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A rule engine written in Ruby.


This library contains a rule engine written in Ruby. It's based on the Rete algorithm and uses a DSL to express rules in a readable way.


Add this line to your application's Gemfile:

gem 'wongi-engine'

And then execute:

$ bundle

Or install it yourself as:

$ gem install wongi-engine


To begin, say

engine = Wongi::Engine.create

Now let's add some facts to the system.


All knowledge in Wongi::Engine is represented by triples of { subject, predicate, object }. Predicates usually stand for subjects' properties, and objects for values of those properties. More complex types can always be decomposed into such triples.

Triples can contain any Ruby object that defines the == comparison in a meaningful way, but some symbols have special meaning, as we will see.

Try this:

engine << [ "Alice", "friend", "Bob" ]
engine << [ "Alice", "age", 35 ]

To remove facts, say:

engine.retract [ "Alice", "age", 35 ]

What can we do with this information?

Simple iteration

Suppose we want to list all we know about Alice. You could, for instance, do:

engine.each "Alice", :_, :_ do |item|
    puts "Alice's #{item.predicate} is #{item.object}"

each takes three arguments for every field of a triple and tries to match the resulting template against the known facts. :_ is the special value that matches anything. This kind of pattern matching plays a large role in Wongi::Engine; more on that later.

In a similar way, you can use select to get an array of matching facts and find to get the first matching one. Both methods take three arguments.

Simple rules

It's not very interesting to use the engine like that, though. Rule engines are supposed to be declarative. Let's try this:

friends = engine.rule "friends" do
    forall {
        has :PersonA, "friend", :PersonB

Here's your first taste of the engine's DSL. A rule, generally speaking, consists of a number of conditions the dataset needs to meet; those are defined in the forall section (also spelled for_all, if you prefer that). has (or fact) specifies that there needs to be a fact that matches the given pattern; in this case, one with the predicate "friend".

When a pattern contains a symbol that starts with an uppercase letter, it introduces a variable which will be bound to an actual triple field. Their values can be retrieved from the result set:

friends.tokens.each do |token|
    puts "%s and %s are friends" % [ token[ :PersonA ], token[ :PersonB ] ]

A token represents all facts that passed the rule's conditions. If you think of the dataset as of a long SQL table being joined with itself, then a token is like a row in the resulting table.

If you don't care about a specific field's value, you can use the all-matcher :_ in its place so as not to introduce unnecessary variables.

Once a variable is bound, it can be used to match further facts within a rule. Let's add another friendship:

engine << [ "Bob", "friend", "Claire" ]

and another rule:

remote = engine.rule "remote friends" do
    forall {
        has :PersonA, "friend", :PersonB
        has :PersonB, "friend", :PersonC

remote.tokens.each do |token|
    puts "%s and %s are friends through %s" % [ token[ :PersonA ], token[ :PersonC ], token[ :PersonB ] ]

(engine.rule returns the created production node - an object that accumulates the rule's result set. You don't have to carry it around if you don't want to - it is always possible to retrieve it later as["remote friends"].)

Stored queries

Taking the SQL metaphor further, you can use the engine to do fancy searches:

q = engine.query "friends" do
    search_on :Name
    forall {
        has :Name, "friend", :Friend

engine.execute "friends", { Name: "Alice" }
q.tokens.each do |token|
    ... # you know the drill

Not that this is a particularly fancy search, but you get the idea.

Queries work the same way as normal rules, but they come with some variables already bound by the time matching starts.

You can also retrieve the query's production node from engine.results["friends"] (they are intentionally kept separate from regular productions).

Taking an action

There's more to rules than passive accumulation:

engine.rule "self-printer" do
    forall {
        has :PersonA, "friend", :PersonB
    make {
        action { |token|
            puts "%s and %s are friends" % [ token[ :PersonA ], token[ :PersonB ] ]

The make section (also spelled do!, if you find it more agreeable English, because do is a keyword in Ruby) lists everything that happens when a rule's conditions are fully matched (we say "the production node is activated"). Wongi::Engine provides only a small amount of built-in actions, but you can define your own ones, and the simplest one is just action with a block. The block will be executed in the engine's context.

More facts!

Note how our facts define relations that always go from subject to object - they form a directed graph. In a perfect world, friendships go both ways, but to specify this in our model, we need to have two facts for each couple. Instead of duplicating everything by hand, let's automate that:

engine.rule "symmetric predicate" do
    forall {
        has :Predicate, "symmetric", true
        has :X, :Predicate, :Y
    make {
        gen :Y, :Predicate, :X

engine << ["friend", "symmetric", true]

If you still have the "self-printer" rule installed, you will see some new friendships pop up immediately!

The built-in gen action creates new facts, taking either fixed values or variables as arguments. (It will complain if you provide a variable that isn't bound by the time it's activated.) Here, it takes all relations we've defined to be symmetric, finds all couples in those sorts of relations and turns them around.


It wouldn't be very useful if has were the only sort of condition that could be used. Here are some more:

neg subject, predicate, object

Passes if the specified template does not match anything in the dataset. Alias: missing.

maybe subject, predicate, object

Passes whether or not the template matches anything. It's only useful if it introduces a new variable; you can think of LEFT JOIN. Alias: optional.

none { ... }

The none block contains other matchers and passes if that entire subchain returns an empty set. In other words, it corresponds to an expression not ( a and b and ... ).

any { option { ... } ... }

The any block contains several option blocks, each of them containing other matchers. It passes if any of the option subchains matches. It's a shame that disjunction has to be so much more verbose than conjunction, but life is cruel.

same x, y

Passes if the arguments are equal. Alias: eq, equal.

diff x, y

Passes if the arguments are not equal. Alias: ne.

less x, y, greater x, y

Should be obvious by now.

assert { |token| ... }, assert var1, var2, ... do |val1, val2, ... | ... end

Passes if the block evaluates to true. Having no arguments passes the entire token as an argument, listing some variables passes only their values.

assign variable do |token| ... end

Not a matcher, strictly speaking, because it always passes. What it does instead is introduce a new variable bound to the block's return value.

Feedback loop prevention

Consider the following rule:

engine.rule "default value" do
    forall {
        neg :car, :colour, :_
    make {
        gen :car, :colour, "black"

The intent here is to provide a default value for an attribute; however, how will it actually execute?

  1. The fact is missing, activate the rule, generate the fact.
  2. The fact is present, invalidate the rule, retract the generated fact.
  3. The fact is missing...

...and so on until you get a stack overflow. In situations like this the engine will try to do the pragmatic thing and detect the loop, stopping after step 1. If you want to keep the "pure" behaviour, give the unsafe: true option to the neg rule and try to do the same thing with helper facts.

Note: this is a specific use case; it is still perfectly possible to construct more elaborate infinite cascades involving several rules that will not be caught.


Wongi::Engine has a limited concept of timed facts: time is discrete and only extends into the past. Matchers that accept a triple specification (has, neg and maybe) can also accept a time option, an integer <= 0, which will make them look at a past state of the system. "0" means the current state and is the default value, "-1" means the one just before the current, and so on.

To create past states, say:


This will shift all facts one step into the past. The new current state will be a copy of the last one. You can only insert new facts into the current state, "retroactive" facts are not allowed.

Time-aware matchers

The following matchers are nothing but syntactic sugar for a combination of primitives.

asserted subject, predicate, object

Short for:

has subject, predicate, object, time: 0
neg subject, predicate, object, time: -1

That is, it passes if the fact was missing in the previous state but exists in the current one. Alias: added.

retracted subject, predicate, object

Short for:

has subject, predicate, object, time: -1
neg subject, predicate, object, time: 0

The reverse of asserted. Alias: removed.

kept subject, predicate, object

Short for:

has subject, predicate, object, time: -1
has subject, predicate, object, time: 0

Alias: still_has.

kept_missing subject, predicate, object

Short for:

neg subject, predicate, object, time: -1
neg subject, predicate, object, time: 0

Since neg rules cannot introduce new variables, neither can this one.

Alias: still_missing.

Other built-in actions

collect variable, collector_name

If you use this action, engine.collection( collector_name ) will provide a uniq'ed array of all values variable has been bound to. It's a bit shorter than iterating over the tokens by hand.

error message, error { |hash_of_variable_assignments| ... }

Useful when you want to detect contradictory facts. engine.errors will give an array of all error messages produced when this action is activated. If you use the block form, the block needs to return a message.

trace options

The debugging action that will print a message every time it's activated. Possible options are:

  • values (boolean = false): whether to print variable assignments as well
  • io (IO = $stdout): which IO object to use
  • generation (boolean = false): whether this rule's gen action should print messages too. trace must come before any gen actions in this case.
  • tracer, tracer_class: a custom tracer that must respond to trace and accept a hash argument. Hash contents will vary depending on the action being traced.

Custom actions

We've seen one way to specify custom actions: using action with a block. Another way to use it is to say:

action class, ... do

Any additional arguments or blocks will be given to initialize, and the class must define an execute method taking a token. Passing any object with an execute method also works.

If your action class inherits from Wongi::Engine::Action, you'll have the following (more or less useful) attributes:

  • rete: the engine instance
  • rule: the rule object that is using this action
  • name: the extension clause used to define this action (read more under DSL extensions)
  • production: the production node

If you can't or don't want to inherit, you can define the accessors yourself. Having just the ones you need is fine.

Organising rules

Using engine.rule and engine.query is fine if you want to experiment, but to make rules and queries more manageable, you will probably want to keep them separate from the engine instance. One way to do that is to just say:

my_rule = rule "name" do

engine << my_rule

For even more convenience, why not group rules together:

my_ruleset = ruleset {
    rule "rule 1" do
    rule "rule 2" do

engine << my_ruleset

Again, you don't need to hold on to object references if you don't want to:

ruleset "my set" do

engine << Wongi::Engine::Ruleset[ "my set" ]

DSL extensions

This is a more advanced method of customising. In general, DSL extensions have the form:

dsl {
    section [ :forall | :make ]
    clause :my_action
    [ action | accept | body ] ...

which is then used in a rule like this:

make {
    my_action ...

DSL extensions are globally visible to all engine instances.

Let's have a look at the three ways to define a clause's implementation.

body { |...| ... }

This simply allows you to group several other actions or matchers. It is perhaps the only way you have to extend the forall section, as any non-trivial matchers will require special support from the engine itself.

action class, action do |token| ... end

This works almost exactly like using the action action directly in a rule, but gives it a more meaningful alias. Arguments to initialize, however, are taken from the action's invocation in make, not the definition.

A useful pattern is having specialised named collectors, defined like this:

dsl {
    section :make
    clause :my_collection
    action Wongi::Engine::SimpleCollector.collector

installed like this:

rule('collecting') {
    make {
        my_collection :X

and accessed like this:

collection = engine.collection :my_collection

accept class

Most library users probably won't need this, but it's here for completion. Acceptors represent an intermediate state. They allow you to have some shared data that you customize for a given engine instance. The class needs to respond to import_into( engine_instance ) and return something usable as an action, or to be usable as an action itself.

The class also gets arguments to initialize from the action's invocation.


The Rete implementation in this library largely follows the outline presented in [Doorenbos, 1995].



  • fixed a bug with recursive generations of multiple facts


  • fixed another NCC bug


  • fixed cleanup of invalidated NCC branches


  • fixed interaction of filters and optional nodes


  • fixed the definition of asserted (#16)


  • preventing the feedback loop introduced in 0.0.7; experimental


  • added a guard against introducing variables in neg clauses
  • fixed execution context of simple action block (#7)
  • fixed #4 once more, better
  • fixed a bug with OptionalNode (#12)
  • fixed behaviour of neg nodes; this will cause feedback loops when a gen action creates a fact that invalidates the action's condition


  • fixed a bug caused by retracting facts from within a rule action (#4)


  • fixed a bug with multiple assert tests following the same node (#2)


  • reintegrated RDF support
  • collapsible filter matchers


  • bug fixes
  • assert, assign


  • initial repackaged release


  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Added some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request
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