# liyue201/gostl

Data structure and algorithm library for go, designed to provide functions similar to C++ STL

Repository: https://github.com/liyue201/gostl
Canonical: https://ross.abutalabs.com/products/gostl
Language: Go
License: MIT
License Family: permissive
Topics: list, vector, deque, queue, stack, set, rbtree, multiset, bitmap, sort, bloomfilterr, hamt, skiplist, stl, ketama
Last push: 2025-08-28T14:05:11+00:00

## Health v2 (maintenance only)
Score: 50/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 39, release rhythm 35, longevity 100
- inputs: {"age_days": 2518, "days_push": 370, "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 1138, forks 115 (observed 2026-08-28T04:03:43.982700+00:00)

## What it is
GoSTL is a data structure and algorithm library for Go that mirrors the C++ STL, providing containers like vector, deque, rbtree, skiplist, and bloom filter plus algorithms like sort and binary search. Most data structures support optional goroutine-safe operation via configuration.

## Use cases
- use C++ STL-style containers in Go
- need a red-black tree or skiplist in Go
- goroutine-safe queue, stack, or deque
- consistent hashing with ketama in Go
- bloom filter or bitmap implementation
- sort and binary search with custom comparators

## When to choose
- you miss STL-style containers and iterators when writing Go
- you need specialized structures like HAMT, skiplist, or rbtree with thread-safety options

## When to avoid
- Go's built-in slices and maps already cover your needs
- you want a minimal dependency-free solution

## Facets
- artifact type: library
- maturity: active
- function: data-science, developer-tools
- domain: developer-tools
- platform: go
- tags: stl, data-structures, algorithms, red-black-tree, skiplist, bloom-filter, ketama, goroutine-safe, containers, iterators

## Member repositories
- liyue201/gostl (main) score 50

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:43.982700+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 2026-08-30T06:36:09.860273+00:00, confidence not recorded.
  - readme: https://github.com/liyue201/gostl (fetched 2026-08-28T04:03:43.982700+00:00, sha e74ebf01d310)
- Data as of 2026-08-30T08:39:29.467469+00:00.