muricoca/crab
Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (numpy, scipy, matplotlib). observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 5616
- days_rel: n/a
- days_push: 2073
- n_releases_24m: 0
Adoption not part of the score
1175 stars · 368 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Crab is a Python recommender engine library integrating classic collaborative filtering and information filtering algorithms with the scientific Python stack (numpy, scipy, matplotlib). It provides components for building customized recommender systems.
Use cases
- build a recommendation engine in python
- collaborative filtering for user-item ratings
- recommend products to users based on similarity
- python library for recommender systems
- compute user and item based recommendations
When to choose
- you need classic collaborative filtering algorithms in Python
- you want a numpy/scipy-based recommender you can customize
When to avoid
- you need actively maintained software (last release 2020)
- you need deep learning based recommenders like implicit or LightFM
Facets
library · maturity abandoned
machine-learning search-engine machine-learning data-science python recommender-system collaborative-filtering information-filtering
1 source
- readme: https://github.com/muricoca/crab · fetched 2026-08-28 · 48fdf91a9ee3
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| muricoca/crab | main | 32 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem