Benchmark: lodash.zipObject vs lodash.reduce

HTML Preparation code:

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

Script Preparation code:

var stuff = [
  { name: 'pi', value: 3.14 },
  { name: 'hundred', value: 100 },
  { name: 'truthy', value: true },
  { name: 'falsy', value: false },
  { name: 'estring', value: '2.71828' },
]

Tests:

_.zipObject
_.zipObject(_.map(stuff,item => item.name), _.map(stuff, item => item.value))
_.reduce
_.reduce(stuff, (acc, item) => { acc[item.name] = item.value return acc }, {})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.zipObject
_.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 dive into the world of JavaScript microbenchmarks and explain what's being tested on MeasureThat.net.

**Benchmark Definition**

The benchmark is comparing two methods: `_.zipObject` from Lodash library and `_.reduce` with an object accumulator, also using Lodash. The purpose of this benchmark is to compare the performance of these two functions in creating a new object from multiple arrays.

**Options Compared**

Two options are being compared:

1. **_zipObject**: This method takes two arrays as arguments and creates a new object where each element from the first array is used as a key, and its corresponding value comes from the second array.
2. **_reduce**: In this case, `_.reduce` is used with an object accumulator `{}` and a callback function that iterates over the `stuff` array. The callback function sets the value of each property in the accumulator based on the name and value of each item in the array.

**Pros and Cons**

Here are some pros and cons for each approach:

1. **_zipObject**:
	* Pros:
		+ Can be more concise and readable, as it uses a built-in method to create the object.
		+ May be faster since it's optimized by Lodash.
	* Cons:
		+ May not be as flexible or customizable as using `_.reduce`.
2. **_reduce**:
	* Pros:
		+ More flexible and customizable, as you can choose your own callback function and accumulator type.
		+ Can be more efficient if the data is large or complex.
	* Cons:
		+ May require more code and reasoning to achieve the same result as `_zipObject`.
		+ May be slower due to the overhead of creating an object with each execution.

**Lodash Library**

Both tests use Lodash, a popular utility library for JavaScript. Lodash provides various functions for tasks like array manipulation, object creation, and more. In this case, we're using two specific functions: `_.map` (to transform the data), `_.zipObject` (to create the object from arrays), and `_.reduce`.

**Special JS Feature or Syntax**

There is no special JavaScript feature or syntax used in these tests. They are standard JavaScript code that utilizes Lodash library.

**Other Considerations**

When choosing between `_zipObject` and `_.reduce`, consider the following:

* If you need to create a simple object with key-value pairs from two arrays, `_zipObject` might be a better choice.
* If you need more control over the data transformation or accumulator creation, `_.reduce` might be a better fit.

**Alternatives**

If you're not using Lodash, here are some alternatives for creating objects from multiple arrays:

1. **Using `Object.create()`**: You can create an object with specified properties using `Object.create()`.
2. **Using array destructuring**: If the data is in an array and has a specific structure, you can use array destructuring to extract the key-value pairs.
3. **Using a loop or iteration**: In some cases, using a simple loop or iteration might be sufficient for creating objects from multiple arrays.

Keep in mind that these alternatives may not offer the same level of convenience or performance as Lodash functions like `_zipObject` and `_.reduce`.

Related benchmarks:

lodash.zipObject vs lodash.reduce (version: 0)

Comparing performance of: _.zipObject vs _.reduce

Created: 7 years ago by: Guest

Jump to the latest result

_.zipObject

_.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):