scraperapi/scraperapi-skills

scraperapi-async

Product-usage reference for ScraperAPI's Async Jobs API — submit scraping jobs in the background and retrieve results via polling or webhook, including batch jobs up to 50,000 URLs. Consult when the user is scraping many URLs, needs non-blocking requests, or wants webhook delivery. Use when user asks: "how do I scrape 1000 URLs with ScraperAPI", "ScraperAPI async jobs", "batch scraping with ScraperAPI", "submit a scraping job and poll for results", "ScraperAPI webhook callback", "scrape URLs in…

First seen Jun 2, 2026

Installation

$ npx skills add scraperapi/scraperapi-skills --skill scraperapi-async

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Stars 10
License LICENSE
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{"requires":{"env":["SCRAPERAPI_API_KEY"]},"emoji":"⚡","homepage":"https:\/\/docs.scraperapi.com\/making-async-requests"}

Package contents

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  • skill md SKILL.md 9,118 B
  • docs SUMMARY.md 822 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 74 installs

SKILL.md

ScraperAPI Async Jobs API

The Async API submits scraping jobs in the background and retries them for up to 24 hours to maximize success. Results are retrieved by polling a status URL or received automatically via webhook.

When NOT to use Async

  • Single URL, result needed immediately → use the Standard API (api.scraperapi.com) — simpler and returns inline.
  • Need to follow links across a site → use the Crawler.
  • Need recurring scheduled scraping → use DataPipeline.

Use Async when: scraping 20+ URLs, the target site is slow or flaky, you want webhook delivery, or you need to scrape PDFs/images.

Endpoints

Action Method URL
Submit single job POST https://async.scraperapi.com/jobs
Submit batch (up to 50k) POST https://async.scraperapi.com/batchjobs
Check / retrieve job GET https://async.scraperapi.com/jobs/<jobId>
Cancel job DELETE https://async.scraperapi.com/jobs/<jobId>

Auth: apiKey in the JSON request body (note: apiKey camelCase, unlike the Standard API's api_key).

Single Job

import os, requests, time

API_KEY = os.environ["SCRAPERAPI_API_KEY"]

# Submit
r = requests.post(
    "https://async.scraperapi.com/jobs",
    json={
        "apiKey": API_KEY,
        "url":    "https://example.com/product/123",
        "apiParams": {
            "render":       True,
            "country_code": "us",
        }
    }
)
job = r.json()
# {"id": "...", "status": "running", "statusUrl": "...", "url": "..."}

# Poll
def poll(status_url, interval=5, max_wait=120):
    deadline = time.time() + max_wait
    while time.time() < deadline:
        data = requests.get(status_url).json()
        if data["status"] == "finished":
            return data["response"]["body"]
        if data["status"] == "failed":
            raise RuntimeError(f"Job failed: {data.get('failReason')}")
        time.sleep(interval)
    raise TimeoutError("Job did not finish in time")

html = poll(job["statusUrl"])

Finished job response shape:

{
  "id": "...",
  "status": "finished",
  "statusUrl": "...",
  "url": "https://example.com/product/123",
  "response": {
    "headers": { "content-type": "text/html", "sa-final-url": "...", "sa-statuscode": "200" },
    "body": "<!doctype html>...",
    "statusCode": 200
  }
}

Batch Jobs (up to 50,000 URLs)

jobs = requests.post(
    "https://async.scraperapi.com/batchjobs",
    json={
        "apiKey": API_KEY,
        "urls": [
            "https://example.com/page/1",
            "https://example.com/page/2",
            # ... up to 50,000
        ],
        "apiParams": {"country_code": "us"}
    }
).json()
# Returns a list of {id, status, statusUrl, url} — one per submitted URL

results = [poll(job["statusUrl"]) for job in jobs]

For workloads over 50,000 URLs, split into multiple batch requests. Use webhooks (below) instead of polling when batches are large — polling 10,000 status URLs serially is slow.

Webhook Callbacks

Use webhooks to receive results without polling. ScraperAPI POSTs the completed job payload to your URL when the scrape finishes.

requests.post(
    "https://async.scraperapi.com/jobs",
    json={
        "apiKey": API_KEY,
        "url":    "https://example.com/",
        "callback": {
            "type": "webhook",
            "url":  "https://yourapp.com/scraperapi/callback"
        }
    }
)

Webhook mechanics:

  • By default, only successful jobs trigger the callback.
  • Set "expectUnsuccessReport": true to also receive failed job payloads.
  • ScraperAPI retries delivery 3 times; if all fail, the job is cancelled.
  • Webhook URL must be publicly accessible.
  • For testing without a server, use webhook.site.

Failed job callback payload:

{
  "id": "...",
  "attempts": 50,
  "status": "failed",
  "failReason": "failed_due_to_timeout",
  "url": "https://example.com/"
}

All Request Body Parameters

{
  "apiKey":               "YOUR_KEY",
  "url":                  "https://example.com",
  "urls":                 ["url1", "url2"],
  "method":               "GET",
  "headers":              { "Accept-Language": "en-US" },
  "body":                 "foo=bar",
  "callback":             { "type": "webhook", "url": "https://..." },
  "expectUnsuccessReport": false,
  "timeoutSec":           600,
  "meta":                 { "jobLabel": "batch-42" },
  "apiParams": {
    "autoparse":          false,
    "country_code":       "us",
    "keep_headers":       false,
    "device_type":        "desktop",
    "follow_redirect":    true,
    "premium":            false,
    "ultra_premium":      false,
    "render":             false,
    "wait_for_selector":  ".content",
    "screenshot":         false,
    "retry_404":          false,
    "output_format":      "html",
    "max_cost":           10
  }
}

Async-exclusive parameters

Parameter Type Purpose
expectUnsuccessReport boolean Receive webhook payload for failed jobs too
timeoutSec integer Override default job timeout (seconds)
meta object Custom metadata — echoed back in every response/callback for correlation

meta is especially useful for tracking which batch or workflow a job belongs to:

{ "meta": { "batchId": "run-2024-06", "sourceFile": "urls.csv" } }

Passing a POST request to the target site

requests.post(
    "https://async.scraperapi.com/jobs",
    json={
        "apiKey":  API_KEY,
        "url":     "https://api.example.com/search",
        "method":  "POST",
        "headers": {"content-type": "application/x-www-form-urlencoded"},
        "body":    "query=scraperapi&page=1",
    }
)

Binary Responses (PDFs and Images)

When the target URL returns binary content, the response body is Base64-encoded in response.base64EncodedBody.

import base64

r = requests.post(
    "https://async.scraperapi.com/jobs",
    json={"apiKey": API_KEY, "url": "https://example.com/report.pdf"}
)
job = r.json()

# ... wait or poll ...
result = requests.get(job["statusUrl"]).json()
pdf_bytes = base64.b64decode(result["response"]["base64EncodedBody"])
with open("report.pdf", "wb") as f:
    f.write(pdf_bytes)

Retention Policy

Job results are stored for up to 72 hours (24 hours guaranteed) after the job finishes. After that, the data is deleted — resubmit the job if you need it again.

Retrieve results before the retention window closes. For long pipelines, prefer webhooks so results are pushed to your system immediately upon completion.

Error Handling

Status Meaning Action
Job finished, statusCode: 200 Success Use response.body
Job finished, statusCode: 403 Target blocked the scrape Retry with premium: true in apiParams
Job failed, failReason: faileddueto_timeout Timed out after 24h retries Check if target is reachable; try render: false
HTTP 401 on submission Bad API key Check SCRAPERAPIAPIKEY
HTTP 403 on submission Out of credits or plan limit Check dashboard
HTTP 429 on submission Too many concurrent submissions Back off and re-submit in batches

Use max_cost in apiParams to cap per-request credit spend — requests that would exceed the cap return a 403 rather than consuming more credits than expected.

Credit Cost

The Async API uses the same credit costs as the Standard API:

Request type Credits
Standard 1
render: true 10
premium: true 10
ultra_premium: true 30
Failed requests 0

Async jobs that fail after exhausting all retries are not charged.

Documentation