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Closest API
(version: 0)
Tests the performance of 'closest' API
Comparing performance of:
deepest.closest vs highest.closest vs average.closest
Created:
5 years ago
by:
Guest
Jump to the latest result
HTML Preparation code:
<div data-cosmos-mode="dark"> <cosmos-button id="highest"></cosmos-button> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <cosmos-button id="average"></cosmos-button> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <cosmos-button id="deepest"></cosmos-button> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div>
Script Preparation code:
var deepest = document.querySelector('#deepest'); var average = document.querySelector('#average'); var highest = document.querySelector('#highest');
Tests:
deepest.closest
deepest.closest('[data-cosmos-mode]')
highest.closest
highest.closest('[data-cosmos-mode]')
average.closest
average.closest('[data-cosmos-mode]')
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (3)
Previous results
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Test case name
Result
deepest.closest
highest.closest
average.closest
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down what's happening in this benchmark. **Benchmark Definition JSON** The `Closest API` benchmark is testing the performance of the `closest` method, which is part of the Cosmos.js library. The `closest` method is used to find an element that matches a specified selector within a document. The `Script Preparation Code` section sets up three variables: `deepest`, `average`, and `highest`. These variables are assigned values from the HTML structure using the `document.querySelector` method, which returns the first matching element. The `#deepest`, `#average`, and `#highest` IDs correspond to the top-level elements in the HTML structure. **Html Preparation Code** The HTML code is a nested structure with multiple `div` elements containing `cosmos-button` elements. Each `cosmos-button` has an ID that corresponds to one of the variables set up in the script preparation code (`deepest`, `average`, and `highest`). The `data-cosmos-mode` attribute is used to identify the element to which the `closest` method will be applied. **Individual Test Cases** The three individual test cases, "deepest.closest", "highest.closest", and "average.closest", are variations of the same benchmark definition. They differ only in the ID of the top-level element that the `closest` method is applied to. **Pros and Cons of Approaches** There are two approaches being tested here: 1. **Direct DOM Access**: The script preparation code directly accesses the DOM elements using `document.querySelector`. This approach is simple and efficient but may not be as scalable or flexible as other methods. 2. **Library-based Solution**: The `closest` method is part of a library (Cosmos.js). Using a library can provide benefits like optimized performance, caching, and reduced DOM pollution. However, it also introduces an additional dependency and potential overhead. **Pros of Library-based Solution** * Optimized performance * Caching for faster execution times * Reduced DOM pollution **Cons of Library-based Solution** * Additional dependency * Potential overhead **Pros of Direct DOM Access** * Simple and efficient * No additional dependencies or overhead **Cons of Direct DOM Access** * May not be as scalable or flexible * Requires manual management of DOM elements **Other Considerations** * The use of `data-cosmos-mode` attribute to identify the element to which the `closest` method will be applied suggests that this is a custom solution, and the Cosmos.js library is being used to optimize the performance of the `closest` method. * The nested structure of the HTML code implies that there may be many elements with similar IDs, making the use of a library like Cosmos.js potentially beneficial. **Alternatives** Other alternatives could include: * Using a CSS selector engine like Sizzle or Core CSS * Implementing a custom solution using a different algorithm or data structure * Using a framework or library specifically designed for performance optimization, such as React or Angular In conclusion, the `Closest API` benchmark is testing the performance of the `closest` method in two approaches: direct DOM access and library-based solution. The use of Cosmos.js suggests that the library-based approach may provide benefits like optimized performance and caching, but it also introduces an additional dependency.
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