Benchmark: Lodash pick/omit

HTML Preparation code:

<script src='https://cdn.jsdelivr.net/npm/lodash@4.17.10/lodash.min.js'></script>

Script Preparation code:

var obj = {
    a: {
        someContext: _.times(1000000).map(x => ({ a: x }))
    },
    b: {
        someContext: _.times(1000000).map(x => ({ a: x }))
    },
    c: {
        someContext: _.times(1000000).map(x => ({ a: x }))
    }
}

Tests:

Pick
_.pick(obj, ['a', 'b'])
Omit
_.omit(obj, ['c'])

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Pick
Omit

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):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

**What is tested?**

The provided benchmark tests two individual test cases:

1. **Pick**: It tests the performance of `_.pick(obj, ['a', 'b'])`, which returns a new object with only the specified properties (`'a'` and `'b'`) from the original object `obj`.
2. **Omit**: It tests the performance of `_.omit(obj, ['c'])`, which returns a new object with all properties except those specified in the array (`['c']`) removed from the original object `obj`.

**Options compared**

The benchmark compares two options:

1. **Lodash's `pick` and `omit` functions**: These are utility functions provided by the Lodash library, which allows for functional programming patterns.
2. **Native JavaScript methods**: The benchmark also includes native JavaScript methods for accessing properties of objects.

**Pros and cons of each approach**

* **Lodash's `pick` and `omit` functions**:
	+ Pros: Convenient way to access specific properties or exclude certain properties from an object, can be useful in functional programming patterns.
	+ Cons: Adds overhead due to the library, might not be as efficient as native JavaScript methods for simple property accesses.
* **Native JavaScript methods**: Directly accessing properties of objects using dot notation (`obj.a`, `obj.b`, etc.) or bracket notation (`obj['a']`, `obj['b']`, etc.).
	+ Pros: Native performance, no additional library overhead.
	+ Cons: Less concise and less readable, especially for complex property accesses.

**Library - Lodash**

Lodash is a popular utility library for JavaScript that provides a collection of helper functions to make common programming tasks easier. The `pick` and `omit` functions are part of this library, which allows you to select specific properties from an object or exclude certain properties from an object.

**Special JS feature or syntax - none**

There's no special JavaScript feature or syntax used in this benchmark.

**Benchmark preparation code analysis**

The provided script preparation code defines a sample object `obj` with three nested objects (`a`, `b`, and `c`). The object contains arrays of 1 million elements, each containing an `a` property with the same value. This creates a large dataset for the benchmark to test.

**Alternative approaches**

Other alternatives for testing similar scenarios might include:

* Using native JavaScript methods for accessing properties of objects
* Utilizing other utility libraries like Underscore.js or Ramda
* Writing custom functions in JavaScript to perform the desired operation

Keep in mind that the choice of approach depends on the specific requirements and constraints of your project.

In conclusion, MeasureThat.net provides a useful platform for comparing the performance of different approaches to accessing properties in JavaScript objects. By testing various scenarios and libraries, users can gain insights into the most efficient ways to write their own code or optimize existing implementations.

Related benchmarks:

Lodash pick/omit (version: 0)

Comparing performance of: Pick vs Omit

Created: 3 years ago by: Registered User

Jump to the latest result

Pick

Omit

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):