batch-me-up v1.0.0

batch-me-up

A utility for efficiently splitting data into batches based on available CPU resources.

Why?

• Automatic Batch Sizing: Optimizes batch size based on the number of available CPUs for efficient processing.
• Custom Batch Sizes: Allows us to specify batch sizes for specific needs.
• Flexibility: Works with arrays of any data type.

Install

npm install batch-me-up

Or yarn:

yarn add batch-me-up

Alternatively, you can also include this module directly in your HTML file from CDN:

UMD: https://cdn.jsdelivr.net/npm/batch-me-up/dist/index.umd.js
ESM: https://cdn.jsdelivr.net/npm/batch-me-up/+esm
CJS: https://cdn.jsdelivr.net/npm/batch-me-up/dist/index.cjs

Usage

import generateBatches from 'batch-me-up'

const data = [1, 2, 3, 4, 5, 6, 7, 8]

// determine batch size based on available CPUs
const batches = await generateBatches(data)

// or specify a custom batch size
const batchesWithCustomSize = await generateBatches(data, 2)

// process each batch
const results = await Promise.all(
  batches.map(async batch => {
    // process each item within the batch concurrently
    return await Promise.all(batch.map(processItem))
  })
)

// flatten the results array, if needed
const finalResults = results.flat()
console.log(finalResults) // Output: [2, 4, 6, 8, 10, 12, 14, 16]

API

generateBatches<T = any>(data: T[], batchSize?: number): Promise<T[][]>

Generates batches of data based on the number of CPUs available or a provided batch size.

• data (array): The array of data to be batched.
• batchSize (number, optional): The desired size of each batch. If not provided, the function automatically determines the optimal batch size based on available CPUs.

Returns: An array of arrays, where each sub-array represents a batch of the original data.

Use cases

• Parallel Processing: Divide a large dataset into batches for parallel processing using libraries like Promise.all or worker threads.
• Streaming Data: Process data in chunks as it is received from a stream or API.
• Machine Learning: Batch training data for efficient model training.

Contributing

We 💛  issues.

When committing, please conform to the semantic-release commit standards. Please install commitizen and the adapter globally, if you have not already.

npm i -g commitizen cz-conventional-changelog

Now you can use git cz or just cz instead of git commit when committing. You can also use git-cz, which is an alias for cz.

git add . && git cz

License

A project by Stilearning © 2021-2024.