A job board scraper is not one universal script. The right implementation starts with the board you need, the purpose of collection, and the permission route that board documents. For LinkedIn, automated crawling without express permission is prohibited and the Job Posting API is a vetted program requiring approval. Indeed directs developers to its API terms and documentation rather than granting blanket permission to crawl pages. Build against an approved API or partner integration whenever one exists, then enforce the source’s rules for storage, display, sharing, and deletion.
What a job board scraper should do
A production scraper or API client collects structured vacancy data, normalizes it, detects changes, and exposes useful results to a search product, internal dashboard, labor-market analysis workflow, or client service. A responsible design has five layers:
- Source adapter: one connector per board or approved feed.
- Policy gate: records the authorization, allowed fields, retention period, and permitted audiences for that source.
- Fetcher: uses the documented endpoint, authentication method, rate limits, and pagination model.
- Normalizer: converts different schemas into your canonical job model.
- Storage and delivery: deduplicates records, applies deletion rules, and serves only uses allowed by the source terms.
Do not treat a page being visible in a browser as permission to collect, retain, or republish it. Terms, contracts, privacy obligations, copyright, and local law can all affect a particular project. The following platform rules are published positions, not a legal opinion about every possible use.
Choose the access route before writing code
| Route | When it fits | What to verify |
|---|---|---|
| Official API | The board offers a documented developer or partner interface. | Eligibility, approval, scopes, quotas, fields, client authorization, storage, caching, display, and deletion. |
| Partner feed or export | You have a contract or an approved integration with a defined delivery format. | Contracted use, update frequency, attribution, redistribution, and termination handling. |
| Automated page collection | Only where the owner expressly permits it and the path is authorized. | Terms, robots restrictions, authentication, rate limits, identity, and whether republishing is allowed. |
For a new project, write a one-page collection specification first:
- Target board and exact product or API name.
- Intended users: your team, your customers, or the public.
- Purpose: private analysis, search, alerts, enrichment, or redistribution.
- Fields required and fields that can be discarded immediately.
- Retention, deletion triggers, and an owner for compliance changes.
LinkedIn: approval is a prerequisite
LinkedIn describes its Job Posting API as a “vetted API program.” Its terms, dated December 18, 2023, say developers and applications must pass LinkedIn’s developer and application vetting and receive approval; there is no right to use the API or its data without that approval. Access requests are reviewed for privacy and security practices, and the approved use case bounds how the data may be used. Read the Job Posting API Terms before designing your schema.
The same terms restrict use, storage, sharing, and deletion of Job Posting Data. Storage or caching is allowed only where the applicable documentation permits it, and defined events can require deletion. Map each database table and cache to those rules instead of assuming that a normal warehouse retention policy is acceptable.
What LinkedIn says about crawling
LinkedIn’s Crawling Terms and Conditions, last revised May 25, 2017, state: “Automated Crawling & Indexing without the express permission of LinkedIn is strictly prohibited.” The terms also limit crawlers to authorized data, paths, and directories, address robot-exclusion restrictions, and prohibit masking crawler identity. LinkedIn Recruiter help separately says third-party software such as crawlers, bots, browser plug-ins, and extensions that scrape or automate activity is not permitted; see Prohibited software and extensions.
Do not build a headless-browser LinkedIn collector and hope that a low request rate makes it acceptable. Request the relevant API access, document the approved use case, and implement only the methods and fields LinkedIn authorizes.
Indeed: use the applicable API terms and documentation
Indeed’s developer agreement describes API use as a limited license governed by the relevant API documentation and agreement. Its Terms FAQ says the answers are not exhaustive legal advice and do not replace the legally binding terms. The Indeed documentation portal contains integration material for jobs, employers, candidates, and job search.
That documentation is a starting point, not blanket permission to crawl Indeed pages or republish listings. Confirm that your account is eligible for the exact service, request access where required, and follow the endpoint’s authentication, quota, field, and display rules. If your plan involves client access or public redistribution, obtain confirmation that those uses are covered.
Design a canonical job schema
Keep source-specific payloads for auditability, but expose a stable internal model. A practical record contains:
sourceandsource_job_idfor traceability.title,description, and normalizedemployment_type.company_name, optional company identifier, and source URL.locationsas structured country, region, city, and remote indicators.salary_min,salary_max,salary_currency, and the stated interval when supplied.posted_at,updated_at,expires_at, and an ingestion timestamp.raw_hashto detect material changes without storing unnecessary copies.policy_profileidentifying retention, display, and deletion rules for that source.
Normalize conservatively. Preserve the original salary text and timezone; do not infer annual pay from an hourly range unless your product clearly labels the conversion. Keep “remote,” “hybrid,” and “on-site” distinct, and record the evidence used for each classification.
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Reference implementation for an authorized JSON feed
The following Python example demonstrates pagination, timeouts, retries, validation, and deduplication for an endpoint you are authorized to call. Replace the URL, authentication, parameters, and field mapping with the target board’s documented values; do not point it at a site whose terms prohibit automated access.
import hashlib
import time
from datetime import datetime, timezone
import requests
API_URL = "https://api.example.com/v1/jobs"
TOKEN = "YOUR_APPROVED_TOKEN"
session = requests.Session()
session.headers.update({
"Authorization": f"Bearer {TOKEN}",
"Accept": "application/json",
"User-Agent": "your-company-job-ingestor/1.0"
})
def canonical(job):
title = (job.get("title") or "").strip()
company = (job.get("company", {}).get("name") or "").strip()
locations = job.get("locations") or []
raw = f"{title}|{company}|{locations}|{job.get('description','')}"
return {
"source_job_id": str(job["id"]),
"title": title,
"company_name": company,
"locations": locations,
"description": job.get("description"),
"source_url": job.get("url"),
"posted_at": job.get("posted_at"),
"updated_at": job.get("updated_at"),
"raw_hash": hashlib.sha256(raw.encode()).hexdigest(),
"ingested_at": datetime.now(timezone.utc).isoformat()
}
def fetch_all():
page = 1
while True:
for attempt in range(4):
try:
response = session.get(
API_URL,
params={"page": page, "page_size": 100},
timeout=(10, 60)
)
if response.status_code == 429:
delay = int(response.headers.get("Retry-After", "10"))
time.sleep(min(delay, 120))
continue
response.raise_for_status()
payload = response.json()
break
except (requests.RequestException, ValueError):
if attempt == 3:
raise
time.sleep(2 ** attempt)
items = payload.get("jobs", [])
if not items:
return
for item in items:
if "id" in item:
yield canonical(item)
if not payload.get("next_page"):
return
page += 1
for record in fetch_all():
# Upsert by (source, source_job_id); apply the source policy before saving.
print(record["source_job_id"], record["title"])Use an idempotent upsert key of (source, source_job_id). If a source has no stable identifier, use a documented composite key and expect occasional merges. Store the raw response only when the terms allow it and when you have a defined deletion process.
Scheduling, change detection, and deletion
Polling
Schedule jobs according to the documented quota and update cadence, not according to how fast your workers can run. Add jitter so a fleet does not synchronize at the same second. Persist cursors or timestamps and request only changes when the API supports incremental synchronization.
Retries and rate limits
Retry network failures and transient 5xx responses with capped exponential backoff. Treat 401 and 403 as authorization or scope problems, not transient errors. Honor 429 responses and any published quota headers. Never increase concurrency to work around a limit.
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Implement a deletion queue separately from normal updates. It should handle source “closed” events, explicit deletion requests, expired retention windows, revoked authorization, and contract termination. Propagate deletion to search indexes, caches, exports, backups where required, and downstream customer copies that you control.
Testing without creating an unauthorized crawler
- Use a mocked API fixture or a sandbox supplied by the board.
- Test malformed JSON, missing IDs, duplicate pages, clock skew, and partial location data.
- Replay a fixture where a salary changes and verify a new hash and update event.
- Simulate 401, 403, 429, 500, timeout, and empty-page responses.
- Verify that a deletion event removes the record from every index and API response.
- Log request ID, endpoint, status, latency, page cursor, and record counts without logging access tokens or unnecessary personal data.
Common failures and fixes
| Symptom | Likely cause | Fix |
|---|---|---|
| 401 Unauthorized | Expired token, wrong audience, or missing scope. | Recheck the approved credentials and scopes; do not scrape a web session as a substitute. |
| 403 Forbidden | Account or application is not approved for that endpoint or use case. | Contact the platform’s developer program and confirm eligibility and stated purpose. |
| 429 Too Many Requests | Quota or burst limit exceeded. | Honor Retry-After, lower concurrency, add jitter, and use incremental sync. |
| Repeated jobs | Offset pagination shifted while listings changed. | Prefer cursor pagination; otherwise deduplicate by the source ID and record the retrieval window. |
| Stale listings | No update polling or failed cursor checkpoint. | Persist checkpoints transactionally and run a periodic reconciliation permitted by the source. |
| Fields disappear | Schema version changed or field is optional. | Version your adapter, validate contracts, and treat absent fields as unknown rather than empty facts. |
| Data remains after removal | Deletion handled in the primary table only. | Trace the record through caches, indexes, exports, backups, and downstream systems. |
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Use the documented options for full-page captures, CSS-selector elements, device and viewport settings, custom headers or cookies, waiting conditions, request blocking, caching TTLs, signed links, asynchronous webhooks, bulk capture of up to 100 URLs per call, and PDF output. These capabilities create an evidence image; they do not grant permission to collect or republish a job board’s data.
cURL (see the ScreenshotNeo documentation):
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webpPython:
import requests
r = requests.get("https://api.screenshotneo.com/v1/shot", params={"access_key": "YOUR_API_KEY", "url": "https://stripe.com"}, timeout=90)
open("shot.webp", "wb").write(r.content)Node.js:
const q = new URLSearchParams({ access_key: 'YOUR_API_KEY', url: 'https://stripe.com' });
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Cost, reliability, and security controls
- Cost: budget for API calls, storage, indexing, monitoring, and any approved partner fees. Delete fields you do not need instead of paying to retain them.
- Reliability: make ingestion idempotent, checkpoint progress, isolate source adapters, and expose freshness timestamps to users.
- Security: keep tokens in a secret manager, rotate them, restrict logs, encrypt stored data, and separate tenant data for client-facing products.
- Governance: assign an owner to review terms and documentation before launch and whenever the platform changes its program.
FAQ
Can I scrape job postings from LinkedIn?
LinkedIn’s published crawling terms prohibit automated crawling and indexing without express permission. Its Job Posting API requires vetting and approval, so use that approved route or do not automate collection.
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Is there an API for job listings?
LinkedIn has a vetted Job Posting API program, and Indeed publishes API and integration documentation. Availability, eligibility, and permitted uses depend on the exact product and your approved use case.
Can I republish collected listings?
Only if the applicable terms or contract allow your specific display or redistribution model. Approval to access data does not automatically authorize public or client-facing republication.
What should I retain for audits?
Keep authorization records, source and adapter versions, request metadata, policy decisions, deletion events, and the minimum payload needed to explain how a displayed listing was obtained.
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