Benchmark: Immer setAutoFreeze(false) vs setAutoFreeze(true) 2

HTML Preparation code:

<script src="https://unpkg.com/immer/dist/immer.umd.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: [], someMethod: function(){ 1 + 1 } }

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:

setAutoFreeze(true)
immer.setAutoFreeze(true) 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) draft.someMethod(); })
setAutoFreeze(false)
immer.setAutoFreeze(false) 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) draft.someMethod(); })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
setAutoFreeze(true)
setAutoFreeze(false)

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Measuring the performance of two different approaches for setting `autoFreeze` in Immer, a library for predictable mutable state management.

**What is Immer?**

Immer is a JavaScript library that helps you create predictable, immutable data structures by providing a way to work with data in a functional programming style. It achieves this through the use of "drafts" – temporary copies of your data that can be modified without affecting the original data.

**Options being compared:**

Two approaches are compared:

1. **`immer.setAutoFreeze(true)`**: This approach uses `autoFreeze` to automatically convert the entire data structure into a frozen, immutable object whenever it is updated.
2. **`immer.setAutoFreeze(false)`**: This approach disables automatic freezing and allows for manual freezing of specific parts of the data structure.

**Pros and Cons:**

**`immer.setAutoFreeze(true)`**:

Pros:

* Simplifies code by reducing the need to manually freeze or unfreeze data structures.
* Can improve performance in some cases, as it eliminates the overhead of manual freezing.

Cons:

* May introduce unnecessary overhead due to automatic freezing, which can impact performance in certain scenarios.
* Requires more careful consideration when modifying the data structure, as changes may have unintended consequences on the original data.

**`immer.setAutoFreeze(false)`**:

Pros:

* Provides fine-grained control over data structure modifications, allowing for more explicit and predictable behavior.
* Can improve performance by avoiding unnecessary freezing and thawing operations.

Cons:

* Requires more manual management of freezing and unfreezing, which can increase code complexity and maintenance burden.
* May introduce bugs or errors if not used carefully, as incorrect freezing or thawing can lead to unpredictable data corruption.

**Other considerations:**

* **Manual freezing and thawing**: When using `immer.setAutoFreeze(false)`, it is essential to manually freeze specific parts of the data structure to prevent unintended changes. This requires careful consideration when modifying the data structure.
* **Performance implications**: Automatic freezing in `immer.setAutoFreeze(true)` can lead to performance overhead due to the need for unnecessary copying and updating of data structures.

**Alternatives:**

1. **Manual management with `Object.freeze()`**: Instead of using Immer, you can manually freeze specific parts of your data structure using `Object.freeze()`. This approach provides full control over data modifications but requires more manual effort.
2. **Other state management libraries**: Depending on the specific requirements and performance constraints, alternative state management libraries like MobX or Redux might be a better fit.

In summary, the choice between `immer.setAutoFreeze(true)` and `immer.setAutoFreeze(false)` depends on your specific use case, performance requirements, and code complexity tolerance. Carefully evaluating the pros and cons of each approach will help you decide which one is best suited for your project.

Related benchmarks:

Immer setAutoFreeze(false) vs setAutoFreeze(true) 2 (version: 1)

Comparing performance of: setAutoFreeze(true) vs setAutoFreeze(false)

Created: 6 years ago by: Registered User

Jump to the latest result

setAutoFreeze(true)

setAutoFreeze(false)

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):