Benchmark: Lodash vs Math vs for loop (positive & negative float)

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/3.10.1/lodash.min.js'></script>

Script Preparation code:

function getRandomInt(max) {
  num = Math.random() * 10000;
  num *= Math.round(Math.random()) ? 1 : -1;
  return num;
}

var arr = [];
for(var i = 0; i < 2000; i++){
  arr.push({value:getRandomInt(5000)});
}

Tests:

Lodash
_.max(arr); _.min(arr);
Math
Math.max(...arr) Math.min(...arr)
for loop
let min = 0; let max = 0; for (let index = 0; index < arr.length; index++) { const element = arr[index]; if (arr[index] < min) { min = arr[index]; } if (arr[index] > max) { max = arr[index]; } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
Math
for loop

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided benchmark definition consists of three test cases: Lodash, Math, and for loop. Each test case measures the performance of different approaches for finding the maximum and minimum values in an array.

**Test Cases**

1. **Lodash**: The first test case uses the Lodash library to find the maximum and minimum values in the `arr` array.
2. **Math**: The second test case uses the built-in Math functions (`max` and `min`) to find the maximum and minimum values in the `arr` array.
3. **For Loop**: The third test case uses a traditional for loop to iterate through the `arr` array and find the maximum and minimum values.

**Options Compared**

The three test cases compare the performance of different approaches:

* Lodash vs Math: Two built-in JavaScript methods (`max` and `min`) are compared with a popular utility library (Lodash).
* Lodash vs For Loop: A traditional for loop is compared with a modern approach using an external library.
* Math vs For Loop: The built-in Math functions are compared with a traditional, iterative approach.

**Pros and Cons**

Here's a brief overview of the pros and cons of each approach:

1. **Lodash**: Pros:
	* Easy to use and well-maintained library.
	* Provides a convenient interface for common operations like max and min.
Cons:
	* Requires an external library, which may add overhead.
2. **Math**: Pros:
	* Built-in functions are always available.
	* Fast execution speed since it's native code.
Cons:
	* Can be slower than other approaches if not optimized.
3. **For Loop**: Pros:
	* No external dependencies or libraries required.
	* Can be faster for small arrays due to caching and loop overhead.
Cons:
	* More verbose and error-prone compared to built-in functions or Lodash.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a lot of useful functions, including `max` and `min`. The `lodash.min()` function takes two arguments (the first array and the second element) and returns the minimum value. In this benchmark, it's used to find the minimum value in the `arr` array.

**Special JS Feature or Syntax**

None mentioned in the provided benchmark definition.

**Other Alternatives**

For finding maximum and minimum values in an array, other alternatives besides Lodash, Math, and for loop include:

* Using the `Array.prototype.reduce()` method with a custom function.
* Utilizing a library like Array.prototype.every() or Array.prototype.some().
* Implementing a custom iterative approach using bit manipulation and bitwise operations.

These alternatives may offer different performance characteristics depending on the specific use case and array size.

Related benchmarks:

Lodash vs Math vs for loop (positive & negative float) (version: 0)

Comparing performance of: Lodash vs Math vs for loop

Created: 5 years ago by: Guest

Jump to the latest result

Lodash

Math

for loop

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):