- Lazy: delays applying operations until their results are needed
- Functional: provides highly composable functions
- Iteration: supports sync iterables, async iterables, and unique concurrent iterables
- Async & Concurrent: apply async operations sequentially over async iterables or concurrently over concurrent iterables
- Tree Shakeable: only bundle the code you actually use!
- Adorable Logo: designed by Jill Marbach!
$ npm i lfi
Here are some examples!
Some synchronous operations:
import {
filter,
map,
pipe,
reduce,
toArray,
toGrouped,
toMap,
toSet,
} from 'lfi'
const messySlothDiaryEntries = [
[`Carl`, `slept`],
[`phil`, `ate `],
[`phil`, ``],
[`CARL`, `climbed`],
[`Frank`, `ate`],
[`frank`, `strolled`],
[`carl`, `Slept`],
[`Frank`, ` `],
]
const cleanSlothDiaryEntries = pipe(
messySlothDiaryEntries,
map(([sloth, activity]) => [sloth, activity.trim()]),
filter(([, activity]) => activity.length > 0),
map(entry => entry.map(string => string.toLowerCase())),
reduce(toArray()),
)
console.log(cleanSlothDiaryEntries)
//=> [ [ 'carl', 'slept' ], [ 'phil', 'ate' ], [ 'carl', 'climbed' ], ... ]
const uniqueActiviesPerSloth = reduce(
toGrouped(toSet(), toMap()),
cleanSlothDiaryEntries,
)
console.log(uniqueActiviesPerSloth)
//=> Map(3) {
//=> 'carl' => Set(2) { 'slept', 'climbed' },
//=> 'phil' => Set(1) { 'ate' },
//=> 'frank' => Set(2) { 'ate', 'strolled' }
//=> }
Some sequential asynchronous operations:
import { createReadStream } from 'node:fs'
import readline from 'node:readline'
import got from 'got'
import { chunkAsync, forEachAsync, mapAsync, pipe } from 'lfi'
const filename = `every-sloth-name.txt`
await pipe(
readline.createInterface({
input: createReadStream(filename, { encoding: `utf8` }),
crlfDelay: Infinity,
}),
chunkAsync(4),
mapAsync(async slothSquad => {
const [adjective] = await got(
`https://random-word-form.herokuapp.com/random/adjective`,
).json()
return `${slothSquad.slice(0, 3).join(`, `)}, and ${slothSquad.at(
-1,
)} are ${adjective}`
}),
forEachAsync(console.log),
)
//=> george, phil, carl, and frank are jolly!
//=> scott, jerry, ralph, and mike are infinite!
// ...
Some concurrent asynchronous operations:
import { createReadStream } from 'node:fs'
import readline from 'node:readline'
import got from 'got'
import { asConcur, chunkAsync, forEachConcur, mapConcur, pipe } from 'lfi'
import limitConcur from 'limit-concur'
const filename = `every-sloth-name.txt`
await pipe(
readline.createInterface({
input: createReadStream(filename, { encoding: `utf8` }),
crlfDelay: Infinity,
}),
chunkAsync(4),
// Query for the adjectives of each group concurrently rather than sequentially!
asConcur,
mapConcur(
// At most 4 requests at a time!
limitConcur(4, async slothSquad => {
const [adjective] = await got(
`https://random-word-form.herokuapp.com/random/adjective`,
).json()
return `${slothSquad.slice(0, 3).join(`, `)}, and ${slothSquad.at(
-1,
)} are ${adjective}`
}),
),
forEachConcur(console.log),
)
//=> george, phil, carl, and frank are jolly!
//=> scott, jerry, ralph, and mike are infinite!
// ...
See the documentation for the full list of available functions and classes.
All non-variadic functions are curried.
A concurrent iterable (represented by the
ConcurIterable
type)
is a collection of values that can be iterated concurrently.
It is implemented as a function that:
- Takes a callback for handling a single value
- Returns a promise that resolves when every value has been handled
The
asConcur
function
constructs a concur iterable from a normal iterable. Here is a simplified
implementation:
const asConcur = iterable => apply =>
Promise.all(Array.from(iterable, value => apply(value)))
The implementation returns a function that calls the apply
callback for each
value in the iterable and returns a promise that resolves once all values have
been handled (taking into consideration that the handling of apply
may be
asynchronous!).
We can iterate over concur iterables:
const concurIterable = asConcur([`sleep`, `climb`, `eat`])
await concurIterable(console.log)
//=> sleep
//=> climb
//=> eat
We can manually map and filter them:
import fs from 'node:fs/promises'
const transformedConcurIterable = apply =>
concurIterable(async name => {
const contents = await fs.readFile(`${name}.txt`, `utf8`)
if (!contents.includes(`sloth`)) {
return
}
await apply(contents)
})
await transformedConcurIterable(console.log)
Or we can use lfi's awesome functions to map and filter them!
import fs from 'node:fs/promises'
import { filterConcur, forEachConcur, mapConcur, pipe } from 'lfi'
await pipe(
concurIterable,
mapConcur(name => fs.readFile(`${name}.txt`, `utf8`)),
filterConcur(contents => contents.includes(`sloth`)),
forEachConcur(console.log),
)
They are different!
-
Concur iterables don't create an intermediate array for each operation:
import { asConcur, filterConcur, mapConcur, pipe, reduceConcur, toArray, } from 'lfi' import pFilter from 'p-filter' import pMap from 'p-map' // N - 1 intermediate arrays for N operations! const intermediateArray1 = await pMap(someFunction, someArray) const intermediateArray2 = await pFilter( someOtherFunction, intermediateArray1, ) // ... const finalArray = await pMap(lastFunction, intermediateArrayN) // No intermediate arrays! No processing even happens until the call to `reduceConcur`! const otherFinalArray = await pipe( asConcur(someArray), mapConcur(someFunction), filterConcur(someOtherFunction), // ... reduceConcur(toArray()), )
-
Concur iterables don't block values from moving down the pipeline before other values:
import { asConcur, filterConcur, mapConcur, pipe, reduceConcur, toArray, } from 'lfi' import pFilter from 'p-filter' import pMap from 'p-map' const delay = timeout => new Promise(resolve => { setTimeout(resolve, timeout) }) const mapDelays = [10, 1, 1] const filterDelays = [1, 1, 10] const array = [0, 1, 2] // Takes 20 seconds! const finalArray = await pFilter( await pMap(array, async index => { await delay(mapDelays[index] * 1000) return index }), async index => { await delay(filterDelays[index] * 1000) return true }, ) // Takes 11 seconds! const otherFinalArray = await pipe( asConcur(array), mapConcur(async index => { await delay(mapDelays[index] * 1000) return index }), filterConcur(async index => { await delay(filterDelays[index] * 1000) return true }), reduceConcur(toArray()), )
-
Concur iterables are unordered (although, you can keep track of each value's initial index if that's important)
Stars are always welcome!
For bugs and feature requests, please create an issue.
MIT ©
Tomer Aberbach
Apache 2.0 ©
Google