Benchmark: localeCompare vs collator

Script Preparation code:

var a = "NODE 42";
var b = "node 42";

var collator = new Intl.Collator();

Tests:

localCompare
a.localeCompare(b, undefined, {sensitivity: 'accent'}) === 0
collator
collator.compare(a, b) === 0

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
localCompare
collator

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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**What is being tested?**

The provided benchmark compares the performance of two approaches to compare strings: `localeCompare` and `collator.compare`. Both methods are used to determine if two strings are equal, but they differ in their implementation.

**Options being compared:**

1. **localeCompare**: This method uses the Unicode Collation Algorithm (UCA) to compare strings. It takes into account the locale of the comparison, which can affect the ordering of characters.
2. **collator.compare**: This method also uses the UCA, but it provides more control over the comparison process through its options, such as sensitivity and language.

**Pros and Cons:**

1. **localeCompare**:
	* Pros:
		+ Simple to use and understand.
		+ Fast and efficient.
	* Cons:
		+ Sensitive to locale settings, which can lead to inconsistent results across different regions.
		+ Not as customizable as `collator.compare`.
2. **collator.compare**:
	* Pros:
		+ Highly customizable through its options.
		+ Can handle edge cases and special characters more accurately than `localeCompare`.
	* Cons:
		+ More complex to use and understand, especially for beginners.
		+ Slower than `localeCompare` due to the additional overhead of its options.

**Library:**

The `collator` library is used in this benchmark. Its purpose is to provide a flexible way to compare strings based on various languages and locales. The `Intl.Collator` API is part of the modern JavaScript standard and is supported by most browsers.

**Special JS feature or syntax:**

This benchmark uses the `Intl.Collator` API, which was introduced in ECMAScript 2019 (ES10). This feature allows for more accurate and locale-aware string comparisons. The use of `sensitivity: 'accent'` option also demonstrates its ability to handle accentuated characters.

**Other alternatives:**

If you need a simple way to compare strings without considering locale or special characters, you can use the built-in `===` operator, which uses a simple ASCII comparison algorithm. However, this approach is less reliable and may not work correctly for all edge cases.

Another alternative is to use a library like `js-string-locale`, which provides a more comprehensive set of string comparison functions based on locale settings.

**Benchmark preparation code explanation:**

The provided Script Preparation Code initializes two variables, `a` and `b`, with different strings. The line `var collator = new Intl.Collator();` creates an instance of the `Intl.Collator` API, which will be used to compare the strings in subsequent test cases.

**Individual test cases explanation:**

The benchmark consists of two test cases:

1. **localCompare**: This test case compares the result of calling `localeCompare` on the variables `a` and `b`. The `undefined` parameter is not necessary, as `localeCompare` will default to its own locale if no argument is provided.
2. **collator**: This test case compares the result of calling `compare` on the same variables using the `collator.compare` method. The options object `{sensitivity: 'accent'}` is used to ensure that accented characters are handled correctly.

The benchmark is designed to measure the performance difference between these two approaches, which can be useful when working with strings in a locale-aware context.

Related benchmarks:

localeCompare vs collator (version: 0)

Comparing performance of: localCompare vs collator

Created: 3 years ago by: Guest

Jump to the latest result

localCompare

collator

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):