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flatten reduce vs for .. of vs for
(version: 0)
Comparing performance of:
reduce vs for of
Created:
2 years ago
by:
Guest
Go to the latest result
Tests:
reduce
const flatten = (arr) => arr.reduce((acc, x) => { Array.isArray(x) ? flatten(x).forEach(y => acc.push(y)) : acc.push(x) return acc; }, []) const x = flatten([ [1,2,3], [ [4,5,6], [7,8,9], [[[[[10,11,12]]], [13,14,15]]] ], [[[[[[[[[[[16,17,18]]]]]]]]]]] ]);
for of
const flat = (argarr) => { const arr = [] for (const item of argarr) { if (Array.isArray(item)) arr.push(flat(item)) else arr.push(item) } return arr } const x = flat([ [1,2,3], [ [4,5,6], [7,8,9], [[[[[10,11,12]]], [13,14,15]]] ], [[[[[[[[[[[16,17,18]]]]]]]]]]] ]);
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
reduce
for of
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
2 years ago
)
User agent:
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36
Browser/OS:
Chrome 124 on Mac OS X 10.15.7
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<iframe src="https://measurethat.net/Embed?id=521328" width="100%" height="500px"></iframe>
for of
182K/s
reduce
135K/s
View exact numbers
Test name
Executions per second
✓
for of
181,553 Ops/sec
reduce
135,192 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the benchmark and explain what's being tested. **Benchmark Definition** The benchmark is called "flatten reduce vs for .. of vs for" and it measures the performance of three different approaches to flatten an array with nested arrays: 1. **Reduce**: Using `Array.prototype.reduce()` method. 2. **For...of loop**: Using a traditional `for` loop with the `of` keyword to iterate over the array. 3. **Traditional `for` loop**: Using a classic `for` loop to iterate over the array. **Options Compared** The three options are compared for their performance, which is measured in executions per second. **Pros and Cons of Each Approach** 1. **Reduce**: * Pros: concise and expressive code, eliminates the need to manually handle array indices. * Cons: can be slower than traditional loops due to the overhead of function calls and intermediate results. 2. **For...of loop**: * Pros: simple and easy to read, eliminates the need to manually handle array indices. * Cons: may not be as performant as traditional loops due to the overhead of iterating over arrays with `for...of`. 3. **Traditional `for` loop**: * Pros: can be highly optimized for performance, allows for manual control over iteration and indexing. * Cons: more verbose code, requires manual handling of array indices. **Library and Special JS Features** There are no libraries used in this benchmark, but the use of the `Array.prototype.reduce()` method is a built-in JavaScript feature. There are no special JS features or syntaxes being tested in this benchmark. **Other Considerations** The benchmark uses a test case that creates an array with multiple levels of nesting to simulate real-world scenarios where arrays need to be flattened. The performance results are reported for each approach, providing insight into which one is faster and more suitable for specific use cases. **Alternative Approaches** There are other approaches to flatten arrays in JavaScript, such as: 1. Using `Array.prototype.forEach()` with a callback function. 2. Using a recursive function to flatten the array. 3. Using a library like Lodash or Underscore.js to flatten arrays. These alternatives may offer different trade-offs in terms of performance, readability, and maintainability compared to the three options tested in this benchmark.
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