Benchmark: Immer vs shallow vs ramda lens (2)

HTML Preparation code:

<script src="https://unpkg.com/immer@9.0.7/dist/immer.umd.production.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>

Script Preparation code:

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

Tests:

immer
data = produce(INITIAL_DATA, draft => { draft.items[NEW_ITEM_ID] = { id: NEW_ITEM_ID, name: 'ITEM-NEW', value: 0 } draft.counter++ draft.keys.push(NEW_ITEM_ID) })
shallow copy
data = { ...INITIAL_DATA, items: { ...INITIAL_DATA.items, [NEW_ITEM_ID]: { id: NEW_ITEM_ID, name: 'ITEM-NEW', value: 0 } }, count: INITIAL_DATA.count +1, keys: [ ...INITIAL_DATA.keys, NEW_ITEM_ID] }
ramda lens
data = compose( over(lensPath(["keys"]), append(NEW_ITEM_ID)), over(lensPath(["count"]), x => x + 1), set(lensPath(["items", NEW_ITEM_ID]), { id: NEW_ITEM_ID, name: "ITEM-NEW", value: 0 }) )(INITIAL_DATA);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
immer
shallow copy
ramda lens

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Mobile Safari/537.36

Browser/OS: Chrome Mobile 135 on Android

View result in a separate tab

shallow copy

972K/s

ramda lens

50K/s

immer

10K/s

View exact numbers

Test name	Executions per second
✓ shallow copy	971,911 Ops/sec
ramda lens	50,109 Ops/sec
immer	10,199 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The benchmark definition represents three different approaches to create a copy of an object: `immer`, `shallow copy`, and `ramda lens`.

1. **Immer**: Immer is a library that provides a simple way to create immutable objects in JavaScript. The benchmark uses the `produce` function from Immer to create a new, deep copy of the initial data.
2. **Shallow Copy**: A shallow copy creates a new object with references to the same values as the original object. In this case, it's used to create a new object with a single property (`items`) that contains all the properties of the original `items` object, and then adds a new item to it.
3. **Ramda Lens**: Ramda is a functional programming library that provides several useful functions for manipulating data. The benchmark uses the `lensPath` function to create a lens (a way to focus on specific parts of an object) and then applies a series of operations using the `over` and `set` functions to update the original data.

**Comparison**

The comparison is between these three approaches:

* **Immer**: Creates a deep copy of the entire object, which can be slower for large objects due to the overhead of creating a new object.
* **Shallow Copy**: Creates a shallow copy by referencing the same values as the original object. This approach is faster but can lead to unexpected behavior if one of the referenced values changes.
* **Ramda Lens**: Uses a combination of lenses and functions to update specific parts of the object without creating a new copy. This approach requires more code and may be slower than Immer or shallow copy.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

1. **Immer**:
	* Pros: Fast, creates a deep copy, easy to use.
	* Cons: May consume more memory, can be slow for large objects.
2. **Shallow Copy**:
	* Pros: Fast, lightweight, simple.
	* Cons: Can lead to unexpected behavior if referenced values change.
3. **Ramda Lens**:
	* Pros: Flexible, allows for fine-grained control over updates.
	* Cons: Requires more code, may be slower.

**Library and Purpose**

* **Immer**: A library that provides a simple way to create immutable objects in JavaScript.
* **Ramda**: A functional programming library that provides several useful functions for manipulating data.

**Special JS Feature or Syntax**

None of the above benchmarks use special JavaScript features or syntax.

Immer vs shallow vs ramda lens (2) (version: 0) Benchmark.js

Comparing performance of: `immer vs shallow copy vs ramda lens`

Created: 4 years ago by: Registered User

Go to the latest result

immer

shallow copy

ramda lens

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Immer vs shallow vs ramda lens (2) (version: 0) Benchmark.js

Comparing performance of: immer vs shallow copy vs ramda lens

Created: 4 years ago by: Registered User

Go to the latest result

immer

shallow copy

ramda lens

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `immer vs shallow copy vs ramda lens`