Awesome

Data.Task

The Task(a, b) structure represents values that depend on time. This allows one to model time-based effects explicitly, such that one can have full knowledge of when they're dealing with delayed computations, latency, or anything that can not be computed immediately.

A common use for this monad is to replace the usual Continuation-Passing Style form of programming, in order to be able to compose and sequence time-dependent effects using the generic and powerful monadic operations.

Example

var Task = require('data.task')
var fs = require('fs')

// read : String -> Task(Error, Buffer)
function read(path) {
  return new Task(function(reject, resolve) {
    fs.readFile(path, function(error, data) {
      if (error)  reject(error)
      else        resolve(data)
    })
  })
}

// decode : Task(Error, Buffer) -> Task(Error, String)
function decode(task) {
  return task.map(function(buffer) {
    return buffer.toString('utf-8')
  })
}

var intro = decode(read('intro.txt'))
var outro = decode(read('outro.txt'))

// You can use `.chain` to sequence two asynchronous actions, and
// `.map` to perform a synchronous computation with the eventual
// value of the Task.
var concatenated = intro.chain(function(a) {
                     return outro.map(function(b) {
                       return a + b
                     })
                   })

// But the implementation of Task is pure, which means that you'll
// never observe the effects by using `chain` or `map` or any other
// method. The Task just records the sequence of actions that you
// wish to observe, and defers the playing of that sequence of actions
// for your application's entry-point to call.
//
// To observe the effects, you have to call the `fork` method, which
// takes a callback for the rejection, and a callback for the success.
concatenated.fork(
  function(error) { throw error }
, function(data)  { console.log(data) }
)

Installing

The easiest way is to grab it from NPM. If you're running in a Browser environment, you can use Browserify

$ npm install data.task

Using with CommonJS

If you're not using NPM, Download the latest release, and require the data.task.umd.js file:

var Task = require('data.task')

Using with AMD

Download the latest release, and require the data.task.umd.js file:

require(['data.task'], function(Task) {
  ( ... )
})

Using without modules

Download the latest release, and load the data.task.umd.js file. The properties are exposed in the global Task object:

<script src="/path/to/data.task.umd.js"></script>

Compiling from source

If you want to compile this library from the source, you'll need Git, Make, Node.js, and run the following commands:

$ git clone git://github.com/folktale/data.task.git
$ cd data.task
$ npm install
$ make bundle

This will generate the dist/data.task.umd.js file, which you can load in any JavaScript environment.

Documentation

You can read the documentation online or build it yourself:

$ git clone git://github.com/folktale/data.task.git
$ cd data.task
$ npm install
$ make documentation

Platform support

This library assumes an ES5 environment, but can be easily supported in ES3 platforms by the use of shims. Just include es5-shim :)

Licence

Copyright (c) 2013-2015 Quildreen Motta.

Released under the MIT licence.