Benchmark: _.pickBy vs _.filter on array

HTML Preparation code:

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

Script Preparation code:

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

Tests:

_.pickBy
_.pickBy(obj, predicate);
filter
_.filter(obj, predicate);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.pickBy
filter

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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I'd be happy to explain the provided benchmark and its various aspects.

**Benchmark Definition**

The benchmark measures the performance of two JavaScript functions: `_.pickBy` from Lodash and `_.filter`. The script preparation code creates an array of 1000 elements, where each element is assigned a unique index value using the `reduce` method. A predicate function is then defined to filter out even-numbered indices.

**Options Compared**

The benchmark compares two approaches:

1. **_.pickBy**: This function returns a new object containing only the properties of the original object for which the predicate function returns `true`. In this case, it would return an object with odd-numbered indices.
2. **_.filter**: This function creates a new array containing only the elements from the original array that satisfy the predicate function. In this case, it would create a new array containing only the odd-numbered indices.

**Pros and Cons**

* `_.pickBy`:
	+ Pros: Returns an object, which can be more memory-efficient than creating a new array for large datasets.
	+ Cons: Can be slower than `_.filter` for very large arrays due to the overhead of creating a new object.
* `_.filter`:
	+ Pros: Creates a new array, which can be faster and more flexible than returning an object.
	+ Cons: Returns a larger data structure, which may consume more memory.

**Library**

The Lodash library is used in this benchmark. Lodash provides a set of high-level functions for functional programming, including `_.pickBy` and `_.filter`. These functions simplify common tasks and can improve code readability and maintainability.

**Special JS Feature/Syntax**

There are no special JavaScript features or syntax mentioned in the benchmark definition. The code is written in standard JavaScript syntax.

**Other Alternatives**

Other alternatives to these two functions could be:

* Using a `for` loop or `forEach` method instead of `_.filter`
* Using `slice()` method instead of `_.filter`
* Using `map()` and `every()` methods instead of `_.pickBy`

However, it's worth noting that the performance difference between these alternatives may not be significant for small to medium-sized datasets.

**Benchmark Preparation Code**

The script preparation code creates an array of 1000 elements using the `reduce` method. The predicate function is defined to filter out even-numbered indices. This code is designed to test the performance of both `_.pickBy` and `_.filter`.

**Individual Test Cases**

Each individual test case measures the performance of one of the two functions:

* `_.pickBy`: Measures the time taken by `_.pickBy` to return an object containing only the properties of the original array that satisfy the predicate function.
* `_.filter`: Measures the time taken by `_.filter` to create a new array containing only the elements from the original array that satisfy the predicate function.

The benchmark results show the performance metrics for each test case, including the number of executions per second and the raw UA string.

Related benchmarks:

_.pickBy vs _.filter on array (version: 0)

Comparing performance of: _.pickBy vs filter

Created: 4 years ago by: Guest

Jump to the latest result

_.pickBy

filter

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):