chunkify

> Split an iterable into evenly sized chunks

Install

``sh
npm install chunkify
`

Usage

`js
import chunkify from 'chunkify';

console.log([...chunkify([1, 2, 3, 4], 2)]);
//=> [[1, 2], [3, 4]]

console.log([...chunkify([1, 2, 3, 4], 3)]);
//=> [[1, 2, 3], [4]]
`

API

$3

Returns an iterable with the chunks. The last chunk could be smaller.

#### iterable

Type: Iterable (for example, Array)

The iterable to chunkify.

#### chunkSize

Type: number (integer)\
Minimum: 1

The size of the chunks.

Use-cases

$3

When dealing with large datasets, breaking data into manageable chunks can optimize the batch processing tasks.

`js
import chunkify from 'chunkify';

const largeDataSet = [...Array(1000).keys()];
const chunkedData = chunkify(largeDataSet, 50);

for (const chunk of chunkedData) {
processBatch(chunk);
}
`

$3

Dividing data into chunks can be useful in parallel processing to distribute workload evenly across different threads or workers.

`js
import {Worker} from 'node:worker_threads';
import chunkify from 'chunkify';

const data = [/ some large dataset /];
const chunkedData = chunkify(data, 20);

for (const [index, chunk] of chunkedData.entries()) {
const worker = new Worker('./worker.js', {
workerData: {
chunk,
index
}
});
}
`

$3

Splitting a large number of network requests into chunks can help in managing the load on the network and preventing rate limiting.

`js
import chunkify from 'chunkify';

const urls = [/ Array of URLs /];

const chunkedUrls = chunkify(urls, 10);

for (const chunk of chunkedUrls) {
await Promise.all(chunk.map(url => fetch(url)));
}
``