Benchmark: Immer vs Spread Reduce4

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/immer@3.1.3/dist/immer.umd.min.js"></script>
<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

function getItems(count) {
  let id = 1;
  return _.times(count, () => ({
    name: "city" + id++,
    visited: true
  }))
}
data = getItems(100)

Tests:

immer
data.reduce((acc, curr) => { return immer.produce({}, draft => { draft[curr.name] = curr.visited; }); }, {});
Spread
data.reduce((acc, curr) => ({ ...acc, [curr.name]: curr.visited, }), {});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
immer
Spread

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):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested, compared, and their pros and cons.

**Benchmark Overview**

The benchmark compares two approaches to update an object in JavaScript:

1. `Immer`: Using the Immer library to create a draft of the original object and then updating it.
2. `Spread`: Using the spread operator (`...`) to create a new object and then assigning values to its properties.

**Script Preparation Code**

The script preparation code defines two functions: `getItems` and `data`. The `getItems` function creates an array of objects with 100 items, each with a unique `name` property. The `data` variable is assigned this array.

The HTML preparation code includes links to the Immer library (`immer.umd.min.js`) and Lodash library (`lodash.min.js`).

**Individual Test Cases**

There are two test cases:

1. **Immer**: The benchmark definition uses the `immer.produce` function to create a draft of the original object (`data`) and then updates it using the spread operator.
```javascript
data.reduce((acc, curr) => {
  return immer.produce({}, draft => {
    draft[curr.name] = curr.visited;
  });
}, {});
```
The purpose of this approach is to create a safe and efficient way to update an object by creating a new draft that can be manipulated without affecting the original object.

Pros:

* Safe: Immer ensures that the original object is not modified accidentally.
* Efficient: Using `immer.produce` reduces the number of assignments required to update the object.

Cons:

* Overhead: Creating a new draft and managing its lifecycle may introduce additional overhead compared to other approaches.

2. **Spread**: The benchmark definition uses the spread operator (`...`) to create a new object and then assigns values to its properties.
```javascript
data.reduce((acc, curr) => ({ ...acc, [curr.name]: curr.visited }), {});
```
The purpose of this approach is to create a lightweight way to update an object by creating a new object with the updated properties.

Pros:

* Lightweight: Using the spread operator creates a new object without introducing additional overhead.
* Fast: Assigning values to existing properties can be faster than using `immer.produce`.

Cons:

* Insecure: If not used carefully, this approach can lead to unexpected side effects or errors when working with large objects.

**Library and Syntax**

The Immer library is used to create a safe and efficient way to update an object. Its purpose is to provide a simple and intuitive API for managing drafts of objects.

No special JavaScript features or syntax are required for this benchmark. It only relies on standard JavaScript language features, such as arrays, objects, and the spread operator.

**Alternatives**

Other alternatives to compare in similar benchmarks might include:

* Using `Object.assign()` instead of Immer
* Using a library like React's `useReducer` hook or MobX
* Implementing a custom update function using recursion or iteration

These alternatives would require careful consideration of their pros and cons, depending on the specific use case and performance requirements.

Related benchmarks:

Immer vs Spread Reduce4 (version: 0)

Comparing performance of: immer vs Spread

Created: 6 years ago by: Guest

Jump to the latest result

immer

Spread

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):