# jiayihu/pretty-algorithms

🌊 Pretty, common and useful algorithms with modern JS and beautiful tests

Repository: https://github.com/jiayihu/pretty-algorithms
Canonical: https://ross.abutalabs.com/products/pretty-algorithms
Language: TypeScript
License: MIT
License Family: permissive
Topics: sorting-algorithms, sort, algorithms, computer-science, binary-trees
Last push: 2017-08-26T19:27:47+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": 3426, "days_push": 3294, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2169, forks 99 (observed 2026-08-28T04:06:21.554143+00:00)

## What it is
A collection of common algorithms (sorting, searching, dynamic programming) written in readable modern JavaScript/TypeScript with Jest snapshot tests. It is an educational repository meant for learning, not production use.

## Use cases
- learn sorting algorithms with readable code
- study binary search trees in javascript
- understand dynamic programming examples like rod cutting
- see jest snapshot testing applied to algorithms
- prepare for coding interviews in typescript

## When to choose
- you want clear, declarative implementations to learn from
- you prefer TypeScript annotations for clarity
- you want tested examples with real-world usage notes

## When to avoid
- you need performant algorithms for production
- you need a maintained, up-to-date library
- you need a comprehensive algorithm collection

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: developer-tools
- domain: education, programming-languages
- platform: cross-platform
- tags: algorithms, sorting, data-structures, typescript, jest, computer-science, educational, nodejs

## Member repositories
- jiayihu/pretty-algorithms (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:21.554143+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 2026-08-30T02:49:27.217632+00:00, confidence not recorded.
  - readme: https://github.com/jiayihu/pretty-algorithms (fetched 2026-08-28T04:06:21.554143+00:00, sha 36e336a7729b)
- Data as of 2026-08-30T08:39:29.467469+00:00.