Benchmark: Lodash vs native iterations 2020

HTML Preparation code:

<script src="lodash.js"></script>

Script Preparation code:

var users = [
    { id: 1, name: 'Sleepy', score: 88 },
    { id: 2, name: 'Dopey', score: 75 },
    { id: 3, name: 'Grumpy', score: 103 },
    { id: 4, name: 'Bashful', score: 189 },
    { id: 5, name: 'Doc', score: 4 },
    { id: 6, name: 'Sneezy', score: 62 },
    { id: 7, name: 'Happy', score: 20 },
];

Tests:

Lodash
var highScorers = _.join( _.map( _.filter( users, (user) => user.score > 75, ), 'name', ), ', ', );
Native
var highScorers = users .filter((user) => user.score > 75) .map((user) => user.name) .join(', ');

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
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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I'll explain the benchmark and its options.

**Benchmark Overview**

The benchmark compares the performance of two approaches: using Lodash's `filter` and `map` methods together, and using native JavaScript `filter`, `map`, and `join` methods. The goal is to determine which approach is faster for a specific use case.

**Lodash Options**

In this benchmark, Lodash's `filter` method is used with the callback function `(user) => user.score > 75`. This means that only users with a score greater than 75 will pass the filter.

The `_map` method is then used on the filtered array to transform each user object into a string in the format `"name"`. The `join` method is finally used to concatenate all these strings with a comma and space separator.

**Native JavaScript Options**

In contrast, the native JavaScript approach uses three separate methods:

1. `filter`: Used to filter out users with scores less than or equal to 75.
2. `map`: Used to transform each remaining user object into a string in the format `"name"`.
3. `join`: Used to concatenate all these strings with a comma and space separator.

**Pros and Cons of Each Approach**

**Lodash Approach:**

Pros:

* More concise and readable code
* No need to worry about edge cases or incorrect filtering

Cons:

* May have performance overhead due to the overhead of Lodash's library
* May not be as efficient as native JavaScript for very large datasets

Native JavaScript Approach:

Pros:

* Can be more efficient than Lodash's approach, especially for large datasets
* More control over filtering and transformation logic

Cons:

* Requires more code and is less concise
* May require handling edge cases or incorrect filtering

**Other Considerations**

It's worth noting that the benchmark results may depend on factors such as:

* The size of the input dataset (in this case, 7 users)
* The specific requirements of the use case (e.g. performance vs conciseness)
* The version of Lodash used and the native JavaScript implementation

**Other Alternatives**

If you want to explore alternative approaches or libraries for similar use cases, consider:

* Other utility libraries like Underscore.js or Moment.js
* Built-in JavaScript methods like `Array.prototype.filter`, `Array.prototype.map`, and `String.prototype.split`
* Custom implementation using a loop or recursion

For the specific case of filtering and mapping an array of objects, other approaches could include using `Promise.all` or Web Workers to parallelize the processing.

Related benchmarks:

Lodash vs native iterations 2020 (version: 0)

Comparison of Lodash's collection iterations to their native counterparts.

Comparing performance of: Lodash vs Native

Created: 5 years ago by: Guest

Jump to the latest result

Lodash

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):