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12 min read

Kotlinify-TS: Kotlin-Inspired Functional & Reactive TypeScript

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Bring Kotlin's composable sequences, scope helpers, flows, and coroutines to TypeScript. Cut boilerplate, gain performance, and unlock reactive mastery.
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I wanted Kotlin's expressiveness in TypeScript without porting an entire runtime. The result is kotlinify-ts: a batteries-included functional and reactive toolkit that merges Kotlin's best ideas with the ergonomics of modern TypeScript. Sequences give you lazy pipelines, scope functions make transformations read like English, flows tame real-time data, and coroutines simplify concurrency. All in a zero-dependency package. Grab the source onGitHubor install it directly from npm.

Why We Built Kotlinify-TS

Teams kept copy-pasting bespoke utility helpers, wrestling with promise waterfalls, and fighting array chains that refused to short-circuit. Kotlinify-TS eliminates the friction by giving TypeScript developers a production-ready bridge to Kotlin's functional toolbox:

  • Kill boilerplate: Chain transformations with intent-first scope functions.
  • Scale pipelines: Run billion-row ETL jobs lazily with sequences and chunked batching.
  • Tame realtime: Use flows and backpressure to process streams without melting clients.
  • Stay safe: Result/Option monads and exhaustive matching remove undefined edge cases.

The Core Building Blocks

1. Sequences: Lazy, Fast, Predictable

Arrays eagerly compute everything. Kotlinify sequences only do the work you actually need. Early termination is baked in, and heavy transformations become cheap.

sequences.ts
import { asSequence } from 'kotlinify-ts'; const premiumCustomers = await asSequence(await fetchCustomers()) .filter(c => c.active && c.region === 'EU') .map(async c => ({ ...c, invoices: await loadInvoices(c.id) })) .filter(({ invoices }) => invoices.some(i => i.total > 5000)) .take(5) // Stops as soon as we find five matches .toArray();

In benchmarks, sequences finish the pipeline 22,000× faster when the match is near the top. That difference turns nightly jobs into on-demand API calls.

2. Scope Functions: Express Intent Directly

Inspired by Kotlin's let, also, and apply, scope helpers make transformations readable and side effects explicit.

scope-functions.ts
import { asScope } from 'kotlinify-ts'; const card = asScope(await fetchUserProfile(userId)) .let(profile => profile?.data) .also(data => analytics.track('profile_viewed', data?.id)) .let(data => ({ name: data?.displayName ?? 'Anonymous', avatar: data?.images?.primary, badges: data?.achievements.filter(a => a.highlighted) })) .value();

You declare what happens, in order, without inventing temporary variables or nested ifs.

3. Flow: Reactive Streams with Backpressure

When data never stops, arrays and promises crumble. Kotlinify flows provide cancellable, backpressure-aware pipelines ideal for websockets, queues, sensors, or Stripe webhooks.

flow.ts
import { flow } from 'kotlinify-ts'; const telemetry = flow(async emit => { const socket = new WebSocket(url); await new Promise<void>((resolve, reject) => { socket.addEventListener('message', async event => { await emit(JSON.parse(event.data as string)); }); socket.addEventListener('close', () => resolve()); socket.addEventListener('error', error => reject(error as Event)); }); return () => socket.close(); }) .buffer(250) .map(batch => batch.filter(m => m.health === 'critical')) .onEach(batch => alertOps(batch)) .catch(err => notifyOnCall(err));

Flows interop with async generators and RxJS, so you can adopt them incrementally while keeping current observability and metrics stacks.

A Real Pipeline: From CSV to Dashboard in 40 Lines

etl.ts
import { asSequence, flowOf, coroutineScope, launch } from 'kotlinify-ts'; export async function syncWarehouse(csvPath: string) { return coroutineScope(async scope => { const records = asSequence(await readCSV(csvPath)) .map(parseLine) .filter(record => record.valid) .distinctBy(record => record.id); const jobs = await records .chunked(1000) .map(batch => launch(scope, () => processBatch(batch))) .toArray(); await Promise.all(jobs.map(job => job.join())); return flowOf(...jobs) .flatMap(job => job.data) .buffer(200) .onEach(upsertDashboard) .catch(handleWarehouseError) .toList(); }); }

This is production code lifted from a logistics client. 200 lines of hand-rolled promises collapsed into a readable, testable pipeline.

Performance Snapshots

Numbers taken from the open-source benchmark suite on a 2023 MacBook Pro (M2 Max, Node 20):

OperationArray/PromiseKotlinify-TSSpeedup
Early exit search (10k items)443 ms0.02 ms22,150×
Filter → map → take89 ms0.3 ms297×
Parallel batch processing2.4 s210 ms11×

Even when pipelines must process everything, sequences stay within a few milliseconds of native arrays thanks to zero allocations and fused operators.

Adoption Playbook

  1. Start with sequences: Wrap your hot-path array transforms to unlock lazy behavior and early termination.
  2. Introduce scope helpers: Replace imperative object assembly with asScopechains for readability.
  3. Migrate to flows: Convert your WebSocket or queue consumers to flows to gain backpressure and cancellation semantics.
  4. Lean on coroutines: Use coroutineScope and launchto coordinate parallel work without racing promises.

Roadmap & Community

The current v0.2 release focuses on core primitives. Upcoming milestones include first-class Effectintegrations, ergonomic React hooks, and a plugin system for domain-specific operators. Contributions are open: bring your favorite Kotlin patterns, share battle stories, or help us harden flow adapters for more runtimes.

Kotlinify-TS thrives when teams give feedback. File issues, request operators, or drop performance traces so we can keep tightening the hot paths.