Benchmark: lodash some vs loop

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/lodash/4.16.2/lodash.min.js"></script>

Script Preparation code:

var sample = [1000, 1234, 1222, 3444, 1, 89, 100, 1200, 88888, 99999, 2000000];
var testArray = [];

for (var i = 1000000; i > 0; i--){
	if(i % 3 === 0){
      sample.push[i]
    }
}

for (var i = 0; i < 1000000; i ++)
{
  testArray[i] = i;
}

function contains(list, item) {
  if (item && (list && list.length)) {
    for (var i = 0; i < list.length; i++) {
      var contains = item === list[i];
      if (contains) {
        return contains;
      }
    }
  }
  return false;
}

Tests:

use for loop
for (var i = 0; i < sample.length; i++) { contains(testArray, sample[i]) }
use lodash some
for (var i = 0; i < sample.length; i++) { _.some(testArray, function(testVal){ return testVal === sample[i]; }); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
use for loop
use lodash some

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

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I'll break down the benchmark for you.

**Overview**

The provided JSON represents a JavaScript microbenchmark test case on MeasureThat.net. The goal is to compare the performance of two approaches: using a traditional `for` loop and using the `_.some()` function from the Lodash library.

**Options Compared**

The two options being compared are:

1. **Traditional `for` loop**: This approach uses a manual index variable (`i`) to iterate over the `sample` array, checking each element against the `testArray`.
2. **Lodash `_some()` function**: This approach uses the Lodash library's `_.some()` function, which iterates over the elements of an array and returns `true` if at least one element passes a provided callback function.

**Pros and Cons**

**Traditional `for` loop:**

Pros:

* No dependencies on external libraries.
* Simple and easy to understand.
* No potential performance overhead due to library loading.

Cons:

* Manual index variable management can lead to errors or off-by-one issues if not handled carefully.
* Performance might suffer if the array is large, as it requires manual indexing.

**Lodash `_some()` function:**

Pros:

* Convenient and expressive syntax for iterating over arrays with a condition.
* Reduces boilerplate code and reduces the chance of human error.

Cons:

* Introduces an external dependency on Lodash, which might increase overhead due to library loading.
* Might have performance implications if not used carefully (e.g., unnecessary function calls or excessive memory allocation).

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a collection of higher-order functions for functional programming. The `_.some()` function is one of its many useful tools, allowing you to check if at least one element in an array passes a provided condition.

**Special JS Feature/Syntax**

There are no special JavaScript features or syntaxes used in this benchmark beyond the standard ES6+ syntax and Lodash's `_some()` function. The test case focuses on comparing two specific approaches rather than exploring advanced features.

**Other Alternatives**

If you were to rewrite this benchmark using a different approach, some alternatives could be:

* Using `Array.prototype.some()` or `Array.prototype.find()`, which are built-in methods for checking elements in an array.
* Utilizing modern JavaScript features like `for...of` loops or `Map`/`Set` data structures.
* Implementing a custom iteration mechanism using Web Workers or other concurrency mechanisms.

Keep in mind that the choice of alternative approach would depend on your specific requirements and constraints.

Related benchmarks:

lodash some vs loop (version: 0)

Comparing performance of: use for loop vs use lodash some

Created: 9 years ago by: Registered User

Jump to the latest result

use for loop

use lodash some

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):