Benchmark: lodash find vs native find by id

HTML Preparation code:

<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.11/lodash.core.js"></script>

Script Preparation code:

var users = [
  { 'user': 'joey',  'age': 32 },
  { 'user': 'ross',    'age': 41 },
  { 'user': 'chandler', 'age': 39 }
]

Tests:

lodash
_.find(users, ['user', 'ross'])
native
users.find((x) => x.user === 'ross')

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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**Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided JSON represents two individual test cases, "lodash" and "native", which compare the performance of two approaches: using Lodash's `find` method (Lodash approach) versus native JavaScript array methods (`find` and condition).

**Test Cases**

There are two test cases:

1. **Lodash approach**: The benchmark definition is `_.find(users, ['user', 'ross'])`, where `users` is an array of objects, and Lodash's `find` method is used to search for the first element in the array that matches the condition `x.user === 'ross'`.
2. **Native JavaScript approach**: The benchmark definition is `users.find((x) => x.user === 'ross')`, which uses native JavaScript array methods to achieve the same result.

**Options Compared**

The two approaches compared are:

* Lodash's `find` method
* Native JavaScript array methods (`find` and condition)

**Pros and Cons**

Here are some pros and cons of each approach:

**Lodash approach (`.find(users, ['user', 'ross'])`)**

Pros:

* Easier to read and maintain, as it uses a clear and concise syntax.
* Lodash provides a robust set of utility functions, making it easier to work with data.

Cons:

* Additional library dependency (Lodash), which may add overhead or security concerns.
* May not be optimized for performance, especially when compared to native JavaScript methods.

**Native JavaScript approach (`users.find((x) => x.user === 'ross')`)**

Pros:

* No additional library dependency, making it a more lightweight and efficient option.
* Native JavaScript methods are often optimized for performance.

Cons:

* Requires more code to achieve the same result, which can be less readable.
* May require more expertise in native JavaScript array methods.

**Other Considerations**

The test also considers the **Browser**, **DevicePlatform**, **OperatingSystem**, and **ExecutionsPerSecond** values, which provide insights into the performance characteristics of each approach across different environments. These factors are not directly related to the code itself but can influence the results.

**Library Used**

In this benchmark, Lodash is used as a utility library for its `find` method, which provides an efficient way to search arrays.

**Special JS Feature/Syntax**

Neither test case uses any special JavaScript features or syntax. They rely on standard JavaScript array methods and a popular utility library (Lodash).

**Alternatives**

If you're looking for alternative approaches, here are some options:

* **Use native JavaScript instead of Lodash**: You could replace the `_.find` call with a simple `for...loop` or `Array.prototype.find` method.
* **Other search methods**: Depending on your use case, you might consider using other search methods, such as `Array.prototype.some()` or custom indexing solutions.
* **Micro-optimizations**: Experiment with different micro-optimizations, like memoization or caching, to improve performance.

Keep in mind that the choice of approach ultimately depends on your specific requirements, personal preference, and familiarity with JavaScript.

Related benchmarks:

lodash find vs native find by id (version: 0)

Comparing performance of: lodash vs native

Created: 6 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):