Benchmark: Immer vs shallow copy222dddxxx

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/immer@6.0.5/dist/immer.umd.production.min.js"></script>

Script Preparation code:

var data = { items: {}, count: 0, keys: [] }

for (let index = 0; index < 100; index++) {
  data.items[index] = { id: index, name: `ITEM-${index}`, value: Math.random() }
  data.count++
  data.keys.push(index)
}

var NEW_ITEM_ID = data.count +1

var produce = immer.default

Tests:

normal
var x = 0; data.keys.forEach(i => x += data.items[i].id);
freez
var x = 0; Object.freeze(data); data.keys.forEach(i => x += data.items[i].id);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
normal
freez

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.

**Benchmark Overview**

The benchmark is designed to compare two approaches: shallow copy and Immer (a library that provides a safe and efficient way to work with immutable data structures).

**Script Preparation Code**

The script preparation code creates an initial dataset `data` consisting of 100 objects, each with an ID and a random value. The `keys` array is also populated with the indices of these objects.

```javascript
var data = { items: {}, count: 0, keys: [] }

for (let index = 0; index < 100; index++) {
  data.items[index] = { id: index, name: `ITEM-${index}`, value: Math.random() }
  data.count++
  data.keys.push(index)
}

var NEW_ITEM_ID = data.count +1

var produce = immer.default
```

The line `var produce = immer.default` imports the Immer library.

**Html Preparation Code**

The HTML preparation code includes a script tag that loads the Immer library from a CDN:

```html
<script src="https://cdn.jsdelivr.net/npm/immer@6.0.5/dist/immer.umd.production.min.js"></script>
```

**Individual Test Cases**

There are two test cases:

1. **"normal"`**: This test case simply iterates over the `data.items` array and accumulates the IDs in a variable `x`.
2. **"freez"`**: This test case uses Immer to freeze the `data` object, making it immutable. It then iterates over the `data.keys` array and accumulates the IDs in a variable `x`.

**Comparison**

The benchmark compares the performance of these two approaches:

* Shallow copy (no library): This approach creates a new shallow copy of the `data` object using the spread operator (`{...data}`).
* Immer (library): This approach uses Immer to create an immutable copy of the `data` object.

**Pros and Cons**

Shallow Copy:

Pros:

* Easy to implement
* No additional library dependencies

Cons:

* May lead to unexpected behavior due to mutable side effects
* Not suitable for complex, nested data structures

Immer:

Pros:

* Provides a safe and efficient way to work with immutable data structures
* Simplifies code and reduces the risk of mutations

Cons:

* Requires an external library dependency
* May have overhead due to the additional library

**Other Considerations**

When choosing between shallow copy and Immer, consider the following factors:

* Complexity of your data structure: If you're working with complex, nested data structures, Immer may be a better choice.
* Performance requirements: If performance is critical, you may want to explore other approaches, such as using a queue or an asynchronous iterator.
* Code readability and maintainability: Immer can simplify code and reduce the risk of mutations, making it easier to read and maintain.

**Other Alternatives**

If you're looking for alternatives to Immer, consider:

* Lodash's `cloneDeep` function: This function provides a deep copy of an object, similar to Immer.
* Immutable.js: Another library that provides immutable data structures and algorithms.
* Functional programming libraries like Ramda or Underscore.js: These libraries provide functional programming utilities that can help simplify code and reduce the risk of mutations.

Related benchmarks:

Immer vs shallow copy222dddxxx (version: 0)

Comparing performance of: normal vs freez

Created: 5 years ago by: Guest

Jump to the latest result

normal

freez

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):