Sequential async pipelines with first-class retry, error boundaries, and smart failure strategies. Pragmatic, direct, no heavy abstractions.
Just plain JavaScript. Eager execution. Perfect stack traces.
To stop writing the same try/catch and manual accumulation boilerplate.
## This is bad coding
for await (const item of iterable) {
try {
const result = await execute(item)
} catch (error) {
// OH BOY
console.error(error)
}
}
## This does not have async transformations and error control
array.filter(predicate).map(transform)Pipelean gives you:
seriesfor sequential work over arrays and async iterables — liveonProgress,pauserate limits,take, first-class error strategiesstopWhento cancel or predicate-stop any source — composes with every consumer, no option changesscan/reducefor stateful accumulation across many itemsflowfor stateful accumulation across one input — each operation enriches the same statejoinfor fork/join over named concurrent tasks — one structured{value, errors, failure}outcome, errors as data per branchpipefor vertical compositiontryCatchandretrymiddleware you can reuse across your app- Structured results
{results, errors, sourceErrors, failure}— no silent crashes *Syncvariants for synchronous code — same error collection, no promises
Need a concurrent map over a homogeneous collection? → p-map
Need fork/join over named, heterogeneous tasks with one structured outcome? → join (built in)
Want lazy iterators? → iter-tools
Love reactive streams? → RxJS / most.js
We believe Pipelean is a pragmatic middle path: sequential by design, with built-in error control and resiliency — so you stop rewriting the same boilerplate every time.
Pipelean focuses on sequential workflows: compose operations, process collections one item at a time, carry state when needed, and control failures with built-in retry and error policies. join() is the deliberate exception: a small fork/join over named branches, not a concurrency runtime. No scheduler, no cancellation — the branches start together and you get one structured result.
Need the full reference for join()? See Fork/join: join() below and docs/reference.md.
Pipelean ships a small ESLint plugin that flags .forEach(), .reduce(), .map(async ...), non-generator loops, and Promise.* static combinators, suggesting pipelean equivalents. It is a separate entry point — importing it does not pull in the runtime library.
import pipeleanConfig from 'pipelean/eslint/config'
export default [
pipeleanConfig,
// Optionally tighten individual rules:
{
rules: {
'pipelean/no-loop-without-yield': 'warn', // loops allowed only in yielding generators
'pipelean/no-promise-combinators': 'warn', // suggests series() / tryCatch()
},
},
]Pipelean is "Agent-Ready." It ships with built-in Skills to help AI assistants (like Claude, Gemini CLI, or Cursor) write better code using this library.
The easiest way to install the skills is using the Vercel agent-skills CLI:
npx skills add https://github.com/ildella/pipelean/tree/master/skillsThis will install:
pipelean-corepipelean-functional-programming
2. (Experimental) using skills-npm
yarn add -D skills-npm
yarn skills-npm- Architecture : The philosophy and design principles.
- Guide : Core concepts and usage patterns.
- Examples - Practical usage examples for all functions
- Reference - Reference docs
import {pipe, series, collect} from 'pipelean'
const pipeline = pipe(
downloadSomething,
transformSomething,
writeToDatabase,
)
async function* pages() {
yield* items
}
const {results, errors, sourceErrors} = await series(pages(), pipeline, {
strategy: collect,
pause: 200,
onProgress: ({item, result, index, total}) => {
updateBar(index + 1, total)
},
})onProgress fires live after each kept item and is awaited before the next one. pause rate-limits. total is omitted when the source has no cheap length. See docs/patterns.md for paging, unknown length, and dead-source recipes.
When each step should enrich the same state object (one input, many enrichments, final accumulated value), use flow():
import { flow } from 'pipelean'
const prepareAlbum = state => ({title: state.rawTitle.trim()})
const extractYear = state => ({year: parseYear(state.rawYear)})
const extractArtists = state => ({artists: state.artists ?? []})
const processAlbum = flow([
prepareAlbum,
extractYear,
extractArtists,
])
const {value, errors, failure} = await processAlbum(input)
// value = {title, year, artists, ...input}flow() defines the operation pipeline upfront and returns a function that runs that flow against different inputs. Each operation receives the current accumulated state and must return an object patch that gets shallow-merged in. Errors are handled per operation using Pipelean strategies, the same as series and scan. See docs/reference.md for the full reference.
When you have a handful of named, heterogeneous async tasks that should run at the same time and be reported together, use join(). Every branch starts immediately and join() waits for all of them to settle — there is no cancellation and completion order never changes the shape of the result.
import { join } from 'pipelean'
const { value, errors, failure } = await join({
ping: () => pingHost('api.example.com'),
scan: () => scanPort('api.example.com', 443),
})
// all good: value = {ping: <ms>, scan: <bool>}, errors = [], failure = false
// ping failed: value = {scan: <bool>},
// errors = [{operation: 'ping', error, index: 0}], failure = falseErrors are data, per branch, using the same strategies as flow: collect (default), failLate, skip, rethrow. failFast is an alias of failLate here, because branches already started and cannot be stopped without an AbortSignal. join() is for named branches; for a concurrent map over a homogeneous collection, use p-map. See docs/reference.md for the full reference.