Benchmark: lodash map vs native map wraig0

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/lodash.min.js'></script>

Script Preparation code:

var i = 0;
var data = Array(1000000).fill({ index: ++i, key: `${i}`, children: [], text: `yoyo${i}`});

Tests:

lodash
_.map(data, (it) => ({level: 0, node: it}))
native
data.map((it) => ({level: 0, node: it}))
native named
const mapper = (it) => ({level: 0, node: it}); data.map(mapper)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash
native
native named

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

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**Overview of the Benchmark**

The provided JSON represents a JavaScript microbenchmark test case on the MeasureThat.net website. The test compares the performance of three approaches: using Lodash's `map` function, a native JavaScript `map` function without a named callback, and a native JavaScript `map` function with a named callback.

**Options Compared**

1. **Lodash's `map` function**: This approach uses the Lodash library's `map` function to perform the transformation on the data array.
2. **Native JavaScript `map` function without a named callback**: This approach uses the built-in JavaScript `map` function without passing a named callback function as an argument.
3. **Native JavaScript `map` function with a named callback**: This approach uses the built-in JavaScript `map` function with a named callback function as an argument.

**Pros and Cons of Each Approach**

1. **Lodash's `map` function**:
	* Pros: Lodash provides a convenient and reusable utility function for mapping over arrays, which can simplify code and improve readability.
	* Cons: Using an external library may introduce additional overhead due to the need to load the library and perform any necessary initialization.
2. **Native JavaScript `map` function without a named callback**:
	* Pros: This approach uses only built-in JavaScript functionality, eliminating the need for external libraries or dependencies.
	* Cons: The code must be written manually, which can lead to more boilerplate code and less readable code if not done correctly.
3. **Native JavaScript `map` function with a named callback**:
	* Pros: This approach provides a good balance between readability and performance, as it uses built-in JavaScript functionality while still allowing for concise and expressive code.
	* Cons: The code may be slightly more verbose than using Lodash's `map` function.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a wide range of helper functions for tasks such as array manipulation, object iteration, and more. In this test case, the Lodash library is used to provide a convenient `map` function that can be used to transform arrays.

**Special JS Feature/Syntax: None**

There are no special JavaScript features or syntax used in this benchmark.

**Other Alternatives**

If you need to perform array transformations in JavaScript, other alternatives include:

1. **Underscore.js**: Another popular utility library similar to Lodash.
2. **Array.prototype.map() with an arrow function**: Using the `map()` method with an arrow function as a callback can provide a concise and readable way to perform array transformations.
3. **ES6's `map()` method with a generator function**: Using the `map()` method with a generator function can provide a concise and expressive way to perform array transformations.

In summary, this benchmark test case compares the performance of three approaches for performing array transformations using Lodash's `map` function, native JavaScript `map` functions without and with named callbacks.

Related benchmarks:

lodash map vs native map wraig0 (version: 0)

Comparing performance of: lodash vs native vs native named

Created: 3 years ago by: Guest

Jump to the latest result

lodash

native

native named

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):