rmp-api 0.1.2

Python wrapper for the RateMyProfessors GraphQL API

rmp-api

A Python library for querying the RateMyProfessors GraphQL API. Search for professors, fetch their ratings, and compute quality signals from the data.

No API key required. No scraping. Requires Python 3.10+.

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What it does

• Search for schools and professors by name
• Fetch individual student ratings with comments, grades, tags, and difficulty scores
• Compute quality signals: recency-weighted rating, reliability score, easiness, would-take-again rate
• Compare multiple professors side-by-side on any signal
• Track how a professor's score has changed over time (by year, semester, or quarter)
• Filter ratings by course code, keyword, or delivery format

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Documentation

Full docs at docs.aidentran.dev/rmp-api/ (Getting Started, API Reference, Examples, Troubleshooting).

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Installation

pip install rmp-api

Or with uv:

uv add rmp-api

Or clone and install locally:

git clone https://github.com/AidenTran900/rmp-api.git
cd rate-my-prof-api
pip install -e .

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Quick start

from rmp_api import (
    search_schools,
    search_professors,
    get_professor_summary,
    get_all_ratings,
    get_courses,
    filter_ratings_by_keywords,
    compute_score,
)

# 1. Find a school
schools = search_schools("UC Berkeley")
school_id = schools[0].id

# 2. Find a professor
professors = search_professors("John DeNero", school_id)
professor_id = professors[0].id

# 3. Quick aggregate summary (single request, no pagination)
summary = get_professor_summary("John DeNero", school_id)
print(summary.avg_rating)               # 4.2
print(summary.avg_difficulty)           # 2.8
print(summary.would_take_again_percent) # 92.0
print(summary.link)                     # https://www.ratemyprofessors.com/professor/...

# 4. Courses taught
courses = get_courses(professor_id)
print(courses[:3])  # [{'courseName': 'CS61A', 'courseCount': 42}, ...]

# 5. All ratings (auto-paginated); filter to a course
ratings = get_all_ratings(professor_id, course_filter="CS61A")

# 6. Filter by keyword
hard_ratings = filter_ratings_by_keywords(ratings, "hard")

# 7. Compute quality signals
score = compute_score(ratings)
print(score.composite_score)  # 0.82
print(score.raw_avg_rating)   # 4.1
print(score.top_tags[:3])     # [('Respected', 14), ('Clear grading', 11), ...]

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Notes

• Uses RateMyProfessors' public GraphQL endpoint. No auth required.
• This wraps an unofficial API!!! It may break if RMP changes their internal schema.
• Ratings are returned newest first.
• Results are cached per process. Call .cache_clear() on search_schools, search_professors, or get_courses to invalidate.
• RMP may rate-limit heavy requests. Add time.sleep(0.5) between calls when fetching many professors.

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Built off snow4060/rmp-api.