# keon/algorithms

Minimal examples of data structures and algorithms in Python

Repository: https://github.com/keon/algorithms
Canonical: https://ross.abutalabs.com/products/keon-algorithms
Homepage: http://keon.kim/algorithms/
Language: Python
License: MIT
License Family: permissive
Topics: algorithm, python, competitive-programming, data-structure, algorithms, sort, search, tree, graph
Last push: 2026-08-01T08:02:17+00:00

## Health v2 (maintenance only)
Score: 88/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 95, release rhythm 71, longevity 100
- inputs: {"age_days": 3576, "days_push": 32, "days_rel": 197, "gap_med": 0, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 25542, forks 4717 (observed 2026-08-28T04:11:38.252399+00:00)

## What it is
A collection of minimal, clean, well-documented implementations of data structures and algorithms in Python 3, installable via pip. Each module is self-contained with docstrings, type hints, and complexity notes, designed primarily for learning and reference.

## Use cases
- learn data structures and algorithms in python
- prepare for coding interviews
- study algorithm implementations with complexity notes
- reference implementations of sorting, searching, and graph algorithms
- practice competitive programming problems
- understand dynamic programming and backtracking with examples

## When to choose
- you want readable, educational Python implementations of classic algorithms
- you need a pip-installable library of algorithm examples for study
- you are preparing for technical interviews or coursework

## When to avoid
- you need production-grade, highly optimized algorithm implementations
- you require algorithms in a language other than Python
- you need a comprehensive algorithms library with advanced data structures

## Facets
- artifact type: learning-resource
- maturity: stable
- function: developer-tools, documentation
- domain: education, programming-languages, tutorials
- platform: python, cross-platform
- tags: data-structures, interview-prep, competitive-programming, pypi-package, educational, algorithms

## Member repositories
- keon/algorithms (main) score 88

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:38.252399+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 2026-08-29T16:56:02.292165+00:00, confidence not recorded.
  - readme: https://github.com/keon/algorithms (fetched 2026-08-28T04:11:38.252399+00:00, sha 227447aa502f)
  - homepage: http://keon.kim/algorithms/ (fetched 2026-08-29T07:52:45.157901+00:00, sha e6a73aac0d93)
  - registry_pypi: https://pypi.org/pypi/algorithms/json (fetched 2026-08-29T07:52:45.166677+00:00, sha f5d989df134e)
- Data as of 2026-08-30T08:39:29.467469+00:00.