selector": "#cookie-policy-notice",
"timeout": 10000,
"continue_on_fail": true
},
{
"type": "click",
"selector": "#cookie-policy-notice",
"continue_on_fail": true
},
{
"type": "wait",
"selector": "#firstHeading",
"timeout": 10000
},
{
"type": "scroll",
"percentage": 100
},
{
"type": "capture_screenshot",
"size": "fullscreen"
}
]
}
}'Replace YOUR_API_KEY with your actual token from your Dashboard. This command has the following actions:
Wait (optional): Detect and accept Wikipedia’s cookie banner if it appears. If it fails, that simply means no banner was present or it did not load in time. Since continue_on_fail defaults to true, Gaffa will move on without halting the workflow, ensuring the rest of the steps still execute.
Wait: Ensure the main heading (#firstHeading) is loaded.
Scroll: Scroll through the entire page to trigger any lazy-loaded content.
Capture Screenshot: Produce a full-page PNG.
Retrieve Your Screenshot
A successful response returns JSON like:
{
"data": {
"id": "brq_VJX3mbESLiyCFYvZQEUih9RdDYovog",
"url": "https://en.wikipedia.org/wiki/Artificial_intelligence",
"proxy_location": null,
"state": "completed",
"credit_usage": 2,
"http_status_code": 200,
"from_cache": false,
"started_at": "2025-06-09T15:55:46.4235903Z",
"completed_at": "2025-06-09T15:56:27.9381332Z",
"running_time": "00:00:40.7348244",
"page_load_time": "00:00:02.2087117",
"actions": [
{
"id": "act_VJX3memaue6YUgFcn44uNscZbVUpYg",
"type": "wait",
"query": "wait?selector=%23cookie-policy-notice%2C%20.mw-cookie-consent-container&timeout=10000&continue_on_fail=true",
"timestamp": "2025-06-09T15:55:48.6323091Z",
"error": "action_timed_out"
},
{
"id": "act_VJX3mkwfwNPdGiMUpqKr34Tm5xzyUU",
"type": "click",
"query": "click?selector=%23cookie-policy-notice%20button%2C%20.mw-cookie-consent-container%20button&continue_on_fail=true&timeout=5000",
"timestamp": "2025-06-09T15:55:58.7949275Z",
"error": "action_timed_out"
},
{
"id": "act_VJX3mkSJ3sevWRXUCjFy6zwfD172fV",
"type": "wait",
"query": "wait?selector=%23firstHeading&timeout=10000&continue_on_fail=false",
"timestamp": "2025-06-09T15:56:03.9581113Z"
},
{
"id": "act_VJX3mbq9Jgj8EwADszW2AqdeJJXJiY",
"type": "scroll",
"query": "scroll?percentage=100&max_scroll_time=20000&scroll_speed=medium&continue_on_fail=false",
"timestamp": "2025-06-09T15:56:03.9691994Z"
},
{
"id": "act_VJX3mjBQYv8zTsXv1SkgUnBkzNFmJU",
"type": "capture_screenshot",
"query": "capture_screenshot?size=fullscreen&continue_on_fail=false",
"timestamp": "2025-06-09T15:56:20.0727905Z",
"output": "https://storage.gaffa.dev/brq/image/brq_VJX3mbESLiyCFYvZQEUih9RdDYovog/act_VJX3mjBQYv8zTsXv1SkgUnBkzNFmJU_full.png"
}
]
},
"error": null
}The response contains the following information:
data.id: Unique request identifier.
data.state: "completed" means the workflow finished (even if some steps timed out).
data.credit_usage: Credits consumed for this run.
data.started_at / data.completed_at: Workflow timing.
data.running_time and data.page_load_time: Performance metrics.
data.actions: Each action’s details, including successes, timeouts, and final screenshot URL.
Within the list of actions you'll be able to see the capture_screenshot action which contains an output parameter containing the full size screenshot that was captured.
If you don't want to use cURL, you can also run this query in the Gaffa API Playground which is an easy way to get started.
Use Cases
Gaffa's screenshot action could be used for a huge number of use cases, but here are a few ideas:
Visual Regression: Integrate into your CI pipeline to compare changes over time.
Archival: Schedule daily captures for audit or compliance purposes.
Monitoring: Automate periodic checks to detect visual bugs or layout shifts.
All this is powered by Gaffa’s hosted headless browsers with no local setup required. Experiment with more actions and build complex browser workflows easily. Refer to the full Browser Requests API documentation for additional capabilities.
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