# linsa-io/books

Awesome Books

Repository: https://github.com/linsa-io/books
Canonical: https://ross.abutalabs.com/products/linsa-io-books
License Family: other
Topics: books, education, list, resources, awesome, awesome-list, learning, learn-anything, free, pdf
Last push: 2026-03-04T15:38:20+00:00

## Health v2 (maintenance only)
Score: 64/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 70, release rhythm 35, longevity 100
- inputs: {"age_days": 3376, "days_push": 182, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7607, forks 819 (observed 2026-08-28T04:10:01.950961+00:00)

## What it is
A curated awesome-list of books organized by category, from algorithms and computer science to philosophy and fiction. Each entry notes the publication year and whether the book is free, sorted newest to oldest.

## Use cases
- find free programming books
- curated list of computer science books
- books to learn machine learning
- free pdf books by topic
- reading list for learning algorithms
- find books on a subject

## When to choose
- you want a broad, community-curated index of books across many topics
- you specifically want free or open books marked clearly
- you want books sorted by year within each category

## When to avoid
- you need actual book content or hosting, not just links
- you want ratings or reviews to guide selection
- you need a narrowly focused, deeply curated list for one topic

## Facets
- artifact type: dataset
- maturity: active
- function: documentation, developer-tools
- domain: education, awesome-lists, tutorials
- platform: -
- tags: awesome-list, books, curated-list, free-resources, pdf, learning-resources, web-server

## Member repositories
- linsa-io/books (main) score 64

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:01.950961+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:36:50.902772+00:00, confidence not recorded.
  - readme: https://github.com/linsa-io/books (fetched 2026-08-28T04:10:01.950961+00:00, sha 69db707ef84a)
- Data as of 2026-08-30T08:39:29.467469+00:00.