Benchmark: spread operator vs...

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/lodash/4/lodash.min.js"></script>

Script Preparation code:

function translateBySpread (a) {
  const b = {
    ...(a.id ? { id: a.id } : {}),
    ...(a.foo ? { foo: a.foo} : {})
  }
  return b;
}

function translateByLodash (a) {
  const b = {
    id: a.id || null,
    foo: a.foo || null
  }
  return _.pickBy(b, !_.isNull);
}

Tests:

spread
translateBySpread({ id: '12345', type: 'article' });
lodash
translateByLodash({ id: '12345', type: 'article' });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
spread
lodash

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; rv:128.0) Gecko/20100101 Firefox/128.0

Browser/OS: Firefox 128 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
spread	18451568.0 Ops/sec
lodash	4043407.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definition and test cases, explaining what's being tested, compared, and the pros and cons of each approach.

**Benchmark Definition Overview**

The benchmark measures the performance difference between two JavaScript functions:

1. `translateBySpread`: This function uses the spread operator (`...`) to create an object with merged properties from two objects (`a.id` and `a.foo`).
2. `translateByLodash`: This function uses the Lodash library (`_.pickBy`) to create an object with only non-null properties.

**Comparison of Spread Operator vs Lodash**

The test cases compare the performance of these two approaches for creating an object with merged properties:

1. **Spread operator (`...`)**:
	* Pros:
		+ Efficient and concise.
		+ Does not require additional library dependencies.
	* Cons:
		+ May have performance overhead due to the creation of a new object.
2. **Lodash (`_.pickBy`)**:
	* Pros:
		+ Provides more control over property selection (e.g., filtering out null values).
		+ Can be useful for more complex object manipulation.
	* Cons:
		+ Requires an additional library dependency, which may introduce overhead.

**Library Used: Lodash**

Lodash is a popular JavaScript utility library that provides various functions for tasks such as string manipulation, array processing, and object manipulation. In this benchmark, `_.pickBy` is used to filter out null properties from the created object.

**Special JS Feature/ Syntax: Spread Operator**

The spread operator (`...`) is a feature introduced in ECMAScript 2015 (ES6) that allows objects to be spread into new objects or arrays. It's a concise way to create a new object with merged properties from two or more sources.

In the `translateBySpread` function, the spread operator is used to merge the `id` and `foo` properties of the input object `a` into a new object.

**Benchmark Preparation Code**

The script preparation code includes both benchmark functions (`translateBySpread` and `translateByLodash`) along with the necessary Lodash library import for the latter.

**Alternative Approaches**

Other possible approaches to create an object with merged properties include:

1. Using the `Object.assign()` method:
```javascript
function translateByAssign(a) {
  return Object.assign({}, a.id ? { id: a.id } : {}, a.foo ? { foo: a.foo} : {});
}
```
2. Using a simple loop to merge properties:
```javascript
function translateByLoop(a) {
  const result = {};
  if (a.id) result.id = a.id;
  if (a.foo) result.foo = a.foo;
  return result;
}
```
These alternatives may have different performance characteristics compared to the spread operator and Lodash approaches.

Related benchmarks:

spread operator vs... (version: 0)

Comparing performance of: spread vs lodash

Created: one year ago by: Guest

Jump to the latest result

spread

lodash

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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