# hyperjumptech/grule-rule-engine

Rule engine implementation in Golang

Repository: https://github.com/hyperjumptech/grule-rule-engine
Canonical: https://ross.abutalabs.com/products/grule-rule-engine
Language: Go
License: NOASSERTION
License Family: other
Topics: golang, rule-engine, rule, inference-engine, rule-based, rule-based-engine, hacktoberfest, hacktoberfest2021
Last push: 2026-02-10T00:34:37+00:00

## Health v2 (maintenance only)
Score: 65/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 66, release rhythm 45, longevity 100
- inputs: {"age_days": 2455, "days_push": 205, "days_rel": 369, "gap_med": 13.5, "n_releases_24m": 5}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2522, forks 373 (observed 2026-08-28T04:06:58.410089+00:00)

## What it is
Grule is a rule engine library for Go, inspired by JBoss Drools, with its own Domain-Specific Language (GRL) for defining production rules. It provides an inference engine that matches facts against rules to implement rule-based expert systems.

## Use cases
- implement business rules in a Go application
- build an expert system with an inference engine
- separate decision logic from application code
- evaluate conditions and trigger actions declaratively
- replace hardcoded if-else chains with a rules engine
- port Drools-style rule systems to Go

## When to choose
- you need a Drools-like production rule system in Go
- business rules change frequently and must be externalized from code
- you want a DSL for declarative rule authoring

## When to avoid
- simple conditional logic that doesn't justify a rule engine
- you need a mature ecosystem like Drools on the JVM
- your project isn't written in Go

## Facets
- artifact type: library
- maturity: active
- function: interpreter, parser, developer-tools
- domain: developer-tools
- platform: go, cross-platform
- tags: rule-engine, inference-engine, drools-inspired, dsl, expert-system, business-rules, automation, algorithms

## Member repositories
- hyperjumptech/grule-rule-engine (main) score 65

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:58.410089+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 2026-08-30T02:25:47.832603+00:00, confidence not recorded.
  - readme: https://github.com/hyperjumptech/grule-rule-engine (fetched 2026-08-28T04:06:58.410089+00:00, sha 7907947b9959)
- Data as of 2026-08-30T08:39:29.467469+00:00.