Benchmark: _.pickBy vs native.reduce2

HTML Preparation code:

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

Script Preparation code:

var getDate = (index) => {
  var sdate = new Date('2023-01-01')
  var tdate = new Date(sdate.getTime() + 86400000 * index)

  return `${tdate.getFullYear()}-${tdate.getMonth() + 1}-${tdate.getDate()}`
}
var dailySettings = Array(752)
  .fill({})
  .reduce((acc, curr, i) => {
    acc = {
      ...acc,
      [getDate(i)]: {
        1: 100,
        2: 110,
        extraAdult: 50,
        extraChild: 50,
        algorithm: 'DBR',
        baseRateCode: 'RATE-1',
        baseAmount: 110
      }
    };

    return acc;
  }, {});
  
var predicate = (v, k) => (k === '2025-1-1')

var predicate2 = v => v === '2025-1-1'

Tests:

pickby
_.pickBy(dailySettings, predicate);
native
Object.keys(dailySettings).reduce((acc, cur) => { if (predicate2(cur)) { acc = { ...acc, [cur]: dailySettings[cur] } } return acc; }, {});

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):

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Let's break down the benchmark and explain what's being tested, compared, and the pros and cons of each approach.

**Benchmark Overview**

The benchmark compares two approaches to filter an object: `_.pickBy` from Lodash and a native implementation using `Object.keys()` and `reduce()`. The test case involves creating an array of objects with varying properties and filtering them based on a predicate function.

**What's being tested?**

1. **_.pickBy**: This is a utility function from the Lodash library that filters an object by a predicate function, returning only the keys with a truthy value.
2. **Native implementation**: A custom implementation using `Object.keys()` and `reduce()` to achieve the same filtering effect.

**Comparison of approaches**

Both methods filter the objects in the `dailySettings` array based on the `predicate` function. However, they differ in their approach:

1. **_.pickBy**:
	* Pros:
		+ Concise and readable code.
		+ Lodash provides a well-maintained and widely used library for utility functions.
	* Cons:
		+ Adds an external dependency (Lodash) to the benchmark.
		+ Might incur additional overhead due to the function call and object lookup.
2. **Native implementation**:
	* Pros:
		+ No external dependencies or overhead.
		+ Native JavaScript, so no performance implications for modern browsers.
	* Cons:
		+ Code can be more verbose and harder to read.
		+ Requires a good understanding of the `Object.keys()` and `reduce()` methods.

**Other considerations**

1. **Optimization**: Lodash's `_.pickBy` is likely optimized for performance, as it has been extensively tested and reviewed by the community.
2. **Browser support**: The benchmark runs on Chrome 114 and Mac OS X 10.15.7, which might not be representative of all browsers or platforms.
3. **Future-proofing**: It's essential to keep in mind that JavaScript and browser implementations can evolve over time, affecting performance characteristics.

**Library used: Lodash**

Lodash is a popular JavaScript library for utility functions. `_pickBy` is a part of the Lodash collection, providing a concise way to filter objects based on a predicate function.

**Special JS feature or syntax**

None mentioned in this benchmark explanation. However, if you'd like to know about other special features or syntax, feel free to ask!

**Alternatives**

If you're looking for alternatives to Lodash's `_.pickBy`, consider using:

1. **Built-in JavaScript methods**: As seen in the native implementation, using `Object.keys()` and `reduce()` can achieve similar results.
2. **Other libraries**: Other libraries like Ramda or Mithril provide similar utility functions for filtering objects.
3. **Custom implementations**: Depending on your specific requirements, you might need to create a custom implementation that suits your needs.

Keep in mind that the choice of library or implementation ultimately depends on your project's specific needs and constraints.

Related benchmarks:

_.pickBy vs native.reduce2 (version: 1)

Comparing performance of: pickby vs native

Created: 2 years ago by: Registered User

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):