Benchmark: Different Styles of Object Diffs in JS

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/immutable/3.8.1/immutable.min.js'></script>
<script src='https://s3.amazonaws.com/www.deanius.com/javascripts/mongodb-diff.umd.js'></script>
<script src='https://s3.amazonaws.com/www.deanius.com/javascripts/immutablediff.umd.js'></script>
<script src='https://cdnjs.cloudflare.com/ajax/libs/deep-diff/0.3.3/deep-diff.min.js'></script>

Script Preparation code:

var beforeText = {"_id":"DZqGmqL6T9TBN6KXp","title":"Foofoo","createdAt":1475201145611,"createdBy":"Pe92xcgNnbi3yAebn","updatedBy":"Pe92xcgNnbi3yAebn","updatedAt":1475201156823,"artifactType":"creation","type":"canvas","status":"active","pages":[{"title":"Page 1","_id":"NMGnvMihjvB4XxZa7","createdAt":1475201145612,"items":{"_order":["dsbDxZQr7zMZ9JKYF"],"dsbDxZQr7zMZ9JKYF":{"_id":"dsbDxZQr7zMZ9JKYF","version":"1.0.0","style":{"text_align":"center","padding_left":12,"padding_right":12,"padding_top":28,"padding_bottom":28,"opacity":1},"settings":{"subtitle":false},"type":"headline","text":{"en":{"text":"<p>The word</p>"}}}}}],"settings":{"viewType":"free-form"}};
var afterText = {"_id":"DZqGmqL6T9TBN6KXp","title":"Foofoo","createdAt":1475201145611,"createdBy":"Pe92xcgNnbi3yAebn","updatedBy":"Pe92xcgNnbi3yAebn","updatedAt":1475201226516,"artifactType":"creation","type":"canvas","status":"active","pages":[{"title":"Page 1","_id":"NMGnvMihjvB4XxZa7","createdAt":1475201145612,"items":{"_order":["dsbDxZQr7zMZ9JKYF","J7y7NPf2WWema4sjy"],"dsbDxZQr7zMZ9JKYF":{"_id":"dsbDxZQr7zMZ9JKYF","version":"1.0.0","style":{"text_align":"center","padding_left":12,"padding_right":12,"padding_top":28,"padding_bottom":28,"opacity":1},"settings":{"subtitle":false},"type":"headline","text":{"en":{"text":"<p>The word</p>"}}},"J7y7NPf2WWema4sjy":{"_id":"J7y7NPf2WWema4sjy","version":"1.0.0","style":{"padding_left":12,"padding_right":12,"padding_top":18,"padding_bottom":18},"settings":{"title":false,"description":false,"caption":false},"type":"text","text":{"en":{"text":"<p>My first text</p>"}}}}}],"settings":{"viewType":"free-form"}};

var newEl = {"_id":"J7y7NPf2WWema4sjy","version":"1.0.0","style":{"padding_left":12,"padding_right":12,"padding_top":18,"padding_bottom":18},"settings":{"title":false,"description":false,"caption":false},"type":"text","text":{"en":{"text":"<p>My first text</p>"}}}
var beforeTextI = Immutable.fromJS(beforeText);
var afterTextI = beforeTextI.setIn(['items', 'J7y7NPf2WWema4sjy'], newEl)

Tests:

DeepDiff (beforeText, afterText)
DeepDiff(beforeText, afterText)
MongoDBDiff.diff(beforeText, afterText)
MongoDBDiff.diff(beforeText, afterText)
MongoDBDiff.diff *.toJS()
MongoDBDiff.diff(beforeTextI.toJS(), afterTextI.toJS())
ImmutableDiff two mostly shared objects
idiff(beforeTextI, afterTextI)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
DeepDiff (beforeText, afterText)
MongoDBDiff.diff(beforeText, afterText)
MongoDBDiff.diff *.toJS()
ImmutableDiff two mostly shared objects

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 definition and explanation.

**What is being tested?**

The test cases are designed to compare different approaches for computing object diffs in JavaScript. The inputs are two JSON objects: `beforeText` and `afterText`. These objects represent before-and-after states of some kind, likely related to a web application.

The objective is to find the most efficient way to determine what has changed between these two states.

**Options being compared:**

1. **DeepDiff**: A library that provides a deep diff algorithm for JavaScript objects.
2. **MongoDBDiff**: Another library specifically designed for computing diffs in MongoDB-style documents (i.e., JSON-like with nested structures).
3. **idiff**: A library that performs incremental diffing between two immutable data structures.

**Pros and Cons of each approach:**

1. **DeepDiff**:
	* Pros: Robust, widely-used, and well-maintained.
	* Cons: May be slower than other approaches for very large objects or complex data structures.
2. **MongoDBDiff**:
	* Pros: Optimized for MongoDB-style documents, which are common in web applications.
	* Cons: May not be as efficient as DeepDiff for general-purpose object diffs.
3. **idiff**:
	* Pros: Designed specifically for incremental diffing, making it potentially faster than other approaches.
	* Cons: May require additional setup and understanding of immutable data structures.

**Other considerations:**

* The use of Immutable.js library (`beforeTextI`) suggests that the test case is interested in exploring different strategies for computing diffs between immutable data structures.
* The `toJS()` method is used to convert Immutable.js objects to regular JavaScript objects, which allows for a more direct comparison with other libraries.

**Other alternatives:**

Some other libraries and approaches worth mentioning include:

1. **diff**: A lightweight library that provides basic diffing functionality.
2. **ObjectDiffer**: Another popular library for computing object diffs.
3. **Lodash.diff**: A utility function from the Lodash library that can be used for diffing.

These alternatives may not be as well-maintained or widely adopted as some of the libraries mentioned above, but they still provide a solid foundation for exploring different strategies for computing object diffs.

Related benchmarks:

Different Styles of Object Diffs in JS (version: 10)

Comparing performance of: DeepDiff (beforeText, afterText) vs MongoDBDiff.diff(beforeText, afterText) vs MongoDBDiff.diff *.toJS() vs ImmutableDiff two mostly shared objects

Created: 9 years ago by: Registered User

Jump to the latest result

DeepDiff (beforeText, afterText)

MongoDBDiff.diff(beforeText, afterText)

MongoDBDiff.diff *.toJS()

ImmutableDiff two mostly shared objects

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):