Benchmark: Immer v Ramda v Splat

HTML Preparation code:

<script src="https://unpkg.com/immer"></script>
<script src="https://unpkg.com/ramda"></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:

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

LLMs can make mistakes. Check important info.

**What is being tested?**

The provided benchmark tests three different approaches to update and modify an object's structure:

1. **Immer**: A library that provides a simple, mutable way to work with immutable objects. It creates a new copy of the original object and updates it in-place.
2. **Shallow Copy**: A manual approach to creating a new copy of the object by spreading its properties into a new object.
3. **Ramda Lens**: A functional programming library that provides a way to update specific parts of an object using functions.

**Options compared**

The benchmark compares the performance of these three approaches:

* Immer: Uses the `immer` library to create a new copy of the object and updates it in-place.
* Shallow Copy: Manually creates a new copy of the object by spreading its properties into a new object.
* Ramda Lens: Uses Ramda's `lensPath` and `over` functions to update specific parts of the object.

**Pros and Cons**

1. **Immer**:
	* Pros: Simple, readable code, efficient updates in-place.
	* Cons: May have higher memory overhead due to creating multiple copies of the original object.
2. **Shallow Copy**:
	* Pros: No additional libraries required, simple code.
	* Cons: Manual code can be error-prone and less readable than using a library like Immer.
3. **Ramda Lens**:
	* Pros: Functional programming style provides elegant and composable updates to objects.
	* Cons: May have higher overhead due to creating multiple function calls and data structures.

**Library used - Ramda**

Ramda is a functional programming library for JavaScript that provides a set of functions for manipulating and transforming data. In this benchmark, Ramda's `lensPath` and `over` functions are used to update specific parts of the object. The `lensPath` function takes an array of strings representing the path to the value to be updated, while the `over` function applies a transformation function to the value at that path.

**Special JS feature - None**

There is no special JavaScript feature or syntax being tested in this benchmark.

**Other alternatives**

If you're looking for alternative libraries or approaches, consider:

1. **Lodash**: A popular utility library that provides a `cloneDeep` function for creating deep copies of objects.
2. **Mongose**: A MongoDB object modeling library that includes functions for updating and modifying documents.
3. **Immutable.js**: Another immutable data structure library that provides similar functionality to Immer.

Keep in mind that the best approach will depend on your specific use case, performance requirements, and personal preference.

Related benchmarks:

Immer v Ramda v Splat (version: 0)

Comparing performance of: immer vs shallow copy vs ramda lens

Created: 6 years ago by: Registered User

Jump to the latest result

immer

shallow copy

ramda lens

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):