# OpenGenus/cosmos

World's largest Contributor driven code dataset | Used in Quark Search Engine, @OpenGenus IQ, OpenGenus Visual Project

Repository: https://github.com/OpenGenus/cosmos
Canonical: https://ross.abutalabs.com/products/opengenus-cosmos
Homepage: http://internship.opengenus.org
Language: C++
License: GPL-3.0
License Family: copyleft
Topics: opengenus, algorithm, datastructures, library, offline-app, interview-questions, sorting-algorithms, search-algorithms, hacktoberfest, internship, internships, hacktoberfest-accepted, hacktoberfest2022, hacktoberfest2023, hacktoberfest2024
Last push: 2024-10-05T22:20:46+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": 3273, "days_push": 697, "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 13742, forks 3657 (observed 2026-08-28T04:11:04.717640+00:00)

## What it is
Cosmos is a large community-contributed collection of algorithm and data structure implementations in many languages including C++, Java, Python, Go, and JavaScript. It serves as an offline code dataset used in OpenGenus projects like the Quark Search Engine and IQ.

## Use cases
- study algorithms and data structures offline
- prepare for coding interviews with categorized problem lists
- find reference implementations of sorting, searching, and dynamic programming algorithms
- contribute to a large open-source algorithm library
- browse algorithm solutions across multiple programming languages

## When to choose
- you need reference implementations of classic algorithms in multiple languages
- you are preparing for technical interviews and want categorized problem sets
- you want an offline collection of algorithm code
- you want a beginner-friendly open-source contribution project

## When to avoid
- you need a production-ready, performance-tested algorithm library for a real application
- you need a single-language, package-installable library with a stable API
- you need actively maintained, correctness-guaranteed code for critical systems

## Facets
- artifact type: dataset
- maturity: active
- function: developer-tools, documentation
- domain: education, developer-tools
- platform: cross-platform
- tags: algorithms, data-structures, interview-preparation, offline-code-dataset, educational, hacktoberfest

## Member repositories
- OpenGenus/cosmos (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:04.717640+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 2026-08-29T17:13:04.234616+00:00, confidence not recorded.
  - readme: https://github.com/OpenGenus/cosmos (fetched 2026-08-28T04:11:04.717640+00:00, sha 12df56581813)
- Data as of 2026-08-30T08:39:29.467469+00:00.