# m9rco/algorithm-php

🍭🍭uniting the internal work in a way that is in PHP

Repository: https://github.com/m9rco/algorithm-php
Canonical: https://ross.abutalabs.com/products/algorithm-php
Language: PHP
License: MIT
License Family: permissive
Topics: php7, arithmetic, php, phper, learning, php-library, php5, composer
Last push: 2023-12-08T06:48:31+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3364, "days_push": 999, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1376, forks 484 (observed 2026-08-28T04:04:33.200743+00:00)

## What it is
A collection of classic algorithms and data structures implemented in PHP, covering sorting, searching, data structures, and miscellaneous algorithm puzzles. It serves as a learning resource for PHP developers studying algorithms.

## Use cases
- learn sorting algorithms in php
- study data structures like stacks and binary search trees with php examples
- prepare for php coding interviews
- find php implementations of dijkstra or kmp
- understand dynamic programming with php code
- reference algorithm implementations in php

## When to choose
- you are a PHP developer learning algorithms from working code
- you want readable reference implementations of classic algorithms in PHP
- you are preparing for interviews and prefer PHP examples

## When to avoid
- you need production-grade, performance-optimized algorithm libraries
- you work in a language other than PHP
- you need actively maintained or extensively tested code

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools
- domain: programming-languages, tutorials
- platform: php, cross-platform
- tags: algorithms, data-structures, sorting, searching, php, interview-prep, educational, education

## Member repositories
- m9rco/algorithm-php (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:33.200743+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 2026-08-30T04:40:30.737825+00:00, confidence not recorded.
  - readme: https://github.com/m9rco/algorithm-php (fetched 2026-08-28T04:04:33.200743+00:00, sha 90474c3b89bf)
- Data as of 2026-08-30T08:39:29.467469+00:00.