Internshala Scraper: Internships & Jobs in India (Stipends, Salaries, WFH)

Internshala Scraper extracts public internship and job listings from Internshala (internshala.com), India's largest internship and fresher-jobs board. Each listing comes back as clean, structured data: title, company, cities, work-from-home and hybrid flags, internship duration, stipend parsed into numbers (min, max, currency, per month / week / lump sum), job salary in INR per year, post-internship job offers ("upto ₹ 6 LPA" becomes 600000), experience, skills, categories and an approximate posted date.

Internships and jobs in one Actor, with category, city and work-from-home as simple input fields. It reads only Internshala's public listing pages (the pages robots.txt allows; no detail-page crawling, no login), so runs are fast, cheap and stable. Turn on Only new listings and schedule it to get a feed of fresh postings. You only pay for the listings you get, with no start fee.

What data can you get?

Field	Example	Internships	Jobs
type, id, url	internship, 3327276, listing link	✅	✅
title, companyName, companyLogoUrl	Python Development, Vaultedge Software	✅	✅
locations	["Malappuram", "Kochi"]	✅	✅
isWorkFromHome, isHybrid	true, false	✅	✅
duration	3 Months	✅	–
stipendText, stipendMin, stipendMax, stipendCurrency, stipendPeriod	₹ 25,000 - 30,000 /month → 25000, 30000, INR, month	✅	–
jobOfferText, jobOfferMaxSalary	Job offer upto ₹ 9LPA → 900000	✅	–
salaryText, salaryMin, salaryMax, salaryCurrency	₹ 2,00,000 - 4,00,000 /year → 200000, 400000	–	✅
experienceText, experienceMinYears	1 year(s) → 1	–	✅
postedText, postedAt	3 days ago → 2026-10-31	✅	✅
isActivelyHiring, isPartTime, isProExclusive, labels	Fresher Job, Be an early applicant, International	✅	✅
skills, moreSkillsCount, tags	Python, Django; +5 more; Web Development	✅	✅
descriptionSnippet	First lines of "About the job"	✅	✅
category, searchUrl, scrapedAt	python-django, the listing page, timestamp	✅	✅

Every item has the same keys; fields that don't apply are null.

Use cases

• Internship and fresher-job feeds for colleges, placement cells, Telegram/WhatsApp channels and career newsletters.
• Stipend and salary research: compare paid internships by city or skill, or track entry-level salaries in Mumbai, Bangalore or Delhi.
• Hiring-market intelligence: which companies are actively hiring interns for data science, marketing or web development.
• Lead lists for EdTech and HR-tech: companies posting internships (company names only, no personal contacts).
• Job aggregators: merge Internshala with other boards through the stable id and url.

How to use

1. Choose Listing type: Internships or Jobs.
2. Type a Category (e.g. python-django, Data Science, Marketing), a City (e.g. Bangalore), and/or tick Work from home only. Or paste Internshala listing URLs into Start URLs.
3. Set Max listings (default 100) and click Start. Download the results as JSON, CSV or Excel, or get them through the API.

Input examples

Data science internships in Bangalore:

{ "listingType": "internships", "category": "Data Science", "location": "Bangalore", "maxItems": 100 }

Work-from-home content writing internships:

{ "listingType": "internships", "category": "content-writing", "workFromHome": true, "maxItems": 100 }

Marketing jobs in Mumbai:

{ "listingType": "jobs", "category": "marketing", "location": "Mumbai", "maxItems": 200 }

Any Internshala listing pages, as a daily "only new" feed:

{
  "startUrls": [
    { "url": "https://internshala.com/internships/internship-in-bangalore/" },
    { "url": "https://internshala.com/jobs/marketing-jobs/work-from-home/" }
  ],
  "maxItems": 500,
  "onlyNew": true,
  "stateKey": "bangalore-and-wfh-marketing"
}

Output example

Real items from a local run (trimmed):

[
  {
    "type": "internship",
    "id": "3325928",
    "url": "https://internshala.com/internship/detail/work-from-home-part-time-python-development-internship-at-nayepankh-foundation1793278766",
    "title": "Python Development",
    "companyName": "NayePankh Foundation",
    "locations": [],
    "isWorkFromHome": true,
    "duration": "1 Month",
    "stipendText": "Unpaid",
    "stipendMin": 0,
    "stipendMax": 0,
    "stipendPeriod": null,
    "jobOfferText": "Job offer post internship",
    "postedText": "4 days ago",
    "postedAt": "2026-10-30",
    "isActivelyHiring": true,
    "isPartTime": true,
    "labels": ["Job offer post internship", "Part time"],
    "skills": ["HTML", "CSS", "Python", "Django", "Machine Learning", "REST API", "Flask"],
    "tags": ["Web Development", "Python/Django", "Information Technology", "Computer Science"],
    "category": "python-django",
    "scrapedAt": "2026-11-03T10:00:53.486Z"
  },
  {
    "type": "job",
    "id": "3313889",
    "url": "https://internshala.com/job/detail/fresher-associate-campaign-management-operations-support-job-in-mumbai-at-cre8rai-grunmech-technologies-private-limited1791802626",
    "title": "Associate - Campaign Management & Operations Support",
    "companyName": "Cre8r.ai (Grunmech Technologies Private Limited)",
    "locations": ["Mumbai"],
    "isWorkFromHome": false,
    "salaryText": "₹ 2,00,000 - 4,00,000 /year",
    "salaryMin": 200000,
    "salaryMax": 400000,
    "salaryCurrency": "INR",
    "experienceText": "No experience required",
    "experienceMinYears": 0,
    "postedText": "3 weeks ago",
    "postedAt": "2026-10-13",
    "labels": ["Be an early applicant", "Fresher Job"],
    "skills": ["Marketing", "Marketing Campaigns"],
    "category": "marketing",
    "scrapedAt": "2026-11-03T10:00:43.972Z"
  }
]

The full sample, with every field, is in samples/sample-output.json. The dataset has three views: Overview, Internships (stipend columns) and Jobs (salary columns).

Pricing

Pay per event, no start fee and no subscription:

Event	Price
listing: one internship or job listing saved to the dataset	$0.001

1,000 listings ≈ $1.00; a daily feed of 50 new internships ≈ $0.05 per day. Listings skipped by Only new listings and duplicates are never charged. Set Maximum cost per run in the run options and the scraper stops cleanly at your budget.

Tips and limits

• Category and city spelling. Use Internshala's names: python-django, web-development, data-science, content-writing, marketing, graphic-design; cities like Bangalore, Mumbai, Delhi, Gurgaon. If Internshala doesn't know a category, it redirects to its generic page; the scraper detects this, warns you and skips that input instead of returning unrelated listings. When in doubt, open the page on internshala.com and paste its URL into Start URLs.
• Work from home + city. Internshala shows remote listings plus listings in that city for this combination.
• Listing-card data only. Detail pages are disallowed by Internshala's robots.txt, so this Actor doesn't fetch them. That means no full description (only the first lines), no start date, no number of openings and no applicant counts. Cards show up to 7 skills; moreSkillsCount says how many more exist.
• postedAt is approximate: computed from relative text like "2 weeks ago".
• Totals. Internshala's page title count (e.g. "219 internships") can be higher than the listings it actually pages through. The scraper follows pages until the last one. Max listings applies to the whole run, across all inputs.
• Speed. About 40-50 listings per request, one request per second: 100 listings in 3-4 seconds.

FAQ

Do I need an Internshala account, cookies or a proxy? No. Listing pages are public. The proxy option is only for the case where Internshala starts blocking requests from Apify's servers; then enable Apify Proxy (datacenter). Residential proxies are not supported: if you pick the RESIDENTIAL group, the scraper logs a warning and uses Apify datacenter proxy instead.

Why is a stipend 0? The internship is unpaid. stipendMin/stipendMax are null when the card has no amount (e.g. "Performance based").

Are job salaries really per year? Yes. Internshala shows job salaries as annual INR (e.g. ₹ 3,00,000 - 5,00,000 /year); LPA values are converted (4.5 LPA = 450000) and monthly figures are multiplied by 12. Internship stipends keep their own period in stipendPeriod.

How does "Only new listings" work? The Actor remembers the listing ids it has output (per State key) in a named key-value store. The next run skips, and doesn't charge, any listing it has seen. Ids not seen for 90 days are forgotten.

What happens if Internshala blocks the run? The run stops with a clear message ("Internshala returned HTTP 403/429 or a page without listings...") and the run summary (RUN_SUMMARY in the key-value store) records it.

Is it legal to scrape Internshala? The Actor collects only public listings that companies publish to attract applicants, from pages Internshala's robots.txt allows. It doesn't log in and collects no personal contact data (no emails, phone numbers or applicant data). You are responsible for making sure your use complies with Internshala's terms and the laws that apply to you, including India's DPDP Act.

Integrations

• API: run it and fetch results with the Apify API or the JavaScript / Python clients:

  curl -X POST "https://api.apify.com/v2/acts/rjmacarthy~internshala-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \
    -H "Content-Type: application/json" \
    -d '{"listingType":"internships","category":"python-django","maxItems":50}'
  

• Make, Zapier, n8n: send new internships to Google Sheets, Airtable, Slack, Telegram or email with no code.

• Webhooks: trigger your pipeline when a run finishes.

• AI agents (MCP): use the Actor as a tool through the Apify MCP server.

Changelog

• 0.1 (Nov 2026): First release. Internships and jobs, category / city / work-from-home filters, start URLs, parsed stipends and salaries, only-new mode.

More scrapers by the same developer

• AI Visibility Tracker: ChatGPT, Perplexity, Gemini, Claude
• Google Ads Transparency Scraper
• Substack Scraper
• Telegram Channel Scraper
• ATS Jobs Scraper: Greenhouse, Lever, Ashby & Workday
• Dice Jobs Scraper

Browse all my Actors on my Apify Store profile.

Support

Found a listing page that doesn't work, or need another field? Open an issue on the Issues tab with your input. Fixes are usually quick.