Benchmark: _.chain then reduce vs for

HTML Preparation code:

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

Script Preparation code:

var users = {}

for (var i = 0; i < 1000; i++) {
  if (i % 2) {
 	users[i] = {a: "a", b: "b"}
  } else {
 	users[i] = {b: "b"}
  } 
}

Tests:

Lodash reduce
var res = _.chain(users) .reduce((acc, a, userID) => { if (a === "a") { acc.push(userID) } return acc }, []) .value()
Native reduce
var res = [] for (key in users) { if (users[key].a) res.push(key) }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash reduce
Native reduce

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided JSON benchmark and explain what's being tested.

**Benchmark Overview**

The benchmark is comparing two approaches to filter an array of objects in JavaScript:

1. Using Lodash's `chain` method with `reduce`
2. Using a traditional `for` loop with object iteration

**Options Compared**

In this benchmark, we have two options being compared:

* **Lodash reduce**: This approach uses the `_chain` function from Lodash to create a pipeline of operations on the `users` array. The `reduce` method is then applied to the pipeline, which iterates over each object in the array and checks if its `a` property is equal to `"a"`. If it is, the `userID` is added to an accumulator array.
* **Native reduce**: This approach uses a traditional `for` loop with object iteration to achieve the same result as Lodash's `reduce`. The loop iterates over each key in the `users` object and checks if its value has an `a` property. If it does, the key is added to an accumulator array.

**Pros and Cons**

Here are some pros and cons of each approach:

* **Lodash reduce**:
	+ Pros:
		- Concise and readable code
		- Easy to maintain and modify
	+ Cons:
		- Adds overhead due to Lodash library inclusion
		- May be slower due to pipeline creation and iteration
* **Native reduce**:
	+ Pros:
		- No additional library dependencies
		- May be faster due to direct access to the `users` object
	+ Cons:
		- More verbose code
		- Less readable due to complex loop logic

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides various functions for common tasks, such as array manipulation, string processing, and more. The `_chain` function creates a pipeline of operations on an array or object, allowing you to chain multiple methods together. In this benchmark, `_.chain` is used to create a pipeline that can be passed to the `reduce` method.

**Special JS Feature: none**

There are no special JavaScript features or syntaxes being tested in this benchmark.

**Other Alternatives**

If you're interested in alternative approaches to filtering arrays in JavaScript, here are a few options:

* Using `filter()` with an arrow function
* Using `forEach()` and pushing elements to an array
* Using `map()` and creating a new array with filtered elements

Each of these alternatives has its own pros and cons, but they can provide different trade-offs in terms of code readability, performance, and maintainability.

Related benchmarks:

_.chain then reduce vs for (version: 0)

Comparing performance of: Lodash reduce vs Native reduce

Created: 5 years ago by: Registered User

Jump to the latest result

Lodash reduce

Native reduce

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):