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Array.from vs Spread vs Concat vs Slice vs Map
(version: 0)
Comparing performance of:
Array.from vs Spread vs Concat vs Slice vs Map
Created:
6 years ago
by:
Guest
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Script Preparation code:
var fooSet = new Array(); for (var i = 0; i < 1000; i++) { fooSet.push(i); }
Tests:
Array.from
var other = Array.from(fooSet);
Spread
var other = [...fooSet];
Concat
var other = fooSet.concat();
Slice
var other = fooSet.slice();
Map
var other = fooSet.map(x => x);
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (5)
Previous results
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Test case name
Result
Array.from
Spread
Concat
Slice
Map
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
The provided JSON represents a JavaScript microbenchmarking test case on the MeasureThat.net website. The benchmark compares the performance of different methods to create a new array from an existing one: 1. `Array.from()` 2. Spread operator (`...`) 3. `concat()` 4. `slice()` 5. `map()` with arrow function syntax Let's break down each method and their pros and cons: **1. Array.from()** `Array.from()` is a modern JavaScript method introduced in ECMAScript 2015 (ES6). It creates a new array from an iterable (e.g., an array, set, or string) by calling the `Iterator` protocol. Pros: * Efficient for large datasets * Can handle various iterables * Returns a new array Cons: * May incur additional overhead due to the creation of an iterator object * Not supported in older browsers **2. Spread operator (`...`)** The spread operator is also introduced in ES6 and allows you to create a new array by spreading elements from an iterable. Pros: * Simple syntax * Fast execution * Works with arrays, sets, and strings Cons: * May not be as efficient for very large datasets * Can lead to shallow copying of objects if used with complex iterables **3. concat()** `concat()` is a legacy method that creates a new array by concatenating multiple elements. Pros: * Simple syntax * Fast execution * Works across older browsers Cons: * Inefficient for large datasets * Creates multiple intermediate arrays, leading to memory allocation and deallocation overhead **4. slice()** `slice()` is another legacy method that creates a new array by extracting a subset of elements from an existing array. Pros: * Fast execution * Works across older browsers Cons: * Inefficient for large datasets * Creates multiple intermediate arrays, leading to memory allocation and deallocation overhead **5. map() with arrow function syntax** `map()` is a functional programming method that applies a transformation to each element of an array. Pros: * Efficient for large datasets * Can handle complex transformations * Works in modern browsers Cons: * May incur additional overhead due to the creation of an iterator object * Requires arrow function syntax (introduced in ES6) In the provided benchmark result, we can see that Chrome 81 is consistently faster than other methods for creating arrays. This suggests that `Array.from()` and spread operator are more efficient than older legacy methods like `concat` and `slice`. The `map()` method with arrow function syntax performs well but not as consistently as `Array.from()`. This may be due to the additional overhead of the iterator object. Other considerations: * The benchmark uses a large dataset (1000 elements) to measure performance, which helps to minimize the impact of warm-up effects. * MeasureThat.net provides a raw UA string and browser information, allowing users to reproduce results in their own environment. * Using modern JavaScript methods like `Array.from()` and spread operator can lead to better code readability and maintainability. Alternatives: * If you need to support older browsers, consider using `concat` or `slice`, but be aware of the potential performance overhead. * For large datasets, `map()` with arrow function syntax can provide good performance, but be mindful of the iterator object overhead. * Consider using a library like Lodash for array-related methods, which provides more efficient and consistent implementations. By understanding these trade-offs, you can make informed decisions about which method to use depending on your specific requirements and constraints.
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