Benchmark: htmlStringToDom - MeasureThat.net

Tests:

Fragment
const htmlString = '<h1 level="1">1</h1><h2 level="2">2</h2><h3 level="3">3</h3><h4 level="4">4</h4><h6 level="6">5</h6><h6 level="6">6</h6>' let range; const extractHeadingFromHtml = (htmlString) => { const headings = []; if (!range) { range = document.createRange(); } const fragment = range.createContextualFragment(htmlString); const hElements = fragment.querySelectorAll('h1,h2,h3,h4,h5,h6'); for (let i = 0; i < hElements.length; i++) { const { textContent, tagName } = hElements[i]; headings.push({ text: textContent || '', level: Number(tagName[1]), }); } return headings; }; extractHeadingFromHtml(htmlString)
DomParser
const htmlString = '<h1 level="1">1</h1><h2 level="2">2</h2><h3 level="3">3</h3><h4 level="4">4</h4><h6 level="6">5</h6><h6 level="6">6</h6>' let domParser; // 提取html字符串中的标题 const extractHeadingFromHtml = (htmlString) => { if (!domParser) { domParser = new DOMParser(); } const headings = []; const hElements = domParser.parseFromString(htmlString, 'text/html').querySelectorAll('h1,h2,h3,h4,h5,h6'); for (let i = 0; i < hElements.length; i++) { const { textContent, tagName } = hElements[i]; headings.push({ text: textContent || '', level: Number(tagName[1]), }); } return headings; }; extractHeadingFromHtml(htmlString)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Fragment
DomParser

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 provided benchmark and explain what's being tested.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The benchmark in question tests two approaches for extracting headings from an HTML string: "Fragment" and "DomParser".

**Options Being Compared**

The "Fragment" approach uses the `createRange` method from the `document` object, which creates a range that can be used to parse the HTML string. This approach is efficient because it allows for fast parsing of the HTML string without loading the entire document.

The "DomParser" approach uses the `DOMParser` API, which parses an HTML string into a Document Object Model (DOM) that can be used to extract elements. This approach is more verbose and requires creating a DOM parser instance before parsing the HTML string.

**Pros and Cons of Each Approach**

**Fragment Approach:**

Pros:

* Fast parsing speed
* Low memory usage

Cons:

* Requires JavaScript engine support for `createRange`
* May not work in older browsers or environments that don't support this feature

**DomParser Approach:**

Pros:

* Works in all modern browsers and environments
* Does not require JavaScript engine support for `createRange`

Cons:

* Slower parsing speed compared to Fragment approach
* Higher memory usage due to the creation of a DOM parser instance

**Library Used**

The "DomParser" approach uses the `DOMParser` API, which is part of the HTML5 specification. The library used here is likely a JavaScript implementation of this API.

**Special JS Feature/Syntax**

There are no special features or syntaxes being used in this benchmark that are not standard JavaScript. However, it's worth noting that the use of `createRange` requires modern JavaScript engines and browsers to support this feature.

**Other Alternatives**

Other alternatives for extracting headings from an HTML string include:

* Using a library like jQuery or Cheerio, which provides DOM manipulation capabilities
* Using a parser like tinycolor2 or jsdom, which can parse HTML strings into a DOM-like structure

However, these alternatives may not be as efficient as the Fragment approach and may require more memory usage.

I hope this explanation helps you understand what's being tested in this benchmark!

Related benchmarks:

htmlStringToDom (version: 0)

Comparing performance of: Fragment vs DomParser

Created: 3 years ago by: Guest

Jump to the latest result

Fragment

DomParser

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):