Benchmark: lodash.zipObject vs native reduce (FORK)

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/lodash/4.16.0/lodash.min.js"></script>

Script Preparation code:

var values = [30310, 100303, 3040494];
var keys = ['a', 'b', 'c'];

Tests:

lodash.values
_.zipObject(values, keys)
native
values.reduce((acc, entry, idx) => { acc[keys[idx]] = entry; return acc; }, {});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash.values
native

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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Let's break down the provided benchmark definition and test cases to understand what is being tested.

**Benchmark Definition**

The benchmark definition consists of two test cases:

1. `_.zipObject(values, keys)`: This test case uses the Lodash library to create a zipped object from the `values` array and the `keys` array.
2. `values.reduce((acc, entry, idx) => { acc[keys[idx]] = entry; return acc; }, {})`: This test case uses native JavaScript to reduce the `values` array and create an object with keys taken from the `keys` array.

**What is being tested**

The benchmark tests two approaches:

1. **Lodash's zipObject**: Lodash provides a utility function called `zipObject` that takes two arrays (in this case, `values` and `keys`) and creates a new object where each key-value pair comes from the corresponding position in both arrays.
2. **Native JavaScript reduce**: The native JavaScript implementation uses the `reduce` method to iterate over the `values` array and create an object with keys taken from the `keys` array.

**Options compared**

The two options are being compared for their performance, specifically:

* **Lodash's zipObject**: This approach relies on the Lodash library, which adds overhead due to the need to import and initialize the library.
* **Native JavaScript reduce**: This approach is a built-in method of JavaScript, which implies less overhead since it doesn't require importing an external library.

**Pros and cons**

Here are some pros and cons for each approach:

**Lodash's zipObject**

Pros:

* Easier to read and write code, as the implementation is provided by Lodash
* Less error-prone, as Lodash handles edge cases

Cons:

* Adds overhead due to importing and initializing the library
* May not be optimized for performance, as it relies on a pre-built implementation

**Native JavaScript reduce**

Pros:

* Optimized for performance, as it's a built-in method of JavaScript
* Less overhead, as it doesn't require importing an external library

Cons:

* Requires more expertise in implementing the logic manually
* May be more error-prone, if not implemented correctly

**Library used (Lodash)**

The Lodash library is a popular utility library for JavaScript that provides various helper functions to simplify common tasks. In this case, `zipObject` is used to create zipped objects from two arrays.

**Special JS feature or syntax**

There are no special JavaScript features or syntaxes being tested in this benchmark. The focus is on comparing the performance of using Lodash's `zipObject` versus native JavaScript's `reduce`.

**Other alternatives**

If you were to implement a similar benchmark for other approaches, here are some alternative options:

* **ES6 object initializer**: Instead of using `_.zipObject`, you could use ES6 object initializer syntax (e.g., `{ a: 30310, b: 100303, c: 3040494 }`) which might be faster.
* **Other libraries or frameworks**: Depending on the specific problem domain, other libraries like Ramda or functional programming frameworks might provide optimized implementations for zipping objects.

Keep in mind that these alternatives would require careful consideration of performance, readability, and maintainability to ensure they are suitable for your use case.

Related benchmarks:

lodash.zipObject vs native reduce (FORK) (version: 0)

Comparing performance of: lodash.values vs native

Created: 7 years ago by: Guest

Jump to the latest result

lodash.values

native

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):