Benchmark: Blob vs TextEncoder

Script Preparation code:

iterations = 1000;
function randomStringGen(n) {
    let strings = [];
    for (let i = 0; i < n; i++) {
      let s = Math.random().toString(36).substring(2, 15) + Math.random().toString(36).substring(2, 15);
      strings[i] = s;
    }
    return strings;
}
var randomStrings = randomStringGen(iterations);
var encoder = new TextEncoder();

Tests:

TextEncoder
var j = 0; for (let i = 0; i < iterations; i++) { var str = randomStrings[i % iterations]; encoder.encode(str).length }
Blob
var j = 0; for (let i = 0; i < iterations; i++) { var str = randomStrings[i % iterations]; new Blob([str]).size }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
TextEncoder
Blob

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

Let's break down what's being tested in the provided JSON.

**Benchmark Comparison:**

The benchmark compares two approaches to encode strings:

1. **TextEncoder**: A built-in JavaScript API that provides an efficient way to convert strings to binary data using UTF-8 encoding.
2. **Blob**: An object representing a blob of binary data, created by wrapping a string in `new Blob([str])`.

**Options Compared:**

The benchmark compares the performance of these two approaches:

* Encoding time: How long it takes to encode a string using TextEncoder and Blob.
* Execution frequency: The number of executions per second for each approach.

**Pros and Cons:**

1. **TextEncoder**:
	* Pros:
		+ Efficient and optimized for UTF-8 encoding.
		+ Provides better support for international characters and Unicode normalization.
	* Cons:
		+ May have slower initial startup time due to its built-in JavaScript implementation.
2. **Blob**:
	* Pros:
		+ Can be faster for small strings, as it avoids the overhead of UTF-8 encoding.
		+ Provides more control over the binary data representation.
	* Cons:
		+ Less efficient than TextEncoder for large or Unicode-encoded strings.
		+ May require additional processing steps to ensure correct encoding.

**Library/Functionality:**

The `TextEncoder` API is a built-in JavaScript library, and its purpose is to provide an efficient way to convert strings to binary data using UTF-8 encoding. The `Blob` constructor creates a new blob object, which represents a binary data structure that can be stored or transmitted.

**Special JS Feature/Syntax:**

None of the code uses any special JavaScript features or syntax that's not widely supported.

**Other Considerations:**

* **UTF-8 Encoding**: Both approaches use UTF-8 encoding, but TextEncoder is more optimized for this encoding.
* **Blob Size**: The blob size calculation can be affected by the specific string being encoded and the used encoding scheme.

**Alternatives:**

Other alternatives to consider when working with binary data in JavaScript include:

1. **Buffer**: A built-in Node.js module that provides a low-level buffer implementation.
2. **Uint8Array**: A typed array that represents an array of unsigned 8-bit integers, often used for binary data storage or manipulation.
3. **Web Workers**: Can be used to offload computationally expensive tasks, such as encoding large strings, to separate threads.

Keep in mind that the choice of alternative depends on the specific use case and requirements of your project.

Latest run results:

Run details: (Test run date: 15 days ago)

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:131.0) Gecko/20100101 Firefox/131.0

Browser/OS: Firefox 131 on Linux

View result in a separate tab

Test name	Executions per second
TextEncoder	5797.0 Ops/sec
Blob	394.6 Ops/sec

Related benchmarks:

Blob vs TextEncoder (version: 0)

Comparing performance of: TextEncoder vs Blob

Created: one year ago by: Guest

Jump to the latest result

TextEncoder

Blob

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):