RateMyProfessors Scraper

Pull professor profiles and the individual student ratings behind them from RateMyProfessors — average quality, difficulty, would-take-again %, top tags, and every comment with its course, grade, and post date. Search a whole school, look up professors by name, or paste profile URLs, and get back clean, linked records. Built for education researchers, EdTech product teams, and academic-advising tools that need professor sentiment at scale without copy-pasting profiles one page at a time.

Why This Scraper?

• Two linked record types in one run — every job returns professor profile rows plus individual rating rows, joined by professorId and professorLegacyId, so you can pivot from a professor's 4.3 average straight to the hundreds of comments behind it.
• The three headline metrics, pre-parsed — a 0–5 average quality rating, a 0–5 average difficulty score, and the would-take-again percentage on every professor, alongside the total rating count.
• Full per-rating breakdown — each student rating carries the course code, a 1–5 quality score, a 1–5 difficulty score, the free-text comment, the reported letter grade, and the post date in clean ISO 8601.
• Grade, textbook, credit, online, and attendance signals — each rating exposes whether a textbook was used, whether the class was for credit, whether it was online, and the attendance-mandatory flag — context you can filter and segment on.
• Top-tags aggregation — up to 5 most-used tags per professor (e.g. "Tough grader", "Gives good feedback", "Get ready to read"), ranked by frequency across their reviews.
• Community helpfulness on every review — thumbs-up and thumbs-down counts per rating, so you can weight comments by peer agreement instead of treating every review equally.
• Three ways to target data — scrape a whole school (by name or numeric RateMyProfessors ID), search professors by name (optionally narrowed to one school), or paste /professor/ and /school/ URLs directly, all mixable in a single run.
• Independent, predictable caps — maxProfessors and maxRatingsPerProfessor are separate controls, so a 50-professor / 100-ratings run stays predictable instead of hiding behind one blurry combined limit.
• Pipeline-ready IDs — every professor ships both the stable RateMyProfessors ID and the numeric legacyId, plus a ready-to-open profileUrl, so downstream re-lookups and follow-up runs chain cleanly.

Use Cases

Academic Research

• Study grade-inflation and student-sentiment trends across departments or entire schools.
• Compare would-take-again rates and difficulty scores between institutions.
• Build longitudinal datasets from rating post dates spanning multiple academic years.

EdTech & Product

• Seed course-planning and professor-matching apps with structured ratings.
• Enrich scheduling tools with quality and difficulty scores plus top tags.
• Power "best professor for this course" recommendation features.

Student Advising & Course Planning

• Flag high-difficulty, low-would-take-again sections before registration.
• Surface a professor's most-used tags so students know what to expect.
• Aggregate course-level feedback by class code across a department.

Reputation & Sentiment Analysis

• Track how a department's ratings evolve over time.
• Mine free-text comments for recurring themes with your own NLP.
• Weight consensus using thumbs-up counts on individual reviews.

Lead Generation (Tutoring & Services)

• Identify high-difficulty courses where tutoring demand is strongest.
• Target schools and departments by average difficulty.
• Build outreach lists segmented by school and department.

Getting Started

Scrape one school (summaries only)

{
  "schools": ["Arizona State University"],
  "maxProfessors": 25,
  "includeRatings": false
}

Find a professor by name, narrowed to a school, with ratings

{
  "schools": ["University of California Los Angeles"],
  "professorNames": ["Andrew Ng"],
  "maxProfessors": 20,
  "includeRatings": true,
  "maxRatingsPerProfessor": 50
}

Paste URLs directly and pull deep ratings

{
  "startUrls": [
    "https://www.ratemyprofessors.com/professor/1936365",
    "https://www.ratemyprofessors.com/school/1234"
  ],
  "maxProfessors": 100,
  "includeRatings": true,
  "maxRatingsPerProfessor": 200
}

Input Reference

What to Scrape

Fill in any combination — everything you populate runs in one job.

Parameter	Type	Default	Description
schools	array	["Arizona State University"]	School names (e.g. Arizona State University) or numeric RateMyProfessors school IDs (e.g. 15723). Pulls every professor at each school. Also narrows the professor-name search below.
professorNames	array	[]	Professor names to search for (e.g. John Smith). Returns matching profiles. Add a school above to narrow the search to that campus.
startUrls	array	[]	RateMyProfessors professor URLs (/professor/<id> → that professor) or school URLs (/school/<id> → all its professors). Type is detected automatically.

Results

Parameter	Type	Default	Description
maxProfessors	integer	50	Maximum professors to collect per school or per name search. Set to 0 for as many as available. Ignored for direct professor URLs (those return one professor each).

Ratings

Parameter	Type	Default	Description
includeRatings	boolean	true	Also collect each professor's individual student ratings (comment, course, quality and difficulty scores, grade, tags, and more), added as separate linked rows. Turn off for professor summaries only.
maxRatingsPerProfessor	integer	100	Maximum ratings to collect per professor when ratings are enabled. Set to 0 for all available. Popular professors can have hundreds to over a thousand ratings.

Output

Every run writes to one Overview tab with all records, plus clean Professors and Ratings tabs that are type-filtered subsets. Each row carries a recordType field so you can split them anywhere.

Professor record

{
  "recordType": "professor",
  "professorId": "VGVhY2hlci0xOTM2MzY1",
  "legacyId": 1936365,
  "firstName": "Jane",
  "lastName": "Doe",
  "fullName": "Jane Doe",
  "department": "Computer Science",
  "schoolId": "U2Nob29sLTE1NzIz",
  "schoolLegacyId": 15723,
  "schoolName": "Arizona State University",
  "avgRating": 4.3,
  "avgDifficulty": 3.1,
  "numRatings": 214,
  "wouldTakeAgainPercent": 88,
  "topTags": ["Gives good feedback", "Caring", "Respected", "Clear grading criteria", "Inspirational"],
  "profileUrl": "https://www.ratemyprofessors.com/professor/1936365"
}

Field	Type	Description
recordType	string	Always "professor"
professorId	string	Stable RateMyProfessors professor ID (use for joins)
legacyId	integer	Numeric professor ID used in the profile URL
firstName	string	Professor's first name
lastName	string	Professor's last name
fullName	string	Combined first and last name
department	string	Department the professor teaches in
schoolId	string	Stable RateMyProfessors school ID
schoolLegacyId	integer	Numeric school ID
schoolName	string	School name
avgRating	number	Average overall quality rating (0–5)
avgDifficulty	number	Average difficulty (0–5)
numRatings	integer	Total number of student ratings on the profile
wouldTakeAgainPercent	number	Percent of students who would take the professor again (null when unrated)
topTags	array	Up to 5 most-used rating tags, ranked by frequency
profileUrl	string	Direct link to the professor's RateMyProfessors page

Rating record

Present only when Include Student Ratings is enabled. One row per student rating, linked back to its professor.

{
  "recordType": "rating",
  "ratingId": "UmF0aW5nLTM4MjE0NTk=",
  "professorId": "VGVhY2hlci0xOTM2MzY1",
  "professorLegacyId": 1936365,
  "professorName": "Jane Doe",
  "schoolName": "Arizona State University",
  "class": "CSE110",
  "qualityRating": 5,
  "difficultyRating": 3,
  "comment": "Clear lectures and fair exams. Attend every class and you'll do well.",
  "date": "2026-03-10T18:02:47Z",
  "grade": "A",
  "wouldTakeAgain": true,
  "attendanceMandatory": "mandatory",
  "textbookUse": true,
  "isForCredit": true,
  "isForOnlineClass": false,
  "tags": ["Clear grading criteria", "Gives good feedback"],
  "thumbsUp": 12,
  "thumbsDown": 1
}

Rating & review

Field	Type	Description
recordType	string	Always "rating"
ratingId	string	Unique rating ID
professorId	string	Parent professor ID (join key back to the professor row)
professorLegacyId	integer	Parent professor numeric ID (join key)
professorName	string	Parent professor's full name (standalone context)
schoolName	string	School name (standalone context)
class	string	Course code the rating is for (e.g. CSE110)
qualityRating	number	Student's quality score (1–5)
difficultyRating	number	Student's difficulty score (1–5)
comment	string	Free-text review comment
date	string	Post date in ISO 8601 UTC (e.g. 2026-03-10T18:02:47Z)

Course context & feedback

Field	Type	Description
grade	string	Letter grade the student reported receiving
wouldTakeAgain	boolean	Whether the student would take the professor again
attendanceMandatory	string	Attendance flag (mandatory / non mandatory / null)
textbookUse	boolean	Whether a textbook was used
isForCredit	boolean	Whether the class was taken for credit
isForOnlineClass	boolean	Whether it was an online class
tags	array	Tags the student applied to this rating
thumbsUp	integer	Helpful (thumbs-up) count from the community
thumbsDown	integer	Not-helpful (thumbs-down) count

Tips for Best Results

• Skip search with direct URLs — paste /professor/<id> or /school/<id> links to jump straight to exactly the professors or schools you want, with no name matching in the way.
• Use a numeric school ID for exact targeting — school names go through a fuzzy match, but the numeric ID (the number in a /school/<id> URL) always resolves to the exact campus.
• Turn off ratings for a fast, cheap professor census — you still get every average rating, difficulty, would-take-again %, and top tags, without the per-professor rating pull.
• Cap maxRatingsPerProfessor for predictable costs — popular professors can have 1,000+ ratings; a cap of 50–100 keeps runs fast. Set it to 0 only when you truly need the full history.
• Add a school to narrow a professor-name search — putting a school in the Schools field limits "John Smith" to that campus instead of every John Smith across North America.
• Keep ratings on if tags matter — RateMyProfessors often leaves the profile-level tag list empty, so top tags are rebuilt from the individual ratings; they populate best when ratings are enabled.
• Start small, then scale — run 10–25 professors first to confirm the school and fields look right, then raise maxProfessors.

Pricing

From $0.80 per 1,000 professors + $0.20 per 1,000 ratings. You're charged per professor profile plus per student rating collected — a dual model that keeps summary-only runs cheap and only adds rating cost when you ask for ratings. No compute or time-based charges; you pay per professor and per rating collected, plus a small fixed per-run start fee.

Bronze, Silver, and Gold discount tiers apply automatically based on your Apify subscription plan — the higher your tier, the less you pay per result.

Per 1,000 professors collected

Volume	No discount	Bronze	Silver	Gold
100 professors	$0.095	$0.090	$0.085	$0.080
1,000 professors	$0.95	$0.90	$0.85	$0.80
10,000 professors	$9.50	$9.00	$8.50	$8.00
100,000 professors	$95.00	$90.00	$85.00	$80.00

Per 1,000 student ratings collected

Volume	No discount	Bronze	Silver	Gold
100 ratings	$0.024	$0.022	$0.021	$0.020
1,000 ratings	$0.24	$0.22	$0.21	$0.20
10,000 ratings	$2.40	$2.20	$2.10	$2.00
100,000 ratings	$24.00	$22.00	$21.00	$20.00

Example totals at Gold pricing

Run	Professors	Ratings	Professor cost	Rating cost	Total
100 professors × 20 ratings each	100	2,000	$0.08	$0.40	$0.48
500 professors × 40 ratings each	500	20,000	$0.40	$4.00	$4.40

A "result" is one professor profile or one student rating. Turn off Include Student Ratings to pay for professors only. Platform usage fees are additional.

Integrations

Export data in JSON, CSV, Excel, XML, or RSS. Connect to 1,500+ apps via:

• Zapier / Make / n8n — Workflow automation
• Google Sheets — Direct spreadsheet export
• Slack / Email — Notifications on new results
• Webhooks — Trigger custom APIs on run completion
• Apify API — Full programmatic access

Legal & Ethical Use

This scraper collects publicly available information from RateMyProfessors. Use the data responsibly and in compliance with RateMyProfessors' terms of service and all applicable laws, including data-protection regulations such as GDPR and CCPA. Student ratings are user-generated opinions — treat them as subjective commentary, not statements of fact, and do not use the data to harass, defame, or make automated decisions about individuals. You are responsible for how you use the data you collect.