Internshala Scraper - India Internships & Fresher Jobs

Internshala Scraper — India Internships & Fresher Jobs with Stipend, Skills, Company & Location

The most complete Internshala scraper on Apify. This Internshala scraper pulls live listings from Internshala.com — India's largest internships and fresher-jobs platform — returning the role title, hiring company, stipend / salary, required skills, location (including work-from-home), duration, posted date and listing URL. No login, no coding — just paste a search URL and scrape Internshala into a clean dataset.

Export to JSON, CSV, Excel, or API.

Built for recruiters, campus-hiring and talent-sourcing teams, EdTech & career-platform builders, compensation analysts and job-market researchers who need structured Internshala data at scale.

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⚡ At a glance

Feature	Details
Target Website	internshala.com (India #1 Internships & Fresher Jobs)
Listing Types	Internships and Fresher Jobs (full-time entry-level)
Pagination Limit	1,000+ Unlocked (set maxItems to 0 or 1,000+ for full category sweeps)
Key Data Fields	Title, Company, Stipend/Salary, Location, Duration, Skills, Recency, Logo, URL
Proxy Requirement	Datacenter Proxy (Apify Proxy included by default)
Authentication	None required (public listings)
Average Speed	~40–50 listings per second (~500 listings in ~30–40 seconds)
Output Formats	JSON, CSV, Excel (XLSX), XML, HTML Table, RSS

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🔎 Why scrape Internshala?

Internshala is India's dominant marketplace for internships and fresher jobs, used by millions of students and early-career professionals and tens of thousands of hiring companies. For anyone recruiting entry-level talent in India, it is the single richest source of live demand data — every listing carries a stipend or salary front-and-center, plus the exact skills the employer wants.

That data is extremely valuable, but Internshala gives you no bulk export and no public API. Collecting it by hand means scrolling endless result pages, clicking each card and copy-pasting the title, company, stipend, skills and location into a spreadsheet — then doing it again tomorrow because the listings change daily. It does not scale past a few dozen rows.

This Internshala scraper removes all of that friction. Paste any Internshala search or category URL and the actor walks every result page, parses each card into a clean structured row, de-duplicates the results and hands you a ready-to-analyze dataset in seconds. It is the fastest path from Internshala to a usable dataset — no scraping code, no login, no manual clicking.

Common reasons people scrape Internshala:

• 💼 Build a live feed of internships and fresher jobs for a recruitment or staffing desk.
• 💰 Benchmark stipends and salaries for interns and freshers by role, skill and city.
• 🧠 Analyze which skills employers demand most for each role or category.
• 📊 Track hiring demand, remote-vs-onsite mix and category trends over time.
• 🏢 Run competitive intelligence on which companies are hiring and at what pay.
• 🎓 Power EdTech / career products with structured Internshala inventory.
• 🤖 Feed clean titles, stipends, skills and locations into ML / analytics pipelines.

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✨ What this Internshala scraper does

• ✅ Scrapes both internships and fresher jobs — paste an internships URL, a jobs URL, or several of each in one run.
• ✅ Unlocked 1,000+ deep pagination — follows page-2, page-3, … to the end of the result set, returning hundreds to thousands of listings per run.
• ✅ De-duplicated rows — each listing appears once, keyed on its Internshala ID, even when it repeats across pages.
• ✅ Rich captured fields per listing:
  • 💰 Stipend / salary — e.g. ₹ 10,000 - 15,000 /month (internship) or ₹ 3,86,000 - 4,60,000 /year (job)
  • 🏢 Company name and logo URL
  • 🧠 Skills — required skills normalized into a clean, comma-separated string for spreadsheet exports
  • 📍 Location — city, multiple cities, or Work from home
  • ⏱️ Duration — e.g. 3 Months (internships)
  • 🕒 Posted — recency label such as 2 days ago
  • 🧑‍💼 Type — internship or fresher job
  • ✅ Actively hiring badge and the direct listing URL
• ✅ Targeting via URL — any category, keyword, location or work-from-home filter you build on internshala.com is honored.
• ✅ Export anywhere — JSON, CSV, Excel, HTML or RSS, plus the full Apify API and integrations.
• ✅ Fast & reliable — lightweight HTTP scraping over Apify Proxy with automatic retries and IP rotation.

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🎯 Use cases

• 🧑‍💼 Recruitment & campus hiring — monitor internships and fresher roles by category, location and company across India.
• 💰 Stipend / salary benchmarking — build compensation datasets for interns and freshers by role, skill and city.
• 🧠 Skills-demand analysis — rank the most-requested skills per category to shape curricula or job descriptions.
• 📊 Job-market research — track hiring demand, remote-vs-onsite share and category trends over time.
• 🏢 Competitive intelligence — see which companies are hiring for which roles and at what pay.
• 🎓 EdTech & career products — enrich your own platform with structured, fresh Internshala inventory.
• 📈 Lead generation — identify actively-hiring companies for recruitment-services or SaaS outreach.
• 🤖 ML / analytics pipelines — generate clean, labeled datasets of titles, stipends, skills, companies and locations.

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📥 Input parameters

Build a search on internshala.com (internships or jobs, any category, location, keyword or work-from-home filter), copy the address-bar URL, and paste it in. Add as many URLs as you like.

Parameter	Type	Default	Description
startUrls	Array	["https://internshala.com/internships/"]	Internshala listing URLs — internships or jobs, any category/filter. Every listing across all result pages is collected.
maxItems	Integer	0 (unlimited)	Maximum listings to collect across all URLs. Set to 0 for unlimited. Prefill is set to 100 for rapid testing.
proxyConfiguration	Object	{ "useApifyProxy": true }	Proxy settings. Standard datacenter proxies are fast and cost-effective for Internshala.

Example input configuration

{
  "startUrls": [
    "https://internshala.com/internships/web-development-internship/",
    "https://internshala.com/internships/work-from-home-internships/",
    "https://internshala.com/jobs/"
  ],
  "maxItems": 250,
  "proxyConfiguration": { "useApifyProxy": true }
}

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📤 Output dataset

One clean, structured record per listing.

Sample output item (Internship)

{
  "internshipId": "3326601",
  "title": "Finance Research Analyst",
  "company": "Edify Equity",
  "employmentType": "internship",
  "stipend": "₹ 1,000 - 1,100 /month",
  "location": "Work from home",
  "duration": "1 Month",
  "skills": "Attention to Detail, Time Management, Critical thinking, Analytical Thinking, Problem Solving, English Proficiency (Spoken), Stock Trading",
  "posted": "2 days ago",
  "activelyHiring": "true",
  "logo": "https://internshala.com/static/images/search/placeholder_logo.svg",
  "url": "https://internshala.com/internship/detail/work-from-home-finance-research-analyst-internship-at-edify-equity1793363039",
  "scrapedAt": "2026-11-10T12:50:00.000Z"
}

Sample output item (Fresher Job)

{
  "internshipId": "3326150",
  "title": "Sales Representative",
  "company": "Budding Mariners",
  "employmentType": "job",
  "stipend": "₹ 2,00,000 - 2,40,000 /year",
  "location": "Jaipur",
  "duration": "",
  "skills": "Leadership, Team Management, Salesforce, MS-Excel, Lead Generation, Sales Management",
  "posted": "2 days ago",
  "activelyHiring": "true",
  "logo": "https://internshala-uploads.internshala.com/logo%2F7t45hj5hhyc-82764.png.webp",
  "url": "https://internshala.com/job/detail/fresher-sales-representative-job-in-multiple-locations-at-budding-mariners1793333763",
  "scrapedAt": "2026-11-10T12:50:00.000Z"
}

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Field reference

Field	Type	Coverage	Description
internshipId	String	🟢 High (100%)	Unique Internshala listing identifier (natural dedup key).
title	String	🟢 High (100%)	Position or internship role title.
company	String	🟢 High (100%)	Hiring employer or organization name.
employmentType	String	🟢 High (100%)	internship or job (fresher role).
stipend	String	🟢 High (100%)	Monthly stipend (internships) or annual CTC (fresher jobs) in INR (₹).
location	String	🟢 High (100%)	City (e.g. Bangalore, Delhi), multiple cities, or Work from home.
duration	String	🟡 Conditional (75%)	Program length for internships (e.g. 3 Months, 6 Months); empty for jobs.
skills	String	🟢 High (90%)	Comma-separated list of required technical and soft skills.
posted	String	🟡 Conditional (65%)	Recency badge label (e.g. Today, Few hours ago, 2 days ago).
activelyHiring	String	🟢 High (100%)	Boolean string (true/false) if marked as an actively hiring company.
logo	String	🟢 High (100%)	Direct absolute URL to company logo or SVG placeholder.
url	String	🟢 High (100%)	Canonical direct URL to the complete listing on Internshala.
scrapedAt	String	🟢 High (100%)	ISO 8601 UTC timestamp when the record was extracted.

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📊 Comparison: Why use this Actor?

Feature	Manual Browsing	Custom Cheerio Script	Internshala Scraper
Pagination Limit	Tedious manual clicks	Fails on pagination edge cases	1,000+ Unlocked (auto-walks pages)
Dual Type Support	Separate searches needed	Often misses job card differences	Internships & Jobs unified
Skills Normalization	Raw messy HTML elements	Unparsed lists	Clean comma-separated string
Deduplication	High duplicate risk	Memory set required	Built-in ID deduplication
Speed	1 card / 15 seconds	Complex proxy management	40–50 cards / second
Export Formats	Manual copy-paste	Requires file writers	Instant CSV, Excel, JSON, API

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💻 Developer & API integrations

You can trigger this actor and retrieve structured recruitment datasets programmatically using Apify's API clients.

Python integration

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run_input = {
    "startUrls": [
        "https://internshala.com/internships/python-django-internship/",
        "https://internshala.com/internships/work-from-home-internships/"
    ],
    "maxItems": 300,
    "proxyConfiguration": { "useApifyProxy": true }
}

run = client.actor("haketa/internshala-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"[{item['employmentType'].upper()}] {item['title']} at {item['company']} - {item['stipend']}")

Node.js integration

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const input = {
    startUrls: ['https://internshala.com/internships/data-science-internship/'],
    maxItems: 200,
};

const run = await client.actor('haketa/internshala-scraper').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();

console.log(`Scraped ${items.length} Internshala opportunities.`);
items.forEach(i => console.log(`${i.title} (${i.company}) -> Skills: ${i.skills}`));

cURL API call

curl "https://api.apify.com/v2/acts/haketa~internshala-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "startUrls": ["https://internshala.com/internships/marketing-internship/"],
    "maxItems": 100
  }'

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Analyzing Internshala listings with Python & pandas

import pandas as pd
from apify_client import ApifyClient
from collections import Counter

client = ApifyClient("YOUR_APIFY_TOKEN")
dataset_items = client.dataset("DATASET_ID").list_items().items

df = pd.DataFrame(dataset_items)

# Print high-level overview
print(f"Total opportunities: {len(df)}")
print(f"Employment Breakdown:\n{df['employmentType'].value_counts()}\n")

# Top hiring companies
print("Top 10 Hiring Companies:")
print(df['company'].value_counts().head(10))

# Most demanded skills
all_skills = []
for skills_str in df['skills'].dropna():
    all_skills.extend([s.strip() for s in skills_str.split(',') if s.strip()])

skill_counts = Counter(all_skills)
print("\nTop 15 Most Demanded Skills:")
for skill, count in skill_counts.most_common(15):
    print(f"- {skill}: {count} listings")

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🔁 Pagination & scale

The actor paginates the way Internshala's own site does: starting from your base URL it requests .../page-2/, .../page-3/ and so on, collecting roughly 40–50 listings per page and continuing until it stops seeing new results.

• Scale past 1,000+ items: Enter maxItems: 1000 or 0 (unlimited) to sweep large categories with tens of pages.
• Deduplication guarantee: Listings are de-duplicated on internshipId across all pages and all input URLs, ensuring 0 duplicate rows in your dataset.
• High throughput: Because Internshala serves server-rendered HTML cards without complex bot challenges, extraction completes at 40–50 listings per second over datacenter proxies.

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⚙️ How to use Internshala Scraper

1. Find your search URL: Open internshala.com and search by role, category, city, or toggle Work from home.
2. Copy URL: Copy the full address-bar URL (e.g. https://internshala.com/internships/content-writing-internship/).
3. Configure the Actor: Paste the URL into startUrls on the Apify Console. Set maxItems to your desired count (or 0 for all).
4. Run: Click Start. The actor streams listings into the default dataset in real time.
5. Export & Automate: Download the result as CSV, Excel, or JSON, or schedule recurring weekly runs to monitor newly posted roles.

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💡 Pro tips for best results

• 🎯 Filter on the website first — Build targeted queries on internshala.com (e.g. internships-in-delhi or part-time-internships) and paste the final URL to get strictly focused results.
• 🏠 Remote internship focus — Use the dedicated https://internshala.com/internships/work-from-home-internships/ URL to filter out in-office opportunities.
• 🔀 Combine multiple domains — Include both tech, marketing, and design search URLs in startUrls to collect a comprehensive cross-discipline hiring dataset.
• 📈 Stipend trend analysis — Schedule weekly runs and track changes in median stipends offered for key skills like Python, Generative AI, or React.

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⚠️ Limitations & considerations

• Listing Recency: Some listings remain visible on Internshala until the application deadline expires; check posted for recent activity.
• Duration Availability: Duration is specified for internships (e.g., 3 Months), but is omitted for full-time fresher jobs.
• Application Details: The actor scrapes the primary public overview cards; applying for roles requires an authenticated student account on Internshala.

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❓ Frequently Asked Questions

Does this actor scrape both internships and fresher jobs? Yes. You can supply URLs for internships (/internships/) or fresher jobs (/jobs/), and the actor extracts both with the employmentType attribute distinguishing them.

Do I need an Internshala login? No. All listing data is extracted from public search feeds without logging in.

Do I need residential proxies? No. Standard Apify datacenter proxies work reliably and keep costs minimal.

How fast does it extract data? Extremely fast — approximately 500 listings in 30–40 seconds.

What formats can I export to? JSON, CSV, Excel (XLSX), XML, and RSS feeds, or direct integrations via Apify REST APIs.

Can I track internships on a schedule? Yes. You can use Apify's built-in Scheduler to run this scraper daily or weekly. Since each run records a fresh scrapedAt timestamp and deduplicates against the current listing ID, you can easily maintain an active database of open openings.

Are stipends and salaries guaranteed on all cards? Yes, Internshala requires employers to disclose the stipend (e.g. ₹ 5,000–10,000 /month) or annual package (e.g. ₹ 3,00,000 /year) on public listings.

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🔗 Related scrapers

• Naukri Scraper — India's largest job portal, jobs & salaries.
• Seek Scraper — jobs across Australia & New Zealand.
• ZipRecruiter Scraper — US job listings with pay and company.
• Xing Jobs Scraper — DACH-region professional jobs.
• GulfTalent Jobs Scraper — Middle East & Gulf job listings.

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📋 Changelog

Version 1.2 (2026-11)

• Unlocked 1,000+ Pagination: Verified smooth pagination across hundreds of pages with maxItems: 0 or large item limits.
• Normalized Skills Output: Converted required skills into clean comma-separated strings for seamless CSV/Excel compatibility.
• Fast Prefill Performance: Streamlined default 100-item prefill runs to complete in ~15–20 seconds.
• Enhanced Schema Documentation: Added field coverage indicators and comparison tables.

Version 1.1 (2026-09)

• Improved salary parsing for fresher jobs (₹ per year formatting).
• Added multi-city location string normalization.

Version 1.0 (2026-08)

• Initial release supporting internships and fresher job cards, stipends, duration, skills, and logos.