ratemyprofessors-client 0.1.0

A Python API Client for RateMyProfessors.

RateMyProfessors API Client

Typed, retrying, rate-limited unofficial client for RateMyProfessors, with optional helpers for ingestion workflows (sentiment, dedupe, course-code normalization).

Note: This library is unofficial and may break if RMP changes their internal API. This library has been made open-source so that if/when there are any changes, someone is able to take note of these changes and help to contribute an update.

Installation

pip install ratemyprofessors-client

With optional sentiment extras (TextBlob):

pip install 'ratemyprofessors-client[sentiment]'

Quickstart

from rmp_client import RMPClient

SCHOOL_ID = 1466  # example: Queen's University ID on RMP

with RMPClient() as client:
    for prof in client.iter_professors_for_school(SCHOOL_ID, page_size=20):
        print(prof.name, prof.overall_rating, prof.num_ratings)

Fetch details and iterate ratings incrementally:

from datetime import date
from rmp_client import RMPClient

with RMPClient() as client:
    professor = client.get_professor("PROFESSOR_ID")

    for rating in client.iter_professor_ratings(professor.id, since=date(2024, 1, 1)):
        print(rating.date, rating.quality, rating.comment)

Extras

Optional helpers live under rmp_client.extras:

• rmp_client.extras.sentiment.analyze_sentiment
• rmp_client.extras.dedupe.normalize_comment / is_valid_comment
• rmp_client.extras.course_codes.build_course_mapping

See docs/ and examples/ for more. This repo also includes an examples/ingest_supabase.py script that mirrors a Supabase-centric scraping pipeline using this client.

Publishing to PyPI

This project follows the Python Packaging User Guide and uses PyPI Trusted Publishing with GitHub Actions.

1. One-time setup: On pypi.org add a trusted publisher for this repo (workflow publish-to-pypi.yml, environment pypi). Create a pypi environment in the repo and enable “Required reviewers” for production releases.
2. Release: Create and push a tag (e.g. v0.1.0). The workflow builds both a wheel and an sdist and publishes to PyPI. Any push builds and publishes to TestPyPI (use the testpypi environment).

Local build (no publish):

pip install build
python -m build
# Outputs in dist/: .whl (wheel) and .tar.gz (sdist)