Benchmark: Search an option inside a dataList

HTML Preparation code:

<datalist id="colours">
    <option value="Red" data-id="1">
    <option value="Blue" data-id="2">
    <option value="Green" data-id="3">
    <option value="Black" data-id="4">
    <option value="White" data-id="5">
</datalist>
<script src='https://cdnjs.cloudflare.com/ajax/libs/jquery/3.3.1/jquery.js'></script>

Script Preparation code:

var rightSelection = "White";
var wrongSelection = "Greeny";
var options = document.getElementById("colours").options;
var $options = $("#colours");
var array = Array.prototype.map.call(options, function (option) {
  return option.value;
});
var hashmap = Array.prototype.reduce.call(options, function (obj, option) {
    if (!obj[option.value]) { obj[option.value] = true; }
    return obj;
}, {});

Tests:

Using each (jQuery)
function findColour (color) { var finded = false; $options.find("option").each(function() { if (this.value === color) { finded = true; return false; } }); return finded; } findColour(rightSelection); findColour(wrongSelection);
Using find (jQuery)
function findColour (color) { return $options.find("option[value='" + color + "']").length; } findColour(rightSelection); findColour(wrongSelection);
Search inside an Array of Strings (Vanilla JS)
function findColour (color) { return array.indexOf(color) >= 0; } findColour(rightSelection); findColour(wrongSelection);
Search inside a HashMap of Strings (Vanilla JS)
function findColour (color) { return hashmap[color]; } findColour(rightSelection); findColour(wrongSelection);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Using each (jQuery)
Using find (jQuery)
Search inside an Array of Strings (Vanilla JS)
Search inside a HashMap of Strings (Vanilla JS)

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

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

**What is being tested?**

The benchmark tests four different methods to search for an option inside a `datalist` element:

1. **Using `each` (jQuery)**: This method iterates over the options in the datalist using jQuery's `find` method and checks if the selected value matches the target color.
2. **Using `find` (jQuery)**: Similar to the previous method, but uses jQuery's `find` method with a filter to check for matching values.
3. **Search inside an Array of Strings (Vanilla JS)**: This method converts the options into an array and uses the `indexOf` method to search for the target color.
4. **Search inside a HashMap of Strings (Vanilla JS)**: This method creates a hashmap from the options and searches for the target color by looking up its value in the hashmap.

**Options compared**

Each test case measures the execution time of each approach on different hardware configurations, including browser type, device platform, operating system, and number of executions per second. The results are then compared to determine which method is fastest.

**Pros and cons of each approach**

1. **Using `each` (jQuery)**:
	* Pros: This method is concise and easy to read.
	* Cons: It may be slower than other methods because jQuery's `find` method can be more resource-intensive.
2. **Using `find` (jQuery)**:
	* Pros: Similar to the previous method, but with a filter, which can improve performance by reducing the number of options checked.
	* Cons: Still uses jQuery's `find` method, which may incur additional overhead.
3. **Search inside an Array of Strings (Vanilla JS)**:
	* Pros: This method is fast and efficient because it uses native JavaScript methods like `indexOf`.
	* Cons: It assumes the number of options is limited, which may not be the case in real-world scenarios.
4. **Search inside a HashMap of Strings (Vanilla JS)**:
	* Pros: Similar to the previous method, but with the added benefit of storing and retrieving values from an object, making it more suitable for larger datasets.
	* Cons: Creating a hashmap can incur additional overhead, which may slow down the search process.

**Other considerations**

1. **jQuery dependence**: Two out of four test cases rely on jQuery, which may not be desirable in all scenarios where jQuery is not available or enabled.
2. **DOM manipulation**: The benchmark involves manipulating the DOM to set up the datalist element and options. This can add overhead to the tests.

**Alternatives**

Other methods for searching inside a `datalist` element could include:

1. Using native JavaScript methods like `includes`, which is supported in modern browsers.
2. Implementing a custom data structure, such as a trie or prefix tree, to store and retrieve options efficiently.
3. Utilizing a library like Lodash or Underscore.js for utility functions that can aid in searching.

Keep in mind that the choice of method depends on the specific requirements and constraints of your project.

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36

Browser/OS: Chrome 128 on Windows

View result in a separate tab

Test name	Executions per second
Using each (jQuery)	122579.7 Ops/sec
Using find (jQuery)	77947.4 Ops/sec
Search inside an Array of Strings (Vanilla JS)	1837482.5 Ops/sec
Search inside a HashMap of Strings (Vanilla JS)	1909541.5 Ops/sec

Related benchmarks:

Search an option inside a dataList (version: 0)

Different methods to check if an option is inside a dataList

Comparing performance of: Using each (jQuery) vs Using find (jQuery) vs Search inside an Array of Strings (Vanilla JS) vs Search inside a HashMap of Strings (Vanilla JS)

Created: 5 years ago by: Registered User

Jump to the latest result

Using each (jQuery)

Using find (jQuery)

Search inside an Array of Strings (Vanilla JS)

Search inside a HashMap of Strings (Vanilla JS)

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):