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spread vs mutation vs Object.assign vs Object.assign (new) for reduce callback 1000
(version: 0)
Comparing performance of:
with spread operator vs with mutation vs with object assign vs with new object assign vs foreach
Created:
4 years ago
by:
Guest
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Script Preparation code:
var range = (from, to) => { const output = [] for (var x = from; x < to; x++) { output.push(x) } return output }
Tests:
with spread operator
range(0, 1000).reduce((acc, num) => { return { ...acc, [num]: num } }, {})
with mutation
range(0, 1000).reduce((acc, num) => { acc[num] = num return acc }, {})
with object assign
range(0, 1000).reduce((acc, num) => { return Object.assign(acc, {[num]: num}) }, {})
with new object assign
range(0, 1000).reduce((acc, num) => { return Object.assign({}, acc, {[num]: num}) }, {})
foreach
const output = {}; range(0, 1000).forEach((num) => { output[num] = num; });
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (5)
Previous results
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Test case name
Result
with spread operator
with mutation
with object assign
with new object assign
foreach
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided benchmark and its test cases to understand what is being tested. **Benchmark Overview** The benchmark measures the performance of different approaches for reducing an array of numbers, where each number is assigned to an object. The aim is to find the most efficient way to perform this operation, likely in terms of execution speed. **Test Cases** There are four test cases: 1. **"with spread operator"`: This approach uses the spread operator (`...`) to create a new object and then updates its properties. 2. **"with mutation"`: This approach modifies an existing object by assigning new values to its existing keys. 3. **"with object assign"`: This approach uses `Object.assign()` to merge two objects, where one is the accumulator (initially empty) and the other is the array of numbers. 4. **"foreach "`**: This approach iterates over the array using `forEach()`, creating a new object with the current index as the key. **Library Used** In all test cases, the `range()` function is used to generate an array of 1000 numbers from 0 to 999. The `Object.assign()` method is used in two test cases (`"with object assign"` and `"with new object assign"`). There are no libraries explicitly mentioned, but it's possible that a custom library is being used. **Special JS Features or Syntax** The use of the spread operator (`...`) is not specific to JavaScript version or syntax, but it was introduced in ECMAScript 2018 (ES10). **Pros and Cons of Different Approaches:** 1. **"with spread operator"`: * Pros: Creates a new object, avoids modifying the original array, potentially more efficient for large datasets. * Cons: May incur additional memory allocation and copying, depending on the JavaScript engine's behavior. 2. **"with mutation"`: * Pros: Avoids creating unnecessary objects, potentially faster due to fewer allocations. * Cons: Modifies an existing object, which may lead to unexpected side effects if the original array is used elsewhere in the codebase. 3. **"with object assign"`: * Pros: Uses a well-established and widely supported method for merging objects, may be more predictable in terms of performance. * Cons: Creates new objects on each iteration, potentially leading to increased memory allocation and copying. 4. **"foreach "`: * Pros: Simple and straightforward approach, easy to understand and implement. * Cons: May incur slower execution times due to the overhead of `forEach()` and the need to create a new object for each index. **Other Alternatives** Additional approaches could include: * Using `Array.prototype.reduce()` directly on the array without modifying it. * Creating an intermediate array with the numbers and then using `Object.assign()` or other methods to update the accumulator. * Using a custom implementation, such as a loop-based approach or a more optimized library function. These alternatives may offer different performance characteristics, memory usage, or code readability. The benchmark can help identify which approach is most efficient for specific use cases.
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