The Internshala API: what breaks a run, and what it costs

There is no official Internshala API. The unofficial one may work for an afternoon, then a challenge page appears, a response comes back empty, or a list stops paging. Yesterday's successful run returns nothing today.

Here is what our Internshala Actor handles, how much a run costs, and where it stops.

Doing it yourself

Building your own scraper makes sense for a single snapshot or when a failed run has no consequences. The work involved is less simple. These specifics come directly from the problems our scraper handles.

The front door. When measured on 2026-08-22, Internshala served a plain request normally (200, nginx). Reaching the page is not the difficult part. Pagination and parsing are—and both need to keep working.

Rate limits. Send requests aggressively enough and Internshala returns 429. Without backoff, the run becomes a queue of failures.

Proxies. Our runs use rotating proxies. A pattern from one IP is trivially detectable. Proxies are also usually the largest expense, costing far more than compute.

Pagination. Listings span multiple pages. Stopping when a page comes back empty is not reliable because a soft block can produce the same empty page.

Silent breakage. Internshala changes its markup without notice. Extraction can then fail quietly, producing empty fields instead of an error. Detecting that drift requires its own work.

Deduplication. Each rerun returns records already collected. Hashing every record and storing those hashes prevents the scraper from re-processing the entire dataset.

The real cost is upkeep. The first version takes an afternoon to write. After that, expect an hour of maintenance every few weeks, forever. Failures stay silent: you discover an empty report instead of receiving a scraper error.

These figures come from a measured run, not an estimate:

• 80 records in 7.7 seconds
• cost: $0.00059 — about $0.00742 per 1,000 records

The shortcut

If you do not want to maintain all of that, one call returns the same result:

```bash curl -X POST "https://api.apify.com/v2/acts/blackfalcondata~internshala-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \ -H 'Content-Type: application/json' \ -d '{"listingType": "..."}' ```

The Python version is:

```python from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN") run = client.actor("blackfalcondata~internshala-scraper").call(run_input={"listingType": "..."})

for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ```

What comes back

Each record contains 65 fields, organized into groups that include:

• description — description, descriptionHtml, descriptionMarkdown, descriptionLength
• salary — salaryMin, salaryMax, salaryCurrency, salaryPeriod
• job — jobId, jobKey, jobOfferText

What people use it for

• Benchmarking. Pricing and salary fields support comparisons across the full dataset instead of a page of results.
• Reputation monitoring. Changes in ratings and review text become visible over time, unlike a single page view.
• Lead lists. Company-level fields narrow the data to the relevant segment before anyone opens a CRM.
• Change detection. Timestamps make it possible to diff runs and work only with new records instead of reviewing everything again.
• Geographic analysis. Location fields enable market-by-market comparisons without another data source.

Where it stops

• Nothing here bypasses an Internshala login. Regardless of who writes the scraper, it covers public pages only.
• A scraper that works today may not work in six weeks. It usually fails silently instead of throwing an exception.
• Proxy costs rise with volume, yet people routinely leave them out of DIY estimates.

Questions people ask

Is scraping Internshala legal?

Reading publicly visible pages is generally treated differently from accessing data behind a login. US courts have repeatedly declined to treat public scraping as unauthorised access. This is not legal advice, and the law is separate from a site's terms of service. Data behind a login remains out of scope either way.

Why am I getting 403s when the page loads fine in my browser?

The URL is not the issue. Our probe sent a plain request to Internshala on 2026-08-22 and received a response from aws cloudfront; 0 of 3 attempts were refused. A browser succeeds because it supplies a TLS fingerprint, a cookie and a header set that a bare HTTP client lacks.

Do I need proxies?

Yes, for more than a small sample. A single origin IP is the simplest target for rate limits, and residential addresses receive different treatment from datacentre ones.

How often will it break?

Plan to revisit the scraper whenever Internshala releases a redesign. You may not notice immediately because extraction returns empty fields instead of errors. Allow an hour every few weeks, not one afternoon followed by no maintenance.

Is it cheaper to build it myself?

Only when your time costs nothing. The measured run below cost $0.00059 for 80 records. A DIY version adds proxy spending and a recurring maintenance hour.

Try it

If you prefer not to own the upkeep, our hosted Internshala API handles everything described above. New accounts receive $5 of free platform credit each month—enough to run a job of this size several times.

Disclosure: we build and maintain this Actor, and the link above is an affiliate link.

Further reading

• hiQ Labs v. LinkedIn — the appeals decision on scraping public pages
• Apify's API reference — the endpoints used above
• dataset storage — how results are stored and exported
• proxy documentation — what the proxy layer costs and offers
• Autoscout24 API — another scraper we build and document
• how the Trustpilot API responds — another scraper we build and document
• the Naukri API field reference — another scraper we build and document

We also publish the Internshala API endpoint and what it returns on blackfalcondata.com — the request, the response, and what a run costs.