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corollary

v0.0.2

Published

A framework for defining and evaluating complex logical systems. (A cool bool rule tool.)

Downloads

1

Readme

corollary

An alternative boolean framework for complex logical systems. More succinctly: a cool bool rule tool.

This is very experimental and a work-in-progress. Just use for fun.

Usage

The basic usage is to define rules using callbacks. Then, you compose rules using the names of the rules in combination with boolean primitives, like and, or, and not. Eventually, you have a heirarchy of rules that you can query using ask().

const { and, not, createRule, ask } = require('corollary');

createRule('isSkyBlue', weather => weather.skyColor === 'blue');
createRule('isSkyRed', weather => weather.skyColor === 'red');
createRule('isSunOut', weather => weather.cloudCoverage < 0.5);
createRule('isRainy', weather => weather.precipitation > 0.25);

createRule('isNice',
  and(
    'isSkyBlue',
    'isSunOut',
    not('isRainy')
  )
);

const today = {
  skyColor: 'blue',
  cloudCoverage: 0.2,
  precipitation: 0.2
};

const tomorrow = {
  skyColor: 'blue',
  cloudCoverage: 0.8,
  precipitation: 0
};

console.log('Is today nice?', today);

if (ask('isNice', today))
  console.log('Yes!');
else
  console.log('No...');

console.log('\nWill tomorrow be nice?', tomorrow);

if (ask('isNice', tomorrow))
  console.log('Yes!');
else
  console.log('No...');

Roadmap (Future Features)

Where to go from here? The end goal of this module is to simplify and centralize the often thousands of business rules that usually accumulate as spaghetti code if unchecked. With that goal in mind, there are a few features that would be nice to have. Since this is an early project, the API will need to be refined such that the module encourages a good programming style that supports the features.

Dependency Graph Generation

It's easy to get lost in the thousands of relationships between object types and their associations. The corollary API should expose a dependency graph-generator that shows the relationships between rules. An explicit rule system would be necessary define this dependency graph.

Dependency Graph Enforcement

We can take this a step further and enforce dependency graph restrictions. What makes dependency graph hard to completely infer would be the use of ask() in a callback. One approach is to have callback rules declare their dependencies, which are evaluated and passed to the callback.

Heirarchical Naming Convention

A heirarchy based on object types and dependencies could help users better locate and understand their rules. A convention-based API that supports a heirarchical pattern would encourage this type of rule definition and potentially make a dependency graph easier to infer.

Non-Boolean Rule Types and Lots of Primitives

It makes sense for rules to calculate non-boolean return values. The more primitives that corollary can provide to support this, the better. Think sum(), isIn(), isDeepEqual(), set operations, etc. These can be optimized. The primitives could just be rules, and more primitives could be added by the user if needed. It would be helpful to corollary for the user to provide the arity of rules. Maybe this could be part of the dependency API.