We extract college rankings, fee structures, cutoff scores, placement statistics, and student reviews from Collegedunia. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for College Profiles objects from collegedunia.com. All fields typed and schema-versioned.
"college_id": "CD-1029", "name": "IIT Bombay", "location": "Mumbai", "state": "Maharashtra", "establishment_year": 1958, "ownership_type": "Public", "cd_rating": 9.1, "total_courses": 84
| # | college_id | name | location | state | establishment_year | ownership_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Courses & Fees objects from collegedunia.com. All fields typed and schema-versioned.
"course_id": "C-4921", "college_id": "CD-1029", "course_name": "B.Tech Computer Science", "degree_level": "Undergraduate", "duration_years": 4, "first_year_fee": 228000, "total_fee": 912000, "admission_exam": "JEE Advanced"
| # | course_id | college_id | course_name | degree_level | duration_years | first_year_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Cutoffs & Exams objects from collegedunia.com. All fields typed and schema-versioned.
"cutoff_id": "CT-992", "college_id": "CD-1029", "course_name": "B.Tech Computer Science", "exam_name": "JEE Advanced", "year": 2023, "category": "General", "round_number": 6, "closing_rank": 67
| # | cutoff_id | college_id | course_name | exam_name | year | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Placements objects from collegedunia.com. All fields typed and schema-versioned.
"placement_id": "PL-2023-1029", "college_id": "CD-1029", "year": 2023, "highest_package": 36700000, "average_package": 2182000, "total_recruiters": 384, "top_recruiters": "['Microsoft', 'Google', 'Optiver']"
| # | placement_id | college_id | year | highest_package | average_package | median_package |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Student Reviews objects from collegedunia.com. All fields typed and schema-versioned.
"review_id": "REV-84729", "college_id": "CD-1029", "course_enrolled": "B.Tech Mechanical Engineering", "graduation_year": 2022, "overall_rating": 8.8, "placement_rating": 9.0, "review_title": "Excellent campus life and academics", "date_posted": "2023-11-14"
| # | review_id | college_id | reviewer_name | course_enrolled | graduation_year | overall_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Collegedunia scraper handles deep directory traversal: institution profiles, nested fee structures, historical cutoff tables, and paginated review feeds with JavaScript execution built in.
Extract basic info, approvals, ownership type, and CD rating across 36,000+ colleges.
Capture first year versus total fees across all undergraduate and postgraduate variants.
Extract historical opening and closing ranks for JEE, NEET, CAT, and state-level exams.
Record highest packages, average packages, and top participating recruiters per institution.
Pull granular ratings across campus life, faculty, and placements from verified student reviews.
Extract faculty counts, hostel fees, campus size, and available facilities.
Monitor exam dates, syllabus links, and lists of participating colleges for major entrance tests.
Extract eligibility criteria, award amounts, and sponsor details mapped to specific institutions.
Run annual bulk exports for admission seasons or configure continuous pipelines for review feeds.
Resilient selectors handle changing DOM structures across different college profile templates.
Brief in. Clean data out.
Provide target states, specific exams, or course categories. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management for collegedunia.com.
Schema validation, null-rate checks, and sample data reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Scraping large directory sites requires handling complex pagination, nested JSON payloads, and dynamic tables. Here is how we build resilient extraction.
Cutoffs and fee structures are rendered dynamically based on user filters. We intercept and parse the underlying JSON payloads rather than scraping the DOM, ensuring accurate data capture across all filter combinations.
Navigating 36,000 colleges requires strict memory management and crawl frontier deduplication. Our Scrapy spiders traverse state, city, and course taxonomies without missing obscure institutions.
Student reviews are heavily paginated. We extract the full corpus including sub-ratings for faculty, placements, and campus life, standardising date formats and removing duplicate entries.
High-concurrency crawls trigger rate limits. We use Indian residential proxies to distribute requests naturally, avoiding IP bans and ensuring continuous pipeline operation during peak admission seasons.
We maintain a hash index of last-seen values for fee structures and placement stats. Subsequent runs only push diffs, reducing downstream processing load for your engineering team.
Populate competing education portals with baseline college metadata, fee structures, and course availability.
Sales agencies identifying colleges and institutions for B2B software, infrastructure, or service sales.
Analysts tracking fee inflation, intake capacity changes, and placement trends across tier 2 and tier 3 cities.
Building internal tools for admission probability calculations based on historical cutoff ranks.
Banks assessing college tiers and placement statistics to structure targeted student loan products.
Tracking new course introductions, accreditation updates, and campus expansion metrics across states.
"Collegedunia holds the most comprehensive taxonomy of Indian higher education, but extracting historical cutoffs and nested fee structures requires purpose-built infrastructure."
Directory scraping seems trivial until you hit dynamic tables, inconsistent schema across colleges, and aggressive rate limiting. DataFlirt manages the proxy rotation, JavaScript hydration, and schema normalisation so your team receives clean, queryable education data.
Everything supported by our collegedunia.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering for dynamic tables and nested filters.
We maintain pools of Indian residential proxies to navigate rate limits and geo-restrictions during high-volume directory crawls.
Pipelines run on AWS ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About collegedunia.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated college data, fees, and reviews. We do not extract personal contact details or bypass OTP verification walls.
We use Indian residential proxies and strict concurrency controls. Request timing is modelled on human behaviour to avoid triggering aggressive bot protection systems.
Placement statistics and fee structures are typically updated annually. We can run full catalogue refreshes on a monthly cadence, or configure targeted pipelines for real-time student review extraction.
Yes. We parse the dynamic tables to extract opening and closing ranks across multiple counselling rounds and categories for exams like JEE, NEET, and CAT.
Engagements typically start at a defined scope, such as all engineering colleges in specific states, or all institutions participating in a specific entrance exam. Contact us for a scoped quote.
Yes. We provide a sample run of up to 100 college profiles with associated courses and fee structures so you can validate the schema before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full export of 36,000 colleges or a targeted feed of engineering cutoffs, we scope, build, and operate the pipeline. Tell us what you need.
