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Some vs. Filter vs. indexOf vs. Find
(version: 0)
Comparing performance of:
Array.some vs Array.filter vs Array.indexOf vs Array.find
Created:
6 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
var hasZero = []; var withoutZero = []; for (var i = 0; i < 10000; i++) { hasZero.push(Math.floor(Math.random() * 1000)); withoutZero.push(Math.floor(Math.random() * 1000) + 1) }
Tests:
Array.some
var tempResult = !!Math.round(Math.random()) ? hasZero.some(v => v === 0) : withoutZero.some(v => v === 0);
Array.filter
var tempResult = !!Math.round(Math.random()) ? hasZero.filter(v => v === 0) : withoutZero.filter(v => v === 0);
Array.indexOf
var tempResult = !!Math.round(Math.random()) ? hasZero.indexOf(0) > -1 : withoutZero.indexOf(0) > -1;
Array.find
var tempResult = !!Math.round(Math.random()) ? hasZero.find(v => v === 0) : withoutZero.find(v => v === 0);
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (4)
Previous results
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Test case name
Result
Array.some
Array.filter
Array.indexOf
Array.find
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 dive into the benchmark. **What is being tested?** The provided JSON represents a JavaScript microbenchmark that tests four different approaches to check if an array contains a specific value (in this case, 0). The arrays are populated with random integers, and the test cases use various methods to find the desired value: `some`, `filter`, `indexOf`, and `find`. **Options compared** The benchmark compares the performance of the following options: 1. **Array.some**: This method returns a boolean indicating whether at least one element in the array satisfies the provided condition. 2. **Array.filter**: This method returns a new array with all elements that pass the test implemented by the provided function. 3. **Array.indexOf**: This method returns the index of the first element in the array that passes the test implemented by the provided function, or -1 if no such element exists. 4. **Array.find**: This method returns the value of the first element in the array that satisfies the provided condition, or undefined if no such element exists. **Pros and cons of each approach** * **Array.some**: This method is concise and easy to read. However, it may be slower than other methods because it needs to iterate over all elements in the array. * **Array.filter**: This method is useful when you need a new array with only the desired elements. However, it can be slower than `some` for large arrays, as it needs to create a new array. * **Array.indexOf**: This method is fast and efficient but may return -1 if no element matches the condition. It's also less flexible than other methods because it returns an index value rather than a boolean or value. * **Array.find**: This method is concise and easy to read, similar to `some`. However, it may be slower than `indexOf` for very large arrays, as it needs to iterate over all elements. **Libraries used** None are explicitly mentioned in the provided JSON. However, the benchmark assumes that the JavaScript engine being tested supports these array methods. **Special JS features or syntax** The benchmark does not use any special JavaScript features or syntax beyond standard language features. **Other considerations** When writing microbenchmarks like this one, it's essential to consider factors such as: * The size and distribution of the input data * The specific requirements of your application (e.g., performance, readability) * The impact of caching, memoization, or other optimizations on benchmark results The benchmark results show that Firefox 109 performs best for `Array.indexOf` and `Array.find`, while performing worst for `Array.filter`. This may be due to the optimization strategies employed by the engine. **Alternatives** Other approaches you could consider using in your microbenchmarking efforts include: * Using a testing framework like Jest or Mocha * Utilizing profiling tools, such as Chrome DevTools or Node.js Inspector * Exploring alternative programming languages, such as C++ or Rust, for performance-critical code
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