"Gopher Holds The Rules"

import "github.com/hyperjumptech/grule-rule-engine"

Grule is a Rule Engine library for Golang programming language. Inspired by the acclaimed JBOSS Drools, done in a much simple manner.

Like Drools, Grule have its own DSL comparable as follows.

Drools's DRL be like :

rule "SpeedUp"
    salience 10
    when
        $TestCar : TestCarClass( speedUp == true && speed < maxSpeed )
        $DistanceRecord : DistanceRecordClass()
    then
        $TestCar.setSpeed($TestCar.Speed + $TestCar.SpeedIncrement);
        update($TestCar);
        $DistanceRecord.setTotalDistance($DistanceRecord.getTotalDistance() + $TestCar.Speed)
        update($DistanceRecord)
end

And Grule's GRL be like :

rule SpeedUp "When testcar is speeding up we keep increase the speed." salience 10  {
    when
        TestCar.SpeedUp == true && TestCar.Speed < TestCar.MaxSpeed
    then
        TestCar.Speed = TestCar.Speed + TestCar.SpeedIncrement;
        DistanceRecord.TotalDistance = DistanceRecord.TotalDistance + TestCar.Speed;
}

There are no better explanation compared to the article authored by Martin Fowler. You can read the article here (RulesEngine by Martin Fowler).

Taken from TutorialsPoint website (with very slight modification),

Grule is Rule Engine or a Production Rule System that uses the rule-based approach to implement and Expert System. Expert Systems are knowledge-based systems that use knowledge representation to process acquired knowledge into a knowledge base that can be used for reasoning.

A Production Rule System is Turing complete with a focus on knowledge representation to express propositional and first-order logic in a concise, non-ambiguous and declarative manner.

The brain of a Production Rules System is an Inference Engine that can scale to a large number of rules and facts. The Inference Engine matches facts and data against Production Rules – also called Productions or just Rules – to infer conclusions which result in actions.

A Production Rule is a two-part structure that uses first-order logic for reasoning over knowledge representation. A business rule engine is a software system that executes one or more business rules in a runtime production environment.

A Rule Engine allows you to define “What to Do” and not “How to do it.”

(also taken from TutorialsPoint)

Rules are pieces of knowledge often expressed as, "When some conditions occur, then do some tasks."

When
   <Condition is true>
Then
   <Take desired Action>

The most important part of a Rule is its when part. If the when part is satisfied, the then part is triggered.

rule  <rule_name> <rule_description>
   <attribute> <value> {
   when
      <conditions>

   then
      <actions>
}

Rules make it easy to express solutions to difficult problems and get the solutions verified as well. Unlike codes, Rules are written in less complex language; Business Analysts can easily read and verify a set of rules.

The data resides in the Domain Objects and the business logic resides in the Rules. Depending upon the kind of project, this kind of separation can be very advantageous.

By using Rules, you create a repository of knowledge (a knowledge base) which is executable. It is a single point of truth for business policy. Ideally, Rules are so readable that they can also serve as documentation.

Since business rules are actually treated as data. Adjusting the rule according to business dynamic nature become trivial. No need to re-build codes, deploy as normal software development do, you only need to roll out sets of rule and apply them to knowledge repository.

• Tutorial. Follow this simple tutorial to use Grule ASAP
• Rule Engine. For those who want to know how Rule Engine works
• GRL. A bit more in-depth about GRL structures and syntax.
• RETE Algorithm. Explain how RETE algorithm implemented in Grule.
• Functions. List of built-in function and how to to call your own function from GRL.

Yes. We need contributor to make Grule even better and useful to Open Source Community.

• Need to do more and more and more test.
• Better code coverage test.
• Better commenting for go doc best practice.
• Improve function argument handling to be more fluid and intuitive.

If you really want to help us, simply Fork the project and apply for Pull Request. Please read our Contribution Manual and Code of Conduct