Benchmark: mapvalues reduce

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.15/lodash.min.js"></script>

Script Preparation code:

var collection = [1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, ]

Tests:

_.mapValues(collection, () => "a")
_.mapValues(collection, () => "a")
Object.keys(collection).reduce( (acc, item) => ({ ...acc, [item]: "a", }), {} )
Object.keys(collection).reduce( (acc, item) => ({ ...acc, [item]: "a", }), {} )

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.mapValues(collection, () => "a")
Object.keys(collection).reduce( (acc, item) => ({ ...acc, [item]: "a", }), {} )

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark and its options.

**Overview**

The provided JSON represents a JavaScript microbenchmark test case for the `mapValues` function from the Lodash library, as well as a custom implementation using the `reduce()` method with object destructuring. The test measures the execution speed of these two approaches on a large dataset.

**Benchmark Definition**

The benchmark definition is divided into two parts:

1. **Lodash `mapValues`**: The first part defines a test case for the Lodash `mapValues()` function, which applies a given value to each key-value pair in an object. In this case, the value is a function that returns the string `"a"`.
2. **Custom implementation using reduce() with object destructuring**: The second part defines a test case for a custom implementation of the same logic using the `reduce()` method and object destructuring.

**Options Compared**

The two options being compared are:

1. **Lodash `mapValues`**: This is the built-in function from the Lodash library, which provides a efficient and reliable way to map values in an object.
2. **Custom implementation using reduce() with object destructuring**: This is a custom implementation of the same logic, but using the `reduce()` method and object destructuring.

**Pros and Cons**

Here are some pros and cons of each option:

**Lodash `mapValues`**

Pros:

* Fast execution speed
* Efficient use of memory
* Reliable and stable

Cons: None mentioned in the benchmark definition.

**Custom implementation using reduce() with object destructuring**

Pros:

* Portable across different environments (not limited to browsers)
* Easy to understand and maintain

Cons:

* Potential performance overhead due to the use of `reduce()` and object destructuring
* May not be as efficient as Lodash's internal implementation

**Other Considerations**

The benchmark definition mentions that the test uses a large dataset, which can impact execution speed. The choice of language and environment (in this case, JavaScript) also affects the results.

It's worth noting that the custom implementation using `reduce()` with object destructuring is not a conventional way to achieve this result in JavaScript. The Lodash library provides an optimized implementation that takes care of many details, making it a reliable choice for performance-critical applications.

**Other Alternatives**

If you were to implement a similar benchmark for other functions or libraries, here are some alternatives to consider:

* For mapping values in objects, you could use the `forEach()` method or a library like Ramda.
* For performing aggregations or reducing data, you could use the `reduce()` method, but also explore libraries like Lodash or Underscore.js.

Keep in mind that each implementation has its own trade-offs and advantages. It's essential to evaluate the specific requirements of your project and choose the best approach for performance, readability, and maintainability.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36

Browser/OS: Chrome 83 on Mac OS X 10.15.5

View result in a separate tab

Test name	Executions per second
_.mapValues(collection, () => "a")	43020.8 Ops/sec
Object.keys(collection).reduce( (acc, item) => ({ ...acc, [item]: "a", }), {} )	32801.5 Ops/sec

Related benchmarks:

mapvalues reduce (version: 0)

Comparing performance of: _.mapValues(collection, () => "a") vs Object.keys(collection).reduce( (acc, item) => ({ ...acc, [item]: "a", }), {} )

Created: 4 years ago by: Guest

Jump to the latest result

_.mapValues(collection, () => "a")

Object.keys(collection).reduce( (acc, item) => ({ ...acc, [item]: "a", }), {} )

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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