# chapin666/books

Awesome Books

Repository: https://github.com/chapin666/books
Canonical: https://ross.abutalabs.com/products/chapin666-books
License Family: other
Topics: linux, algorithm, database, protocol, language-learning, mq, operating-system
Last push: 2021-05-22T13:38:21+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3633, "days_push": 1929, "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 1252, forks 430 (observed 2026-08-28T04:04:08.336714+00:00)

## What it is
A curated collection of programming and computer science e-books (mostly PDFs, largely in Chinese) covering algorithms, operating systems, databases, DevOps, and languages like Go, JavaScript, and Erlang. It is a reading resource repository rather than software.

## Use cases
- find free programming ebooks
- learn algorithms from beginner books
- study unix and linux system programming
- learn go language from pdf books
- find kubernetes and docker learning material
- learn javascript and es6 in depth

## When to choose
- you want a curated list of downloadable programming books
- you prefer Chinese-language technical books
- you need broad coverage from algorithms to DevOps in one place

## When to avoid
- you need software or code, not reading material
- you require only legally distributed or English-language books
- you need actively updated content

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation
- domain: developer-tools, tutorials, awesome-lists, programming-languages, operating-systems, databases
- platform: cross-platform
- tags: ebooks, pdf-books, awesome-list, chinese-language, programming-books, computer-science, algorithms, devops

## Member repositories
- chapin666/books (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:08.336714+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 2026-08-30T05:07:32.397078+00:00, confidence not recorded.
  - readme: https://github.com/chapin666/books (fetched 2026-08-28T04:04:08.336714+00:00, sha f55cbabc083a)
- Data as of 2026-08-30T08:39:29.467469+00:00.