Benchmark: Intl.DateTimeFormat formatToParts vs. format then regex

Script Preparation code:

jsDate = new Date()

dtf = new Intl.DateTimeFormat("en-US", {
	hour12: false,
	timeZone: "America/New_York",
	year: "numeric",
	month: "2-digit",
	day: "2-digit",
	hour: "2-digit",
	minute: "2-digit",
	second: "2-digit",
	era: "short",
})

// from luxon
function hackyOffset(dtf, date) {
	const formatted = dtf.format(date).replace(/\u200E/g, ""),
		parsed = /(\d+)\/(\d+)\/(\d+) (AD|BC),? (\d+):(\d+):(\d+)/.exec(formatted),
		[, fMonth, fDay, fYear, fadOrBc, fHour, fMinute, fSecond] = parsed ?? []
	return [fYear, fMonth, fDay, fadOrBc, fHour, fMinute, fSecond]
}

const typeToPos = {
	year: 0,
	month: 1,
	day: 2,
	era: 3,
	hour: 4,
	minute: 5,
	second: 6,
}

function partsOffset(dtf, date) {
	const formatted = dtf.formatToParts(date)
	const filled = []
	for (let i = 0; i < formatted.length; i++) {
		const { type, value } = formatted[i]
		const pos = typeToPos[type]

		if (type === "era") {
			filled[pos] = value
		} else if (pos !== undefined) {
			filled[pos] = parseInt(value, 10)
		}
	}
	return filled
}

Tests:

hackyOffset
hackyOffset(dtf, jsDate)
partsOffset
partsOffset(dtf, jsDate)
dtf.formatToParts
dtf.formatToParts(jsDate)
dtf.format
dtf.format(jsDate)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
hackyOffset
partsOffset
dtf.formatToParts
dtf.format

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/150.0.0.0 Safari/537.36

Browser/OS: Chrome 150 on Mac OS X 10.15.7

View result in a separate tab

dtf.format

656K/s

hackyOffset

557K/s

dtf.formatToParts

244K/s

partsOffset

221K/s

View exact numbers

Test name	Executions per second
✓ dtf.format	656,307 Ops/sec
hackyOffset	556,966 Ops/sec
dtf.formatToParts	243,667 Ops/sec
partsOffset	221,321 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's dive into the benchmark and explain what's being tested.

**Overview**

The benchmark measures the performance of four different approaches:

1. `dtf.formatToParts(jsDate)`
2. `dtf.format(jsDate)` followed by a regular expression replacement
3. `hackyOffset(dtf, jsDate)`

These approaches are used to format and parse dates using the `Intl.DateTimeFormat` API.

**Internationalized Date Time Format**

The `Intl.DateTimeFormat` API is used to format dates in a locale-specific way. The `formatToParts()` method returns an array of objects containing the formatted date parts, while the `format()` method returns a string representing the formatted date.

**Benchmark Definition JSON**

The benchmark definition JSON contains the following information:

* Four test cases: `hackyOffset`, `partsOffset`, `dtf.formatToParts`, and `dtf.format`
* The `Name` field specifies the name of each test case
* The `Description` field is empty, indicating that no description is provided for these tests
* The `Script Preparation Code` field contains the code necessary to prepare the environment for each test
* The `Html Preparation Code` field is empty, indicating that no HTML preparation code is needed

**Library: Luxon**

The `hackyOffset()` function is part of the Luxon library, which provides a modern and efficient way to work with dates in JavaScript. The function takes an `Intl.DateTimeFormat` object (`dtf`) and a date object as input and returns an array of formatted date parts.

**Special JavaScript Feature: Template Literals**

The regular expression replacement used in the third test case is part of the template literals feature, introduced in ECMAScript 2015 (ES6). This feature allows you to embed expressions inside string literals using backticks (`).

**Pros and Cons of Each Approach**

Here's a brief overview of each approach:

1. `dtf.formatToParts(jsDate)`: Pros: simple and efficient way to get the formatted date parts; Cons: may not be suitable for all use cases, as it returns an array of objects.
2. `dtf.format(jsDate)` followed by regular expression replacement: Pros: allows for more control over the formatting process; Cons: adds complexity and potential performance overhead due to the regular expression replacement.
3. `hackyOffset(dtf, jsDate)`: Pros: provides a modern and efficient way to work with dates using Luxon; Cons: requires additional library dependencies.

**Other Alternatives**

If you need more control over the formatting process or want to use a different library, consider these alternatives:

* `moment.js`: A popular date formatting library that provides a wide range of formatting options.
* `date-fns`: A modern date formatting library that offers a simple and efficient way to work with dates.

Keep in mind that each alternative has its own strengths and weaknesses, so be sure to evaluate them based on your specific requirements.

Intl.DateTimeFormat formatToParts vs. format then regex (version: 0) Benchmark.js

Comparing performance of: `hackyOffset vs partsOffset vs dtf.formatToParts vs dtf.format`

Created: 2 years ago by: Guest

Go to the latest result

hackyOffset

partsOffset

dtf.formatToParts

dtf.format

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

Intl.DateTimeFormat formatToParts vs. format then regex (version: 0) Benchmark.js

Comparing performance of: hackyOffset vs partsOffset vs dtf.formatToParts vs dtf.format

Created: 2 years ago by: Guest

Go to the latest result

hackyOffset

partsOffset

dtf.formatToParts

dtf.format

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

Related benchmarks

Comparing performance of: `hackyOffset vs partsOffset vs dtf.formatToParts vs dtf.format`