Benchmark: lodash.round VS Math.round

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

var x = 5.236;

Tests:

Round floating number using lodash round function
for (var i = 0; i < 1000; i++) { _.round(x); }
Round floating number using toFixed()
for (var i = 0; i < 1000; i++) { Math.round(x); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Round floating number using lodash round function
Round floating number using toFixed()

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Round floating number using lodash round function	156144.7 Ops/sec
Round floating number using toFixed()	563782.4 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON data and explain what's being tested, compared, and their pros and cons.

**Benchmark Definition:**

The benchmark compares the performance of two rounding functions: `_` (lodash) `round()` function and JavaScript native `toFixed()` function. The purpose is to determine which function is faster for rounding floating-point numbers.

**Options Compared:**

1. **Lodash `round()`**: A custom implementation of the round function using a 16-bit rounding strategy.
2. **JavaScript Native `toFixed()`**: A built-in function that rounds numbers to a fixed number of decimal places.

**Pros and Cons:**

* **Lodash `round()`**:
	+ Pros:
		- Customizable precision (not shown in this benchmark).
		- May be more readable for developers familiar with the `_` function.
	+ Cons:
		- Slower performance compared to native JavaScript functions.
		- Requires importing the lodash library, which may add extra overhead.
* **JavaScript Native `toFixed()`**:
	+ Pros:
		- Faster performance compared to custom implementations.
		- Built-in and widely supported, reducing potential issues with polyfills or older browsers.
	+ Cons:
		- Fixed precision (not shown in this benchmark), which might not be desirable in all cases.
		- May not provide as much control over rounding behavior.

**Library:**

The benchmark uses the `lodash` library, specifically version 4.17.5, which is a popular utility library for JavaScript that provides various helper functions, including `round()`.

**Other Considerations:**

* The benchmark only compares two specific rounding functions and does not account for other factors that might affect performance, such as:
	+ Browser and JavaScript engine differences.
	+ Platform-specific optimizations (e.g., WebAssembly).
	+ Edge cases or unusual input data.

**Alternatives:**

If you want to explore alternative rounding strategies, consider the following options:

1. **Decimal.js**: A library that provides a precise decimal arithmetic system, allowing for more control over rounding and formatting.
2. **Number.js**: A lightweight library that extends JavaScript's Number type with additional features, including rounding and formatting functions.
3. **Custom implementations**: You can also create your own custom rounding functions using various algorithms, such as banker's rounding or round-to-even rounding.

Keep in mind that each alternative has its pros and cons, and you should choose the one that best fits your specific use case and performance requirements.

Related benchmarks:

lodash.round VS Math.round (version: 0)

Compare round lodash function vs javascript native toFixed() function

Comparing performance of: Round floating number using lodash round function vs Round floating number using toFixed()

Created: 4 years ago by: Guest

Jump to the latest result

Round floating number using lodash round function

Round floating number using toFixed()

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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