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Nigro Simone
Nigro Simone

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Turbo Array: Supercharge Your JavaScript Array Operations ๐Ÿš€

Handling large arrays in JavaScript can sometimes feel sluggish. Methods like .map(), .filter(), some(), every() and .reduce() are powerful but can be inefficient when chained together. What if we could optimize them for performance? Meet Turbo Array, a library designed to supercharge array operations by reducing function calls and optimizing execution under the hood. โšก

๐Ÿ”ฅ The Problem: Chained Array Methods Are Slow

When you chain multiple array methods, JavaScript loops through the array multiple times:

const numbers = [1, 2, 3, 4, 5]; const result = numbers .filter(n => n % 2 === 0) // Iterates once .map(n => n * 2); // Iterates again console.log(result); // [4, 8] 
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Each method (.filter(), .map()) creates a new intermediate array, leading to extra memory usage and repeated iterations. Turbo Array solves this by fusing operations into a single optimized function.

๐Ÿš€ Meet Turbo Array

Turbo Array compiles the entire transformation pipeline into a single efficient function, avoiding unnecessary iterations:

import { turbo } from 'turbo-array'; const turboFn = turbo() .filter(n => n % 2 === 0) .map(n => n * 2) .build(); const result = turboFn([1, 2, 3, 4, 5]); console.log(result); // [4, 8] 
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๐Ÿ’ก What happens behind the scenes? Instead of looping twice, Turbo Array merges the operations into one optimized function, reducing overhead and boosting performance.

โšก Performance Boost: How Fast Is It?

Benchmarks show significant speed improvements for large arrays. A simple .filter().map() chain runs 2-5x faster compared to native JavaScript methods.

See live example with benchmark: https://stackblitz.com/edit/turbo-array

๐Ÿ“ฆ Install and Try It Out

Ready to optimize your array operations? Install Turbo Array via npm:

npm install turbo-array 
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Try it in your next JavaScript project and experience the speed boost! ๐Ÿš€

Top comments (2)

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Nigro Simone

You're absolutely right that for small datasets, the overhead may outweigh the benefits. However, Turbo Array is designed to optimize processing for large datasets, where chaining built-ins can introduce unnecessary overhead. Regarding security, I acknowledge the risks of eval, I'm actively looking into safer alternatives. Lastly, while bespoke loops can be faster, Turbo Array aims to provide a more ergonomic and readable way to handle complex array transformations without manually optimizing every time.