Benchmark: _.pickBy vs native reduce

HTML Preparation code:

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

Script Preparation code:

var dailyRateSettings = Array(1000)
  .fill()
  .reduce((acc, curr, i) => {
    acc[i] = i;
    return acc;
  }, {});

var predicate = v => v % 2 === 0;

Tests:

_.pickBy
_.pickBy(dailyRateSettings, predicate);
native
Object.keys(dailyRateSettings).reduce((accr, cur) => { return { ...accr, [cur]: dailyRateSettings[cur], } }, {})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.pickBy
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):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and explain what's being tested.

**Benchmark Definition:**

The benchmark is comparing two approaches to achieve the same result:

1. **_.pickBy**: This is a method from the Lodash library, which is a utility function that picks values from an object based on a predicate (a function that returns true or false). In this case, the predicate filters out odd-indexed values from the `dailyRateSettings` array.
2. **Native Reduce**: This approach uses the built-in `reduce()` method of JavaScript arrays to achieve the same result. It iterates over the indices of the array and creates a new object with the even-indexed values mapped to their corresponding values in the original array.

**Options being compared:**

The benchmark is comparing the performance of two different approaches:

* **Lodash's _.pickBy**: This approach uses a utility function from a third-party library (Lodash) to perform the filtering.
* **Native Reduce**: This approach uses only built-in JavaScript features and does not rely on any external libraries.

**Pros and Cons:**

Here are some pros and cons of each approach:

* **_.pickBy (Lodash)**:
	+ Pros:
		- Easier to read and maintain, as it's a well-known utility function.
		- Less prone to errors, as it's been thoroughly tested and validated.
	+ Cons:
		- Adds an additional dependency (Lodash), which may not be desirable for all projects.
		- May have slightly higher performance overhead due to the library's execution time.
* **Native Reduce**:
	+ Pros:
		- No additional dependencies, making it a more lightweight solution.
		- Can be optimized further by using various techniques (e.g., caching, loop unrolling).
	+ Cons:
		- May require more manual error handling and testing.
		- Can be less readable and maintainable for complex filtering scenarios.

**Library:**

In this case, the library being used is Lodash, which provides a utility function `_.pickBy` that can simplify code and improve readability. Lodash is a popular JavaScript library that offers a wide range of functional programming utilities.

**Special JS feature or syntax:**

There are no special JavaScript features or syntax being tested in this benchmark. The focus is on comparing the performance of two different approaches to achieve a specific result.

**Other alternatives:**

If you're interested in exploring alternative approaches, here are a few options:

* **Array.prototype.filter()**: This method can be used to filter an array based on a predicate, but it may not be as efficient as `_.pickBy` or the native reduce approach.
* **Custom implementation**: You could write your own custom implementation of the filtering logic using only JavaScript built-ins. However, this would likely require more manual error handling and testing.

Keep in mind that the choice of approach depends on your specific use case, performance requirements, and personal preferences.

Related benchmarks:

_.pickBy vs native reduce (version: 0)

Comparing performance of: _.pickBy vs native

Created: 2 years ago by: Guest

Jump to the latest result

_.pickBy

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):