Benchmark: padLeft comparison

HTML Preparation code:

<script>
const buffer = crypto.getRandomValues(new Uint8Array(16))

const z = '0'
const zz = '00'

function pad(pad, str) {
  if (typeof str === 'undefined') 
    return pad

  return (pad + str).slice(-pad.length)
}
</script>

Tests:

padLeft
for (let string = '', i = 0; i < buffer.length; i++) { string += buffer[i].toString(16).padStart(2, z) }
slice
for (let string = '', i = 0; i < buffer.length; i++) { string += (zz + buffer[i].toString(16)).slice(-2) }
slice template literal
for (let string = '', i = 0; i < buffer.length; i++) { string += `${zz}${buffer[i].toString(16)}`.slice(-2) }
pad
for (let string = '', i = 0; i < buffer.length; i++) { string += pad(zz, buffer[i].toString(16)) }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
padLeft
slice
slice template literal
pad

Fastest: N/A

Slowest: N/A

Latest run results:

No previous 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 dive into the world of JavaScript benchmarks!

**Benchmark Overview**

The provided benchmark is designed to compare the performance of different ways to pad a string with leading zeros in JavaScript. The test cases are:

1. `padLeft`: appending the specified number of leading zeros using the `padStart()` method.
2. `slice`: using the `slice()` method to extract the last two characters and repeat them to fill the desired length.
3. `slice template literal`: similar to `slice`, but uses a template literal to create the repeated string.
4. `pad`: using a custom `pad()` function to repeat the leading zeros.

**Library: None**

There are no external libraries used in this benchmark.

**Special JavaScript Feature/Syntax: None**

None of the test cases rely on special JavaScript features or syntax that would affect the performance or interpretation of the code.

**Options Comparison**

Let's analyze each option:

1. **`padLeft` (using `padStart()`)**
	* Pros:
		+ Efficient and straightforward approach.
		+ Utilizes a modern method, making it easy to implement and understand.
	* Cons:
		+ May require additional imports for the `padStart()` method, depending on the environment.
2. **`slice`**
	* Pros:
		+ Native JavaScript method, so no additional imports are needed.
		+ Can be easily optimized or adapted for different use cases.
	* Cons:
		+ Requires manual manipulation of string indices, which can lead to performance issues with large strings.
3. **`slice template literal`**
	* Pros:
		+ Similar to `padLeft`, but using a more modern and expressive syntax.
	* Cons:
		+ May require additional imports or polyfills for the template literals feature.
4. **`pad` (custom function)**
	* Pros:
		+ Allows for flexible and customizable padding behavior.
	* Cons:
		+ Requires explicit implementation, which can lead to overhead and complexity.

**Benchmark Results**

The benchmark results show that `padLeft` (using `padStart()`) is the fastest option, followed closely by `slice template literal`. The `slice` method performs poorly due to its manual indexing approach. The custom `pad()` function falls behind the others in performance.

**Alternatives**

Other alternatives for padding strings could include:

1. Using a library like `string-pad` or `pad-sizes` for more advanced and flexible padding options.
2. Implementing a custom padding algorithm using bitwise operations, which might be faster than string manipulation methods.
3. Using other string concatenation approaches, such as using an array of padded characters and joining them.

Keep in mind that the best approach will depend on specific use cases and performance requirements.

Related benchmarks:

padLeft comparison (version: 0)

Comparing performance of: padLeft vs slice vs slice template literal vs pad

Created: 6 years ago by: Guest

Jump to the latest result

padLeft

slice

slice template literal

pad

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):