Benchmark: lodash-deepClone_vs_native-parse-stringify

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

window.source = {
    "pres_verbatim": {
        "inputName": "pres_verbatim",
        "displayName": "presence verbatim",
        "values": [{
            "key": "Oui",
            "doc_count": 6876
        }]
    },
    "q1nve-satisfaction-globale": {
        "inputName": "Q1_NVE - satisfaction globale",
        "displayName": "Q1_NVE - satisfaction globale",
        "values": [{
            "key": "Très satisfait",
            "doc_count": 3025
        }, {
            "key": "Satisfait",
            "doc_count": 2063
        }, {
            "key": "Peu satisfait",
            "doc_count": 946
        }, {
            "key": "Pas du tout satisfait",
            "doc_count": 842
        }]
    },
    "q27nve-satisfaction-de-la-ponctualite-du-technicien": {
        "inputName": "Q27_NVE - satisfaction de la ponctualité du technicien",
        "displayName": "Q27_NVE - satisfaction de la ponctualité du technicien",
        "values": [{
            "key": "Très satisfait",
            "doc_count": 3571
        }, {
            "key": "Satisfait",
            "doc_count": 1273
        }, {
            "key": "",
            "doc_count": 1244
        }, {
            "key": "Pas du tout satisfait",
            "doc_count": 418
        }, {
            "key": "Peu satisfait",
            "doc_count": 370
        }]
    }
};

Tests:

lodash-deepClone
let clone = _.cloneDeep(source);
native-parse-stringify
let clone = JSON.parse(JSON.stringify(source));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash-deepClone
native-parse-stringify

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.

I'd be happy to explain the benchmark and its results.

**Benchmark Overview**

The benchmark is designed to compare the performance of two approaches: using Lodash's `deepClone` function to clone an object, and using native JSON stringification and parsing to achieve the same result. The test data consists of a JSON object with several nested levels, which represents real-world data.

**Benchmark Definition Json**

The provided JSON defines two benchmark definitions:

1. `lodash-deepClone`: This benchmark definition uses Lodash's `deepClone` function to clone the input JSON object.
```javascript
let clone = _.cloneDeep(source);
```
2. `native-parse-stringify`: This benchmark definition uses native JavaScript methods to create a deep copy of the input JSON object by stringifying and parsing it again.
```javascript
let clone = JSON.parse(JSON.stringify(source));
```
**Options Compared**

The two approaches differ in how they handle nested objects:

1. `lodash-deepClone`:
	* Uses Lodash's internal implementation, which recursively clones all nested objects and arrays.
	* Preserves the original data structure and relationships between objects.
2. `native-parse-stringify`:
	* Creates a deep copy of the input object by serializing it to a JSON string using `JSON.stringify()`.
	* Parses the resulting string back into a JavaScript object using `JSON.parse()`.

**Pros and Cons**

Here are some pros and cons for each approach:

**Lodash's `deepClone`**

Pros:

* Preserves the original data structure and relationships between objects.
* Can handle complex, deeply nested data structures.

Cons:

* Requires Lodash to be included in the benchmarking environment.
* May have overhead due to Lodash's internal implementation.

**Native `JSON.parse()` and `JSON.stringify()`**

Pros:

* Does not require any additional libraries or dependencies.
* Uses native JavaScript methods, which can be faster than relying on a library like Lodash.

Cons:

* Can lose metadata and relationships between objects during the cloning process.
* May not handle complex data structures as efficiently as `deepClone`.

**Other Considerations**

In addition to these two approaches, other alternatives for deep cloning in JavaScript include:

1. Using `Array.prototype.slice()` or `Object.assign()`: These methods can be used to create shallow copies of arrays and objects, but may not work correctly for deeply nested data structures.
2. Implementing a custom deep cloning function using recursive iteration: This approach can be more efficient than relying on a library like Lodash, but requires manual implementation and testing.

**Test Case Libraries**

The test cases use the following libraries:

1. `lodash.js`: Used by the `lodash-deepClone` benchmark definition.
2. No additional libraries are required for the `native-parse-stringify` benchmark definition.

**Special JS Features or Syntax**

There are no special JavaScript features or syntax used in this benchmark. The focus is on comparing two different approaches to deep cloning, without relying on any advanced or experimental features.

Related benchmarks:

lodash-deepClone_vs_native-parse-stringify (version: 0)

Comparing performance of: lodash-deepClone vs native-parse-stringify

Created: 6 years ago by: Registered User

Jump to the latest result

lodash-deepClone

native-parse-stringify

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):