Benchmark: lodash prop with native map vs deconstruct with native map

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.21/lodash.min.js"></script>

Script Preparation code:

var array = [{ 'id' : '0xD'}]

Tests:

lodash prop with native map
array.map(_.property('id'))
deconstruct with native map
array.map(({id}) => id)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash prop with native map
deconstruct with native map

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36

Browser/OS: Chrome 110 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
lodash prop with native map	6953366.0 Ops/sec
deconstruct with native map	21895806.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark.

The test case is comparing two approaches to extract a value from an object in an array: using Lodash's `prop` function and the `native map` approach, which uses destructuring.

**Lodash `prop` function**

Lodash is a popular JavaScript library that provides a variety of utility functions. The `prop` function is used to access a property of an object. In this case, it's being used with the `_.property('id')` syntax, which returns an accessor function that can be used to extract the value from each object in the array.

**Native map approach (deconstructing)**

The native map approach uses destructuring to extract the value directly from each object in the array. The syntax `{ id } => id` is used, where `id` is a property of the object being processed.

Now, let's discuss the pros and cons of these approaches:

**Pros of using Lodash `prop` function:**

1. **Readability**: The code is more concise and readable, as the intent is explicitly stated.
2. **Reusability**: The accessor function returned by `_prop` can be reused in other parts of the codebase.

**Cons of using Lodash `prop` function:**

1. **Performance overhead**: Using a library like Lodash introduces additional overhead due to the dynamic imports and method calls.
2. **Code size**: The final compiled code will be larger, which may impact performance or file size limitations.

**Pros of native map approach (deconstructing):**

1. **Performance**: This approach is generally faster, as it avoids the overhead of a library function call.
2. **No additional dependencies**: No extra libraries are required, making it easier to optimize for smaller code sizes.

**Cons of native map approach:**

1. **Readability**: The code may be less readable, as the intent is not explicitly stated in the syntax.
2. **Less reusable**: This approach can't be easily reused without re-declaring the same logic elsewhere.

Other alternatives:

* Using a library like jQuery or another utility library with similar functionality to Lodash.
* Implementing a custom accessor function directly in the codebase, avoiding any external dependencies.
* Optimizing for performance by using other techniques, such as caching or memoization, around the extraction operation.

In terms of special JS features or syntax, the test case uses destructuring (the `{ id } => id` syntax), which is a modern JavaScript feature introduced in ECMAScript 2015. This feature allows for concise and expressive way to extract values from objects.

Related benchmarks:

lodash prop with native map vs deconstruct with native map (version: 0)

lodash prop with native map vs deconstruct with native map

Comparing performance of: lodash prop with native map vs deconstruct with native map

Created: 3 years ago by: Guest

Jump to the latest result

lodash prop with native map

deconstruct with native map

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):