Toggle navigation
MeasureThat.net
Create a benchmark
Tools
Feedback
FAQ
Register
Log In
dgsfgdfsh
(version: 0)
dfgdfhdfg
Comparing performance of:
Lodash vs Native
Created:
7 years ago
by:
Registered User
Jump to the latest result
HTML Preparation code:
<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>
Script Preparation code:
var data = [0, 1, false, 2, '', 3];
Tests:
Lodash
_.compact(data);
Native
data.filter(Boolean);
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
Fork
Test case name
Result
Lodash
Native
Fastest:
N/A
Slowest:
N/A
Latest run results:
No previous run results
This benchmark does not have any results yet. Be the first one
to run it!
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
**What is being tested?** MeasureThat.net is testing the performance of two approaches to compacting an array: using the `lodash` library and the native JavaScript method. In this specific benchmark, the test data consists of an array with five elements: `[0, 1, false, 2, '')`. The goal is to measure how many executions per second each approach can handle. **Options being compared** There are two options being compared: 1. **Using `lodash` library**: In this approach, `_.compact(data)` function from the Lodash library is used to remove all falsy values (including `false`, `''`, and `0`) from the array. 2. **Native JavaScript method**: The native JavaScript method `data.filter(Boolean)` is used to achieve the same result as the Lodash approach. **Pros and cons of each approach** **Lodash approach:** Pros: * Easier to read and maintain code, as it's a single line of code that achieves the desired result. * May be more efficient due to optimizations in the Lodash library. Cons: * Adds an external dependency (the Lodash library) which can increase download time and potentially affect performance. * May not be optimized for specific use cases or edge cases. **Native JavaScript method:** Pros: * No additional dependencies are required, making it a more lightweight solution. * Can be customized to fit specific needs and optimize performance for particular scenarios. Cons: * Requires more lines of code to achieve the same result, which can make it less readable and maintainable. * May not be as efficient due to potential overhead in implementing the filtering logic. **Other considerations** * The `executionsPerSecond` value is a measure of how many times each approach executes for every second. A higher value indicates better performance. * The `DevicePlatform`, `OperatingSystem`, and `Browser` information provides context about the environment where the benchmark was run, which can help identify potential performance issues. **Library description** The Lodash library is a popular JavaScript utility library that provides a wide range of functions for tasks such as array manipulation, object manipulation, and functional programming. In this case, the `_.compact(data)` function is used to remove all falsy values from the array. **Special JS feature or syntax** There are no special features or syntax mentioned in the provided code snippets. The code uses standard JavaScript syntax and the Lodash library's API. **Alternatives** Other alternatives for compacting an array include: * Using `Array.prototype.filter()` method with a custom function to filter out falsy values. * Implementing a custom loop that iterates through the array and skips over falsy values. * Using a library like Moment.js or Underscore.js, which provide similar functionality as Lodash. However, for most use cases, using `lodash` or implementing a simple filtering logic with native JavaScript methods is sufficient.
Related benchmarks:
ramda vs lodash/fp vs native
ramda vs lodash/fp vs native again
instanceOf Lodash vs Vanilla
Map (Lodash vs Lodash/fp vs Immutable) new versions
Comments
Confirm delete:
Do you really want to delete benchmark?