Benchmark: Aviiiiii - MeasureThat.net

HTML Preparation code:

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

Tests:

Ronnnnn
var l = [...new Set([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7])]; return l;
Gaiiiiiii
var l = [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]; return _.uniq(l);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ronnnnn
Gaiiiiiii

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gemma2:9b, generated one month ago):

LLMs can make mistakes. Check important info.

This benchmark tests the performance of two different approaches to removing duplicate numbers from an array:

**Approach 1 (Native JavaScript):**

*   `var l = [...new Set([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7])]; return l;`
    * This approach leverages the `Set` object, which inherently stores only unique values.  The spread operator (`...`) is used to expand the Set back into an array.

**Approach 2 (Lodash Library):**

*   `var l = [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]; return _.uniq(l);`
    * This approach utilizes the `_.uniq()` function from the Lodash library. Lodash is a popular JavaScript utility library that provides a wide range of functions for working with arrays, objects, and other data structures.

**Pros and Cons:**

*   **Native Approach:**
    *   **Pros:** More performant in modern JavaScript engines due to optimized `Set` implementation; no external dependencies.
    *   **Cons:** Requires understanding of `Set` object.

*   **Lodash Approach:**
    *   **Pros:** Easier to read and understand for developers familiar with Lodash syntax; provides other useful array manipulation functions.
    *   **Cons:** Adds an external dependency (Lodash) to the project, potentially increasing bundle size.

**Other Considerations:**

*   For very large arrays, performance differences might become more significant. 
*   Consider whether using a specialized library like Lodash is justified for the specific project based on its complexity and requirements.

Let me know if you have any other questions about this benchmark or need further clarification!

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36

Browser/OS: Chrome 98 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Ronnnnn	2232128.8 Ops/sec
Gaiiiiiii	4035966.5 Ops/sec

Related benchmarks:

Aviiiiii (version: 0)

Comparing performance of: Ronnnnn vs Gaiiiiiii

Created: 2 years ago by: Guest

Jump to the latest result

Ronnnnn

Gaiiiiiii

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gemma2:9b, generated one month ago):