Getting started with fp-ts: IO

gcanti profile image Giulio Canti Updated on ・4 min read

In fp-ts a synchronous effectful computation is represented by the IO type, which is basically a thunk, i.e. a function with the following signature: () => A

interface IO<A> {
  (): A

Note that IO represents a computation that never fails.

Examples of such computations are:

  • read / write to localStorage
  • get the current time
  • write to the console
  • get a random number

Example (read / write to localStorage)

import { fromNullable, Option } from 'fp-ts/lib/Option'

const getItem = (key: string): IO<Option<string>> => () =>

const setItem = (key: string, value: string): IO<void> => () =>
  localStorage.setItem(key, value)

Example (get the current time)

const now: IO<number> = () => new Date().getTime()

Example (write to the console)

const log = (s: unknown): IO<void> => () => console.log(s)

Example (get a random number)

const random: IO<number> = () => Math.random()

The IO type admits a Monad instance, so you can map...

import { io } from 'fp-ts/lib/IO'

/** get a random boolean */
const randomBool: IO<boolean> = io.map(random, n => n < 0.5)

...or chain computations

/** write to the `console` a random boolean */
const program: IO<void> = io.chain(randomBool, log)


Note that nothing happens until you call program().

That's because program is a value which just represents an effectful computation, so in order to execute any side effect you must "run the IO action".

Since IO actions are just values you can use useful abstractions like Monoid to handle them...

Example (Dungeons and Dragons)

import { log } from 'fp-ts/lib/Console'
import { getMonoid, IO, io } from 'fp-ts/lib/IO'
import { fold, Monoid, monoidSum } from 'fp-ts/lib/Monoid'
import { randomInt } from 'fp-ts/lib/Random'

type Die = IO<number>

const monoidDie: Monoid<Die> = getMonoid(monoidSum)

/** returns the sum of the roll of the dice */
const roll: (dice: Array<Die>) => IO<number> = fold(monoidDie)

const D4: Die = randomInt(1, 4)
const D10: Die = randomInt(1, 10)
const D20: Die = randomInt(1, 20)

const dice = [D4, D10, D20]

io.chain(roll(dice), result => log(`Result is: ${result}`))()
Result is: 11

..or define useful combinators

/** Log any value to the console for debugging purposes */
const withLogging = <A>(action: IO<A>): IO<A> =>
  io.chain(action, a => io.map(log(`Value is: ${a}`), () => a))

io.chain(roll(dice.map(withLogging)), result => log(`Result is: ${result}`))()
Value is: 4
Value is: 2
Value is: 13
Result is: 19

Error handling

What if we want to represent a synchronous effectful computation that may fail?

We need two effects:

Type constructor Effect (interpretation)
IO<A> a synchronous effectful computation
Either<E, A> a computation that may fail

The solution is to put Either inside IO, which leads to the IOEither type

interface IOEither<E, A> extends IO<Either<E, A>> {}

When we "run" a value of type IOEither<E, A>, if we get a Left it means that the computation failed with an error of type E, otherwise we get a Right which means that the computation succeeded with a value of type A.

Example (read a file)

Since fs.readFileSync may throw, I'm going to use the tryCatch helper

tryCatch: <E, A>(f: () => A) => IOEither<E, A>

where f is a thunk that either throws an error (which is automatically catched by tryCatch) or returns a value of type A.

import { toError } from 'fp-ts/lib/Either'
import { IOEither, tryCatch } from 'fp-ts/lib/IOEither'
import * as fs from 'fs'

const readFileSync = (path: string): IOEither<Error, string> =>
  tryCatch(() => fs.readFileSync(path, 'utf8'), toError)

readFileSync('foo')() // => left(Error: ENOENT: no such file or directory, open 'foo')
readFileSync(__filename)() // => right(...)


The fp-ts/lib/IOEither module provides other helpers which allow to create values of type IOEither, they are collectively called lifting functions.

Here's a summary

Start value lifting function
IO<E> leftIO: <E, A>(ml: IO<E>) => IOEither<E, A>
E left: <E, A>(e: E) => IOEither<E, A>
Either<E, A> fromEither: <E, A>(ma: Either<E, A>) => IOEither<E, A>
A right: <E, A>(a: A) => IOEither<E, A>
IO<A> rightIO: <E, A>(ma: IO<A>) => IOEither<E, A>

Example (loading a random file)

Let's say we want to randomly load the content of one of three files (1.txt, 2.txt, 3.txt).

The randomInt: (low: number, high: number) => IO<number> function returns a random integer uniformly distributed in the closed interval [low, high]

import { randomInt } from 'fp-ts/lib/Random'

We can chain randomInt with the readFileSync function defined above

import { ioEither } from 'fp-ts/lib/IOEither'

const randomFile = ioEither.chain(
  randomInt(1, 3), // static error
  n => readFileSync(`${__dirname}/${n}.txt`)

This doesn't type check though!

The types don't align: randomInt runs in the IO context while readFileSync runs in the IOEither context.

However we can lift randomInt to the IOEither context by using rightIO (see the summary above)

import { ioEither, rightIO } from 'fp-ts/lib/IOEither'

const randomFile = ioEither.chain(rightIO(randomInt(1, 3)), n =>

Posted on Apr 14 '19 by:


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Fantastic article, as always.

I'm pretty new to FP concepts, and I still need to learn how some simple imperative code translates to functional code.

How can I execute a side effect in a chain? EG:

  .chain(getCharactersA) // This returns an Option
  // Execute my side effect only if there is a value

EDIT: I'm used to the tap operator of RxJS

Thank you!


You return a (representation of a) side effect rather than execute a side effect.


import { log } from 'fp-ts/lib/Console'
import { IO, io } from 'fp-ts/lib/IO'
import { chain, fold, none, Option, some } from 'fp-ts/lib/Option'
import { pipe } from 'fp-ts/lib/pipeable'

function getCharactersA(s: string): Option<string> {
  return s.length > 3 ? some(s.substring(3)) : none

function program(input: string): IO<void> {
  return pipe(
    // return my side effect only if there is a value
    fold(() => io.of(undefined), log)

program('foo')() // no output
program('barbaz')() // outputs "baz" to the console

Excellent articles, I have been following along since the beginning (tcomb types articles) and FP-TS is groovy.

One thing I was curious about was what motivated you go into the direction of TS being the language of choice in comparison to some other compile to JS such as purescript, clojurescript, etc ? Just wondering about the origins.


TypeScript allows me to reach for more people, my very goal is to spread fp concepts. TS is only a means, not an end.


What is the difference between writing to the localStorage and writing to the DOM? Could you think a reasonably simple example where the effect is to activate reactjs to create some components into the DOM and listen to user input provided through them?

Do you think it is possible to construct a realistically useable FP-powered engine to handle interactions with the DOM without having to create a huge cathedral like the elm runtime? (which sometimes reminds me more of a prison than of a cathedral ;-)


I like it but didn't' understand much.


The point of IO is to defer execution (making it lazy).
Deferring execution allows us to make pure functions from impure functions.
We prefer pure functions because they are easier to reason about.
The impure function has dependencies which are "tricky" because they are not deterministic.
It means, the impure function has side-effects and may return a different value or affects other functions.
Dangerous stuff better to avoid.
IO helps us to move a burden to the caller.

In Haskell like pure functional application, IO functions are only in composition root aka main.
Everything else (our app) is pure.

Watch this youtube.com/watch?v=cxs7oLGrxQ4&t=...


This is a great intro! I'm really excited to see async!


Great project! I was able to follow this IO tutorial and created a sample project that loads a file (synchronously) and parses the resulting YAML (github.com/anotherhale/fp-ts_sync-...). I am struggling with Tasks, dependent tasks specifically, that attempts the same file loading and parsing YAML but asynchronously (github.com/anotherhale/fp-ts_async...). Can anyone provide any feedback?


Hi there,

I'm learning fp with this library and I'm wondering, is there a way to chain 3 or more IOEithers?
It seems like chain is statically typed to only allow 2 IOEithers



You can use pipe (frok fp-ts/pipeable)


I would love to see a reactive example with mouse click events.