We extract institution profiles, course fee structures, placement records, cutoff percentiles, and student reviews from Getmyuni. 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 getmyuni.com. All fields typed and schema-versioned.
"college_id": "GMU-7842", "college_name": "Indian Institute of Technology Madras", "location_city": "Chennai", "location_state": "Tamil Nadu", "established_year": 1959, "university_type": "Public", "approvals": "['AICTE', 'UGC']", "accreditation": "NAAC Grade A++", "campus_size_acres": 617
| # | college_id | college_name | location_city | location_state | established_year | university_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Courses & Fees objects from getmyuni.com. All fields typed and schema-versioned.
"course_id": "CRS-9921", "course_name": "B.Tech Computer Science and Engineering", "degree_type": "Undergraduate", "duration_years": 4, "study_mode": "Full Time", "total_fees_inr": 850000, "first_year_fees_inr": 215000, "exams_accepted": "['JEE Advanced']"
| # | course_id | college_id | course_name | degree_type | duration_years | study_mode |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Placements objects from getmyuni.com. All fields typed and schema-versioned.
"placement_year": 2025, "highest_package_inr": 19800000, "average_package_inr": 2140000, "median_package_inr": 1800000, "total_recruiters": 380, "placement_percentage": 94.5, "top_companies": "['Microsoft', 'Google', 'Amazon', 'Goldman Sachs']"
| # | college_id | placement_year | highest_package_inr | average_package_inr | median_package_inr | lowest_package_inr |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Cutoff Scores objects from getmyuni.com. All fields typed and schema-versioned.
"course_name": "B.Tech Computer Science", "exam_name": "JEE Main", "category": "General", "quota": "All India", "round_number": 6, "opening_rank": 142, "closing_rank": 894, "year": 2024
| # | college_id | course_name | exam_name | category | quota | round_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Student Reviews objects from getmyuni.com. All fields typed and schema-versioned.
"review_id": "REV-883920", "student_name": "Rahul S.", "course_enrolled": "MBA Marketing", "graduation_year": 2023, "overall_rating": 4.2, "placement_rating": 4.5, "faculty_rating": 4.0, "infrastructure_rating": 4.8, "review_date": "2025-11-12"
| # | review_id | college_id | student_name | course_enrolled | graduation_year | overall_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Getmyuni scraper navigates complex portal structures: dynamic fee tables, historical cutoff charts, placement records, and paginated student reviews. We handle the JavaScript rendering and session management required to extract complete datasets.
Extract approvals, accreditations (NAAC, NBA), establishment year, university affiliations, and campus size for every listed institution.
Capture year-wise breakdowns, total course fees, hostel charges, and NRI quota pricing across all undergraduate and postgraduate programs.
Extract highest, average, and median salary packages alongside lists of top recruiting companies and sector-wise placement percentages.
Track category-wise opening and closing ranks for major entrance exams like JEE, NEET, CAT, and state-level CETs across multiple counselling rounds.
Scrape granular ratings for faculty, infrastructure, and placements, along with full-text student reviews and graduation years.
Extract eligibility criteria, accepted entrance exams, application deadlines, and document requirements for specific courses.
Catalogue available facilities including libraries, sports complexes, hostels, cafeterias, and medical centres.
Capture NIRF rankings, NAAC grades, and internal Getmyuni ranking metrics across various academic disciplines.
Run continuous pipelines to track fee revisions, new cutoff releases during counselling seasons, and fresh student reviews.
Brief in. Clean data out.
Provide target states, degree types, or specific college URLs. We design the extraction schema together.
We configure Playwright crawlers, proxy rotation, and pagination handling for Getmyuni's dynamic portal.
Schema validation, null-rate checks on fee data, and sample review exports before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Indian education portals feature highly variable DOM structures and aggressive rate limiting. Here is how we maintain data integrity.
Portals like Getmyuni monitor traffic anomalies and block datacenter IPs. We route requests through residential proxies located in India to maintain high success rates and prevent IP bans during large-scale crawls.
Critical data like historical cutoff charts and detailed fee breakdowns are rendered client-side via JavaScript. Our Playwright instances execute the necessary scripts to ensure no data is left behind in the DOM.
College profile pages often use different layout templates depending on their premium status on the portal. We deploy multi-layered XPath and CSS fallback selectors to normalise data across all template variations.
Student reviews are loaded dynamically as the user scrolls. We script browser interactions to trigger API calls and capture the complete review corpus for institutions with thousands of entries.
We monitor extraction yields in real time. If a portal update causes fee or cutoff fields to return null values at an abnormal rate, the pipeline pauses and alerts our engineers for immediate selector maintenance.
Online degree providers track traditional university fee structures and placement records to position their programs competitively.
Education consultancies enrich their CRM data with accurate college details, accepted exams, and admission criteria to better advise students.
Researchers analyse long-term trends in engineering and medical cutoffs to map shifts in student preferences and institutional quality.
Aggregators ingest normalised fee and placement data to build independent comparison engines for prospective students.
Financial institutions use intake capacity and fee data to model the total addressable market for student loans in specific states.
Institutions process bulk student reviews through NLP models to identify operational issues in campus facilities or faculty performance.
"Getmyuni aggregates the fragmented landscape of Indian higher education. Extracting this data requires navigating thousands of inconsistent college templates."
Building a reliable pipeline for Indian education portals means handling heavy JavaScript rendering, aggressive rate limiting, and constantly shifting DOM structures. DataFlirt manages the proxy rotation and schema maintenance so your data team receives clean, normalised tables ready for analysis.
Everything supported by our getmyuni.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 manages JavaScript execution for dynamic charts and paginated reviews. Combined via middleware for optimal throughput.
We route traffic through verified Indian residential proxies. Rotation happens per-request to distribute load and mimic legitimate user behaviour across the portal.
Pipelines run on AWS Lambda for burst scaling during counselling seasons. Airflow manages dependencies and delivery schedules. State is maintained in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About getmyuni.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Getmyuni is generally permissible under Indian law. DataFlirt targets only public, non-authenticated college profiles, fee structures, and reviews. We do not extract personal student data or circumvent authentication walls. Clients should review Getmyuni's terms of service and consult legal counsel for specific use cases.
We use Playwright to execute JavaScript, hydrate React components, and script browser interactions. This allows us to trigger infinite scroll events on review pages and render dynamic cutoff charts exactly as a human user would.
Yes. We configure scheduled pipelines to monitor specific institutions or courses. Our change detection system compares new scrapes against historical state and delivers only the modified records.
Yes. College portals often present fees in unstructured text formats. We parse these strings into clean numeric fields (e.g. converting '2.5 Lakhs' to 250000) for immediate use in your database.
Our smallest packages start at a defined list of institutions (typically 500 to 5,000 colleges) with monthly delivery. For full catalogue extraction or high-frequency updates during admission seasons, we price based on compute volume.
Absolutely. We provide a sample run of up to 50 college profiles, including their associated courses and reviews, during the scoping phase. This allows your engineering team to validate the schema before signing a contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off dump of engineering colleges or a continuous feed of MBA cutoffs, we scope, build, and operate the pipeline. Tell us what you need.
