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Affection

Declarative side-effects

npm install affection

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Affection is a library for describing side-effects as plain data and providing composition utilities. This project aims to improve on similar libraries by not using generators.

Generators make testing difficult in that:

  • They can have internal state.
  • Each segment of the function cannot be tested in isolation.
  • Each segment of the function can only be reached after the segments before it.
  • Generators are awkward. Conversing with a generator using next() isn't as simple as function calling.
  • Composition of generators is harder than functions inherently.

So Affection is all about functions, with the goals:

  • Improve testability through the use of pure functions.
  • Improve code reuse through la-a-carte composition of side-effects.

Let's see how we do.

Examples

This first example does not use any composition.

import { run, call, callMethod } from 'affection'

const getJSON = url => [
  call(fetch, [url]),
  resp => [callMethod(resp, 'json')]
]

async function main () {
  const payload = await run(getJSON('http://example.com'))
  console.log(payload)
}

This second example does the same as the first. Here we are using the composition utilities.

import { step, runStep, batchSteps, call, callMethod } from 'affection'

const fetchUrl = url => call(fetch, [url])
const readJSON = resp => callMethod(resp, 'json')
const getJSON = batchSteps([fetchUrl, readJSON].map(step))

async function main () {
  const payload = await runStep(getJSON, 'http://example.com')
  console.log(payload)
}

Documentation

The package contains the following:

Effects

See defaultHandle for adding more.

Execution
Composition

call

call(func: function, args: Array<any>, context: any): Effect

Describes a function call of func.apply(context, args).

callMethod

callMethod(obj: any, method: String, args: Array<any>): Effect

Describes a method call of obj[method].apply(obj, args)

all

all(effects: Array<Effect>): Effect

Describes combining effects. Like Promise.all.

race

race(effects: Array<Effect>): Effect

Describes racing effects. Like Promise.race.

itself

itself(value: any): Effect

Describes a value. This is an identity function for Effects.

defaultHandle

defaultHandle(effect: Effect, handle: function): any

Performs the action described by a particular effect. defaultHandle provides the handling for the effects included in Affection. To add more, create a new handle that wraps defaultHandle and pass that to run.

For example, say we want to add a timeout effect:

import { defaultHandle } from 'affection'

export function timeout (duration) {
  return { type: 'timeout', duration }
}

export function myHandle (effect, handle) {
  if (effect.type === 'timeout') {
    return new Promise(resolve => setTimeout(resolve, effect.duration))
  }
  return defaultHandle(effect, handle)
}

// Later...

async function main () {
  await run([timeout(1000)], myHandler)
  // Will have waited a second
}

run

run(plan: [Effect, function?], handle: function = defaultHandle): any

Executes a plan. A plan is an array where the first element is an Effect to be handled using handle and the second element is a function to call with the result of the Effect. If the function is not provided, execution terminates and the result is returned.

step

step(makeEffect: any -> Effect): Step

Creates a step. A step is a means of encapsulating an effect without needing a plan (as described by run).

This is hard to understand without an understanding of how run works. The run function is recursively executing plans until there is nothing more to do. A step is a way of saying, "Execute this effect; I don't know what happens with the result." This is for code reuse: effects should be decoupled from their consumers.

For more clarity, let's look at the step function:

const step = makeEffect => next => input => [makeEffect(input), next]

We define our makeEffect without needing to know the consumer. The next is what will consume the result. Later, steps are composed when the consumers are known. Finally, the step is given an input to build its effect.

In summary, steps decouple:

  • Creating the effect: makeEffect
  • Consuming the effect's result: next
  • Building the final plan, given an input

mapStep

mapStep(step: Step, transform: function): Step

Creates a new step which will return the result of transform called with the input to the step makeEffect and the result of the Effect.

This is good for passing along context without mucking up simple steps. For example, we are building a dictionary of the most used word for each country. We want to retain the country we are querying about in the result.

const getMostUsedWordInCountry = country => call(MyAPI, [country])
const countryWordStep = step(getMostUsedWordInCountry)
const getCountryWord = mapStep(countryWordStep, (result, country) => ({ country, word: result }))

runStep(getCountryWord, 'Canada').then(result => {
  console.log(result)
  // => { country: 'Canada', word: 'Sorry' }
})

batchSteps

batchSteps(steps: Array<Step>): Step

Creates a new step which will call each step passing the result of first step to the next and so on.

runStep

runStep(step: Step, input: any, handle: function = defaultHandle): any

Executes a step with a given input. Uses run so handle works in the same way.